Mid Level Managers

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};

<\/p>\n\n\n\n

Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

References-<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

References-<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

References-<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

References-<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

Summary<\/strong><\/p>\n\n\n\n

(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

References-<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

Summary<\/strong><\/p>\n\n\n\n

(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

References-<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
The future-proof organization is essentially rooted in Full-Stack Leaders<\/em><\/strong> at all levels. They are beyond typical roles; they are catalysts who can function across a range of dimensions of leadership, connecting strategic intent with actual execution and creating meaningful business impact.<\/p>\n\n\n\n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
The Emergence of the Full-Stack Leader: A Strategic Imperative<\/strong><\/h5>\n\n\n\n
The future-proof organization is essentially rooted in Full-Stack Leaders<\/em><\/strong> at all levels. They are beyond typical roles; they are catalysts who can function across a range of dimensions of leadership, connecting strategic intent with actual execution and creating meaningful business impact.<\/p>\n\n\n\n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
In such an environment, dependency on traditional paradigms of leadership can hinder agility, suppress innovation, can lead to lots of friction points thus leading to organizational drag. The challenge is not merely to manage, but to nurture a new generation of leaders capable of functioning, and high-performing in such complexity.<\/p>\n\n\n\n
The Emergence of the Full-Stack Leader: A Strategic Imperative<\/strong><\/h5>\n\n\n\n
The future-proof organization is essentially rooted in Full-Stack Leaders<\/em><\/strong> at all levels. They are beyond typical roles; they are catalysts who can function across a range of dimensions of leadership, connecting strategic intent with actual execution and creating meaningful business impact.<\/p>\n\n\n\n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Incomprehensibility:<\/strong> The explosion of data, the intricacy & complexity of modern technology stacks, the need to stitch together lots of special components or services, and the rapidly shifting customer requirements and expectations make it extremely hard to see clear patterns or foresee the desired outcome, resulting in paralysis of analysis and lost opportunities.<\/li>\n<\/ul>\n\n\n\n
In such an environment, dependency on traditional paradigms of leadership can hinder agility, suppress innovation, can lead to lots of friction points thus leading to organizational drag. The challenge is not merely to manage, but to nurture a new generation of leaders capable of functioning, and high-performing in such complexity.<\/p>\n\n\n\n
The Emergence of the Full-Stack Leader: A Strategic Imperative<\/strong><\/h5>\n\n\n\n
The future-proof organization is essentially rooted in Full-Stack Leaders<\/em><\/strong> at all levels. They are beyond typical roles; they are catalysts who can function across a range of dimensions of leadership, connecting strategic intent with actual execution and creating meaningful business impact.<\/p>\n\n\n\n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Non-linearity:<\/strong> Product development paths today are rarely linear. Due to ongoing emergent requirements and interdependent complexities, development methodologies and new ways of working, no matter what labels are assigned to them (Agile, Hybrid), will make traditional controls to be stifling innovation and responsiveness.<\/li>\n\n\n\n
Incomprehensibility:<\/strong> The explosion of data, the intricacy & complexity of modern technology stacks, the need to stitch together lots of special components or services, and the rapidly shifting customer requirements and expectations make it extremely hard to see clear patterns or foresee the desired outcome, resulting in paralysis of analysis and lost opportunities.<\/li>\n<\/ul>\n\n\n\n
In such an environment, dependency on traditional paradigms of leadership can hinder agility, suppress innovation, can lead to lots of friction points thus leading to organizational drag. The challenge is not merely to manage, but to nurture a new generation of leaders capable of functioning, and high-performing in such complexity.<\/p>\n\n\n\n
The Emergence of the Full-Stack Leader: A Strategic Imperative<\/strong><\/h5>\n\n\n\n
The future-proof organization is essentially rooted in Full-Stack Leaders<\/em><\/strong> at all levels. They are beyond typical roles; they are catalysts who can function across a range of dimensions of leadership, connecting strategic intent with actual execution and creating meaningful business impact.<\/p>\n\n\n\n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Anxiety:<\/strong> Constant demands for innovation, ever-changing customer requirements, pressure of quick iterations, and perpetual fear of disruption all contribute to rising stress and burnout even for highly skilled technical teams, impacting talent retention and psychological safety.<\/li>\n\n\n\n
Non-linearity:<\/strong> Product development paths today are rarely linear. Due to ongoing emergent requirements and interdependent complexities, development methodologies and new ways of working, no matter what labels are assigned to them (Agile, Hybrid), will make traditional controls to be stifling innovation and responsiveness.<\/li>\n\n\n\n
Incomprehensibility:<\/strong> The explosion of data, the intricacy & complexity of modern technology stacks, the need to stitch together lots of special components or services, and the rapidly shifting customer requirements and expectations make it extremely hard to see clear patterns or foresee the desired outcome, resulting in paralysis of analysis and lost opportunities.<\/li>\n<\/ul>\n\n\n\n
In such an environment, dependency on traditional paradigms of leadership can hinder agility, suppress innovation, can lead to lots of friction points thus leading to organizational drag. The challenge is not merely to manage, but to nurture a new generation of leaders capable of functioning, and high-performing in such complexity.<\/p>\n\n\n\n
The Emergence of the Full-Stack Leader: A Strategic Imperative<\/strong><\/h5>\n\n\n\n
The future-proof organization is essentially rooted in Full-Stack Leaders<\/em><\/strong> at all levels. They are beyond typical roles; they are catalysts who can function across a range of dimensions of leadership, connecting strategic intent with actual execution and creating meaningful business impact.<\/p>\n\n\n\n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Brittleness:<\/strong> Technology shifts and market pressures can render traditional strategies and product roadmaps obsolete at a frightening speed, illustrating the susceptibility of even robust systems and processes.<\/li>\n\n\n\n
Anxiety:<\/strong> Constant demands for innovation, ever-changing customer requirements, pressure of quick iterations, and perpetual fear of disruption all contribute to rising stress and burnout even for highly skilled technical teams, impacting talent retention and psychological safety.<\/li>\n\n\n\n
Non-linearity:<\/strong> Product development paths today are rarely linear. Due to ongoing emergent requirements and interdependent complexities, development methodologies and new ways of working, no matter what labels are assigned to them (Agile, Hybrid), will make traditional controls to be stifling innovation and responsiveness.<\/li>\n\n\n\n
Incomprehensibility:<\/strong> The explosion of data, the intricacy & complexity of modern technology stacks, the need to stitch together lots of special components or services, and the rapidly shifting customer requirements and expectations make it extremely hard to see clear patterns or foresee the desired outcome, resulting in paralysis of analysis and lost opportunities.<\/li>\n<\/ul>\n\n\n\n
In such an environment, dependency on traditional paradigms of leadership can hinder agility, suppress innovation, can lead to lots of friction points thus leading to organizational drag. The challenge is not merely to manage, but to nurture a new generation of leaders capable of functioning, and high-performing in such complexity.<\/p>\n\n\n\n
The Emergence of the Full-Stack Leader: A Strategic Imperative<\/strong><\/h5>\n\n\n\n
The future-proof organization is essentially rooted in Full-Stack Leaders<\/em><\/strong> at all levels. They are beyond typical roles; they are catalysts who can function across a range of dimensions of leadership, connecting strategic intent with actual execution and creating meaningful business impact.<\/p>\n\n\n\n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
\n
Brittleness:<\/strong> Technology shifts and market pressures can render traditional strategies and product roadmaps obsolete at a frightening speed, illustrating the susceptibility of even robust systems and processes.<\/li>\n\n\n\n
Anxiety:<\/strong> Constant demands for innovation, ever-changing customer requirements, pressure of quick iterations, and perpetual fear of disruption all contribute to rising stress and burnout even for highly skilled technical teams, impacting talent retention and psychological safety.<\/li>\n\n\n\n
Non-linearity:<\/strong> Product development paths today are rarely linear. Due to ongoing emergent requirements and interdependent complexities, development methodologies and new ways of working, no matter what labels are assigned to them (Agile, Hybrid), will make traditional controls to be stifling innovation and responsiveness.<\/li>\n\n\n\n
Incomprehensibility:<\/strong> The explosion of data, the intricacy & complexity of modern technology stacks, the need to stitch together lots of special components or services, and the rapidly shifting customer requirements and expectations make it extremely hard to see clear patterns or foresee the desired outcome, resulting in paralysis of analysis and lost opportunities.<\/li>\n<\/ul>\n\n\n\n
In such an environment, dependency on traditional paradigms of leadership can hinder agility, suppress innovation, can lead to lots of friction points thus leading to organizational drag. The challenge is not merely to manage, but to nurture a new generation of leaders capable of functioning, and high-performing in such complexity.<\/p>\n\n\n\n
The Emergence of the Full-Stack Leader: A Strategic Imperative<\/strong><\/h5>\n\n\n\n
The future-proof organization is essentially rooted in Full-Stack Leaders<\/em><\/strong> at all levels. They are beyond typical roles; they are catalysts who can function across a range of dimensions of leadership, connecting strategic intent with actual execution and creating meaningful business impact.<\/p>\n\n\n\n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
The leadership archetypes and ways of thinking encouraged and probably worked during more stable periods are being challenged ever more by the very nature of our world today. We are operating in a BANI world<\/strong> (B<\/strong>rittle, A<\/strong>nxious, N<\/strong>on-linear, I<\/strong>ncomprehensible). This acronym is not just in theory; it is very close to the reality of the pervasive problems that rule product development organizations today:<\/p>\n\n\n\n
\n
Brittleness:<\/strong> Technology shifts and market pressures can render traditional strategies and product roadmaps obsolete at a frightening speed, illustrating the susceptibility of even robust systems and processes.<\/li>\n\n\n\n
Anxiety:<\/strong> Constant demands for innovation, ever-changing customer requirements, pressure of quick iterations, and perpetual fear of disruption all contribute to rising stress and burnout even for highly skilled technical teams, impacting talent retention and psychological safety.<\/li>\n\n\n\n
Non-linearity:<\/strong> Product development paths today are rarely linear. Due to ongoing emergent requirements and interdependent complexities, development methodologies and new ways of working, no matter what labels are assigned to them (Agile, Hybrid), will make traditional controls to be stifling innovation and responsiveness.<\/li>\n\n\n\n
Incomprehensibility:<\/strong> The explosion of data, the intricacy & complexity of modern technology stacks, the need to stitch together lots of special components or services, and the rapidly shifting customer requirements and expectations make it extremely hard to see clear patterns or foresee the desired outcome, resulting in paralysis of analysis and lost opportunities.<\/li>\n<\/ul>\n\n\n\n
In such an environment, dependency on traditional paradigms of leadership can hinder agility, suppress innovation, can lead to lots of friction points thus leading to organizational drag. The challenge is not merely to manage, but to nurture a new generation of leaders capable of functioning, and high-performing in such complexity.<\/p>\n\n\n\n
The Emergence of the Full-Stack Leader: A Strategic Imperative<\/strong><\/h5>\n\n\n\n
The future-proof organization is essentially rooted in Full-Stack Leaders<\/em><\/strong> at all levels. They are beyond typical roles; they are catalysts who can function across a range of dimensions of leadership, connecting strategic intent with actual execution and creating meaningful business impact.<\/p>\n\n\n\n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
In the fast-paced era of high-technology product development, there is one question that is increasingly facing executive leadership: Are our organizational leaders fully prepared to lead results in a world ruled by relentless change?<\/em><\/strong><\/p>\n\n\n\n
The leadership archetypes and ways of thinking encouraged and probably worked during more stable periods are being challenged ever more by the very nature of our world today. We are operating in a BANI world<\/strong> (B<\/strong>rittle, A<\/strong>nxious, N<\/strong>on-linear, I<\/strong>ncomprehensible). This acronym is not just in theory; it is very close to the reality of the pervasive problems that rule product development organizations today:<\/p>\n\n\n\n
\n
Brittleness:<\/strong> Technology shifts and market pressures can render traditional strategies and product roadmaps obsolete at a frightening speed, illustrating the susceptibility of even robust systems and processes.<\/li>\n\n\n\n
Anxiety:<\/strong> Constant demands for innovation, ever-changing customer requirements, pressure of quick iterations, and perpetual fear of disruption all contribute to rising stress and burnout even for highly skilled technical teams, impacting talent retention and psychological safety.<\/li>\n\n\n\n
Non-linearity:<\/strong> Product development paths today are rarely linear. Due to ongoing emergent requirements and interdependent complexities, development methodologies and new ways of working, no matter what labels are assigned to them (Agile, Hybrid), will make traditional controls to be stifling innovation and responsiveness.<\/li>\n\n\n\n
Incomprehensibility:<\/strong> The explosion of data, the intricacy & complexity of modern technology stacks, the need to stitch together lots of special components or services, and the rapidly shifting customer requirements and expectations make it extremely hard to see clear patterns or foresee the desired outcome, resulting in paralysis of analysis and lost opportunities.<\/li>\n<\/ul>\n\n\n\n
In such an environment, dependency on traditional paradigms of leadership can hinder agility, suppress innovation, can lead to lots of friction points thus leading to organizational drag. The challenge is not merely to manage, but to nurture a new generation of leaders capable of functioning, and high-performing in such complexity.<\/p>\n\n\n\n
The Emergence of the Full-Stack Leader: A Strategic Imperative<\/strong><\/h5>\n\n\n\n
The future-proof organization is essentially rooted in Full-Stack Leaders<\/em><\/strong> at all levels. They are beyond typical roles; they are catalysts who can function across a range of dimensions of leadership, connecting strategic intent with actual execution and creating meaningful business impact.<\/p>\n\n\n\n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
Rethinking Leadership in Times of Volatility and Uncertainty<\/strong><\/h5>\n\n\n\n
In the fast-paced era of high-technology product development, there is one question that is increasingly facing executive leadership: Are our organizational leaders fully prepared to lead results in a world ruled by relentless change?<\/em><\/strong><\/p>\n\n\n\n
The leadership archetypes and ways of thinking encouraged and probably worked during more stable periods are being challenged ever more by the very nature of our world today. We are operating in a BANI world<\/strong> (B<\/strong>rittle, A<\/strong>nxious, N<\/strong>on-linear, I<\/strong>ncomprehensible). This acronym is not just in theory; it is very close to the reality of the pervasive problems that rule product development organizations today:<\/p>\n\n\n\n
\n
Brittleness:<\/strong> Technology shifts and market pressures can render traditional strategies and product roadmaps obsolete at a frightening speed, illustrating the susceptibility of even robust systems and processes.<\/li>\n\n\n\n
Anxiety:<\/strong> Constant demands for innovation, ever-changing customer requirements, pressure of quick iterations, and perpetual fear of disruption all contribute to rising stress and burnout even for highly skilled technical teams, impacting talent retention and psychological safety.<\/li>\n\n\n\n
Non-linearity:<\/strong> Product development paths today are rarely linear. Due to ongoing emergent requirements and interdependent complexities, development methodologies and new ways of working, no matter what labels are assigned to them (Agile, Hybrid), will make traditional controls to be stifling innovation and responsiveness.<\/li>\n\n\n\n
Incomprehensibility:<\/strong> The explosion of data, the intricacy & complexity of modern technology stacks, the need to stitch together lots of special components or services, and the rapidly shifting customer requirements and expectations make it extremely hard to see clear patterns or foresee the desired outcome, resulting in paralysis of analysis and lost opportunities.<\/li>\n<\/ul>\n\n\n\n
In such an environment, dependency on traditional paradigms of leadership can hinder agility, suppress innovation, can lead to lots of friction points thus leading to organizational drag. The challenge is not merely to manage, but to nurture a new generation of leaders capable of functioning, and high-performing in such complexity.<\/p>\n\n\n\n
The Emergence of the Full-Stack Leader: A Strategic Imperative<\/strong><\/h5>\n\n\n\n
The future-proof organization is essentially rooted in Full-Stack Leaders<\/em><\/strong> at all levels. They are beyond typical roles; they are catalysts who can function across a range of dimensions of leadership, connecting strategic intent with actual execution and creating meaningful business impact.<\/p>\n\n\n\n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
A CXO Perspective<\/strong><\/p>\n\n\n\n
Rethinking Leadership in Times of Volatility and Uncertainty<\/strong><\/h5>\n\n\n\n
In the fast-paced era of high-technology product development, there is one question that is increasingly facing executive leadership: Are our organizational leaders fully prepared to lead results in a world ruled by relentless change?<\/em><\/strong><\/p>\n\n\n\n
The leadership archetypes and ways of thinking encouraged and probably worked during more stable periods are being challenged ever more by the very nature of our world today. We are operating in a BANI world<\/strong> (B<\/strong>rittle, A<\/strong>nxious, N<\/strong>on-linear, I<\/strong>ncomprehensible). This acronym is not just in theory; it is very close to the reality of the pervasive problems that rule product development organizations today:<\/p>\n\n\n\n
\n
Brittleness:<\/strong> Technology shifts and market pressures can render traditional strategies and product roadmaps obsolete at a frightening speed, illustrating the susceptibility of even robust systems and processes.<\/li>\n\n\n\n
Anxiety:<\/strong> Constant demands for innovation, ever-changing customer requirements, pressure of quick iterations, and perpetual fear of disruption all contribute to rising stress and burnout even for highly skilled technical teams, impacting talent retention and psychological safety.<\/li>\n\n\n\n
Non-linearity:<\/strong> Product development paths today are rarely linear. Due to ongoing emergent requirements and interdependent complexities, development methodologies and new ways of working, no matter what labels are assigned to them (Agile, Hybrid), will make traditional controls to be stifling innovation and responsiveness.<\/li>\n\n\n\n
Incomprehensibility:<\/strong> The explosion of data, the intricacy & complexity of modern technology stacks, the need to stitch together lots of special components or services, and the rapidly shifting customer requirements and expectations make it extremely hard to see clear patterns or foresee the desired outcome, resulting in paralysis of analysis and lost opportunities.<\/li>\n<\/ul>\n\n\n\n
In such an environment, dependency on traditional paradigms of leadership can hinder agility, suppress innovation, can lead to lots of friction points thus leading to organizational drag. The challenge is not merely to manage, but to nurture a new generation of leaders capable of functioning, and high-performing in such complexity.<\/p>\n\n\n\n
The Emergence of the Full-Stack Leader: A Strategic Imperative<\/strong><\/h5>\n\n\n\n
The future-proof organization is essentially rooted in Full-Stack Leaders<\/em><\/strong> at all levels. They are beyond typical roles; they are catalysts who can function across a range of dimensions of leadership, connecting strategic intent with actual execution and creating meaningful business impact.<\/p>\n\n\n\n
Why \"Full-Stack\" and what is it?<\/em><\/strong> Solo skills won't be enough in a BANI world as high-technology product development leadership demands an unbroken set of competencies:<\/p>\n\n\n\n
\n
Business Acumen:<\/strong> To recognize opportunity through market volatility and translate strategic vision into real-world, value-driven outcomes.<\/li>\n\n\n\n
People Leadership<\/strong>: To create unity, inspire through change, foster innovation, build trusting relationships, and create psychological safety during times of anxiety and change.<\/li>\n\n\n\n
Self-Mastery:<\/strong> To cultivate resilience, clarity, and confidence amidst uncertainty and ongoing pressure.<\/li>\n<\/ul>\n\n\n\n
These connected competencies are a paradigm shift, enabling organizations to escape reactivity to become proactive in shaping their future and long-term value creation for their stakeholders. As this is at be at all levels, we also bring forth the idea of creating a Leadership pipeline.<\/p>\n\n\n\n
Deconstructing the Full-Stack Leader: The Layers of the Stack of Critical Capabilities<\/strong><\/h5>\n\n\n\n
Developing Full-Stack Leaders is an executive leadership responsibility to address the most significant aspects of leadership to succeed in the BANI world. These competencies are grouped into three interdependent layers:<\/p>\n\n\n\n
Layer <\/strong>1. Creating an Impact on Business:<\/strong><\/p>\n\n\n\n
This dimension fosters a complete business perspective, allowing leaders to move beyond their functional silos. They are not just proficient at managing today's deadlines and operations but also at developing the capability for making strategic choices. Discovering means of innovation and creating value by connecting day-to-day activities to overall organizational goals. In a brittle environment, these types of leaders can quickly change strategies and product roadmaps, converting threats into opportunities. They can understand the power of newer and emerging technologies for example, AI. They possess foresight and critical thinking to manage complexity, driving purposeful decisions to achieve tangible business value rather than freezing in paralysis.<\/p>\n\n\n\n
Layer 2. Leading Others:<\/strong><\/p>\n\n\n\n
This is about mastering team activation and people dynamics in teams and across the larger organization, and becoming capable of empowering teams, establishing psychological safety, and mobilizing collaboration. It encompasses the ability to lead with influence, work with differences constructively, manage conflict, and to collaborate effectively with peers. In a non-linear world, leaders skilled at \"Leading Others\" create spaces where teams can experiment, learn, and develop. They turn potential tension into productive conversation, developing resilient units that can navigate uncertain cycles of growth.<\/p>\n\n\n\n
Layer 3. Leading Self:<\/strong> This core dimension grounds a leader's inner foundation. It includes developing self-awareness, emotional intelligence, mindfulness, and a strong professional presence. The aim is to establish confidence and habits that build trust and credibility, allowing authentic and effective leadership in pressure situations. The ever-changing nature and inherent unknowability of the BANI world can be emotionally and mentally draining. High \"Leading Self\" capability leaders possess mental toughness and emotional stability to stay clear, make good decisions, and stay grounded amidst uncertainty, and be beacons of stability and trust for others.<\/p>\n\n\n\n
Principles for Effective Leadership Development for the BANI world<\/strong><\/h5>\n\n\n\n
Effective transition to leadership in a BANI world cannot be done through generic training in isolated topics. It requires deep contextualization and experience-based learning events and bring back learning to the workplace. It begins with a well-defined understanding of an organization's strategic goals and specific leadership needs.<\/p>\n\n\n\n
We believe that one of the most powerful ways to develop Full-Stack Leaders is through a well-crafted program that can take leaders on an impactful learning journey:<\/p>\n\n\n\n
\n
Immersive Learning Methodology:<\/strong> Highly Interactive and engaging workshops, real-life scenario-based case studies, interactive role-plays, group assignments, peer-to-peer learning, and business simulations with hands-on exposure and direct applicability can make an impact on learning. These learnings can remain with leaders for much longer.<\/li>\n\n\n\n
Stakeholder-Centered Development<\/strong>: Incorporate the 360^{o<\/sup> feedback for leaders and use this as an opportunity for uncovering blind spots and launching development plans.<\/li>\n\n\n\n}
Personalized Coaching:<\/strong> Individualized, one-to-one guidance to correct specific leadership deficiencies and chart personal development aligned with the organizational imperative.<\/li>\n\n\n\n
Reflection opportunities:<\/strong> Offer reflection opportunities for Leaders to showcase learnings to their stakeholders.<\/li>\n<\/ul>\n\n\n\n
Future-Ready Organizations: Return on Investment?<\/strong><\/h5>\n\n\n\n
Investment in developing Full-Stack Leaders creates multi-layered results in the organization, to bring about both individual change and to create impactful business results:<\/p>\n\n\n\n
At the Individual Leader Level (Mindset & Behavioural Shift): Leaders emerging out of this transition are demonstrating concrete changes in their style and capabilities:<\/p>\n\n\n\n
\n
Value & Impact-Mindset:<\/strong> They form a broader strategic mindset, making bold, value-creating choices that drive innovation and result in achieving long-term business goals even in the event of market incomprehensibility.<\/li>\n\n\n\n
Resilient & Adaptive Presence:<\/strong> They develop greater levels of self-awareness, emotional intelligence, and resiliency so that they are able to lead with greater presence, confidence, and adaptability across the inherent brittleness and non-linearity of the BANI world.<\/li>\n\n\n\n
Empathetic & Collaborative Influence:<\/strong> They establish psychological safety and inspire high-performing teams, efficiently managing variations and promoting collaboration across complex organizational landscapes, confining anxiety and tension.<\/li>\n<\/ul>\n\n\n\n
At the Organizational Results Level (Business Impact): These leaders can lead to measurable and tangible improvements in your organization's performance:<\/p>\n\n\n\n
\n
Increased Organizational Agility & Strategic Alignment:<\/strong> Cross-functional collaboration significantly enhances, allowing for better ways of working, enhanced strategic alignment, and increased responsiveness to changing market conditions.<\/li>\n\n\n\n
Higher Innovation & Market Responsiveness:<\/strong> Businesses have faster cycles of innovation, better product quality, and faster time-to-market, leading to enhanced market responsiveness as well as customer satisfaction.<\/li>\n\n\n\n
Better Talent Engagement & Resilience:<\/strong> Psychological safety and enabled leadership result in a culture that gives rise to more engaged employees, more talent retention, and the development of genuinely resilient delivery organizations.<\/li>\n<\/ul>\n\n\n\n
Conclusion: The Need for Strategic Leadership Transformation<\/strong><\/strong><\/h5>\n\n\n\n
The age of just managing is giving way to the imperative of holistic leadership. To leaders of high-technology product development companies, the question is no longer whether your leadership must change, but how deeply and strategically that change should happen.<\/em><\/strong> It is time to develop a leadership pipeline, not just managing current processes, but shaping the future, seizing the challenges of the BANI world as a fertile ground to create business impact and sustained growth.<\/p>\n\n\n\n
Full-Stack Leadership investment is not a cost of doing business; it is a strategic imperative that can directly improve performance, promote innovation, and build organizational resilience to help navigate and thrive in an increasingly uncertain world.<\/p>\n\n\n\n
<\/p>\n","post_title":"Navigating the BANI World: An Imperative for Full-Stack Leadership","post_excerpt":"This white paper examines why a comprehensive set of leadership competencies: Creating Business Impact, Leading Others, and developing Self-Mastery is a strategic necessity. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"navigating-the-bani-world-an-imperative-for-full-stack-leadership","to_ping":"","pinged":"","post_modified":"2025-06-02 18:08:38","post_modified_gmt":"2025-06-02 12:38:38","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=1000300","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":999540,"post_author":"24","post_date":"2025-01-10 17:14:53","post_date_gmt":"2025-01-10 11:44:53","post_content":"\n
$\"\"$ <\/figure>\n\n\n\n
Background<\/strong><\/p>\n\n\n\n
There is an ongoing debate about whether Agile will survive the rapid development of Artificial Intelligence (AI). Some have even pronounced it dead. I believe this debate arises from a misunderstanding of either Agile, AI, or both.<\/p>\n\n\n\n
As Carlota Perez, author of Technological Revolutions and Financial Capital<\/em>, aptly states: \u201cArtificial intelligence is almost certainly revolutionary in the sense that it will spawn new technology platforms, transform or eliminate many industries, and create new ones. But it must be understood as belonging to a larger, more mature technological revolution that began a half-century ago.\u201d Perez explains that AI is best understood as a significant development within the ongoing information and communications technology (ICT) revolution, which began in the 1970s with the advent of the microprocessor.<\/p>\n\n\n\n
This perspective resonates with the rapid advancements in AI tools and their transformative impact across industries. When we loosely refer to \u201cAI,\u201d we are inherently pointing to the evolution of AI tools, deeply intertwined with the continuous progress in computing technology.<\/p>\n\n\n\n
Agile, on the other hand, has been the cornerstone of modern software development, championing customer focus through collaboration, self-managed teams, iterative progress, and adaptation. Since its inception, Agile methodologies like Scrum, Kanban, and Scaled Agile have revolutionized how teams capture customer requirements, build software, and deliver it effectively. At its core, Agile is people-driven. It relies on defined roles, disciplined practices, and the creation of artifacts. However, Agile also incorporates tools\u2014tools that are evolving rapidly alongside advancements in AI.<\/p>\n\n\n\n
AI, being data-driven, automates repetitive tasks, predicts outcomes, and optimizes processes. While there is speculation about AI surpassing human intelligence, I believe we are still in a phase of stabilizing AI models. For now, AI remains a powerful tool in human hands. Current reports indicate better productivity but decreased outcomes due to less perfect tools.<\/p>\n\n\n\n
With this understanding, I present my thoughts on how NextGen Agile could evolve alongside Newgen AI. For the rest of the article, when I say \u2018AI\u2019, I mean AI tools e.g., Jira Align, Microsoft PowerBI, GitHub copilot etc., I explore this evolution from two perspectives: the lens of Agile values and the end-to-end software development lifecycle.<\/p>\n\n\n\n\n\n\n\n
Agile Values and AI<\/strong><\/p>\n\n\n\n
Agile has clearly articulated the value of individuals and interactions<\/strong> over processes and tools. The need for collaboration, consensus-building, teamwork, and self-management lies at the root of Agile. Agile formalizes interactions through ceremonies like sprint planning and stand-ups while encouraging more people-to-people interactions through smaller teams.<\/p>\n\n\n\n
The other Agile values - Working Software -<\/strong> Emphasizes rapid development and iterative feedback cycles; Responding to Change-<\/strong> Encourages adaptability through Agile workflows and Customer Collaboration-<\/strong> Focusses on customer needs over contractual obligations.<\/p>\n\n\n\n
How are these values likely to change? Let us look at some of the frameworks.<\/p>\n\n\n\n
Scrum: AI-Driven Workflows<\/strong><\/p>\n\n\n\n
\n
Sprint Planning:<\/strong> AI can analyse past sprint data to recommend achievable sprint goals and match capacity and skills, reducing the effort needed for pre-planning and planning.<\/li>\n<\/ul>\n\n\n\n
\n
Daily Stand-ups:<\/strong> AI can flag blockers and provide progress updates, reducing the frequency of meetings and saving time.<\/li>\n\n\n\n
Backlog Refinement:<\/strong> AI analyses market trends, user feedback, and technical debt for easier prioritization.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI-driven insights offer organized feedback loops and improved tracking.<\/li>\n<\/ul>\n\n\n\n
Kanban: AI-Enhanced Flow and Visualization<\/strong><\/p>\n\n\n\n
\n
Dynamic WIP Limits:<\/strong> AI adjusts WIP limits in real-time to prevent bottlenecks, cutting cycle time and improving flow.<\/li>\n\n\n\n
Retrospectives:<\/strong> AI identifies recurring blockers and recommends process improvements.<\/li>\n\n\n\n
Demand Forecasting:<\/strong> AI forecasts demand based on incoming ticket patterns, aligning work capacity to demand.<\/li>\n<\/ul>\n\n\n\n
Scaled Agile Workflows with AI<\/strong><\/p>\n\n\n\n
\n
Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n
Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n
AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n
AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n
High Impact Stages<\/strong><\/p>\n\n\n\n
\n
Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n
Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n
Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n
\n
Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
Summary<\/strong><\/p>\n\n\n\n
Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n
As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n
(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n
References-<\/p>\n\n\n\n
https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n
AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n
https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n
Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
Middle Managers & Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
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