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Food for Agile Thought #518: Fujifilm vs Kodak, Product Premortem, Product Discovery Bias, Traditional Change Failure

by Stefan Wolpers | 2025-11-07 News

TL; DR: Fujifilm vs Kodak — Food for Agile Thought #518

Welcome to the 518th edition of the Food for Agile Thought newsletter, shared with 40,351 peers. This week, Martin Eriksson applies his decision stack to Fujifilm vs Kodak, showing how Fujifilm avoided Kodak’s fate by aligning strategy and execution. Jason Fried reflects on why great products feel whole and personal, shaped more by craft than management, while Laura Klein calls out the chaos of DIY AI adoption and urges ops teams to step in with structure. Steve Newman questions AI’s readiness for complex, adaptive work, and Christina Wodtke highlights how premortems surface risks before they hit delivery.

Next, David Pereira offers 21 practical templates to help product managers focus on value without slipping into a performative process. Jana Paulech unpacks how bias distorts product discovery and calls for better documentation and broader input. Also, Chris Loy redefines prompt engineering as context engineering, applying software principles to AI workflows, and Sebastian Raschka surveys emerging LLM alternatives with different trade-offs. Simon Powers warns that change efforts fall flat when they rely on outdated mental models.

Lastly, John Cutler shows how Shape Up uses constraints to channel focus and pace when paired with clear intent. Andi Roberts advocates for small-scale experiments to navigate uncertainty and build learning cultures. Additionally, Peter Hunter and Elena Stojmilova share how decentralizing architecture decisions improved team ownership and speed, and Allan Kelly reframes OKRs as tools for autonomy and alignment. Finally, Mike Fisher suggests treating organizational change as a Hero’s Journey to unite teams around purpose.

Food for Agile Thought #518: Fujifilm vs Kodak, Product Premortem, Product Discovery Bias, Traditional Change Failure — Age-of-Product.com

Product Development AI Risks: When Your Leverage Becomes Your Liability

by Stefan Wolpers | 2025-11-02 Agile and ScrumAgile Transition

TL; DR: How Your Advantage Becomes Your Achilles Heel

AI can silently erode your product operating model by replacing empirical validation with pattern-matching shortcuts and algorithmic decision-making. This article on product development AI risks, along with its corresponding video, identifies three consolidated risk categories and practical boundaries to maintain customer-centric judgment while leveraging AI effectively.

Product Development AI Risks: When Your Leverage Becomes Your Liability — Age-of-Product.com

Food for Agile Thought #517: The AI Boom-or-Bust Situation, Project vs. POM Debate, Testing Business Ideas, Agile’s Future?

by Stefan Wolpers | 2025-10-31 News

TL; DR: AI Boom-or-Bust Situation — Food for Agile Thought #517

Welcome to the 517th edition of the Food for Agile Thought newsletter, shared with 40,352 peers. This week, Grant Harvey dissects the AI boom-or-bust situation, warning of inflated valuations built on shaky economics. Petra Wille urges teams to switch deliberately between product and project thinking, guided by feedback loops, and John Cutler skewers empty calls for simplification that mask vague agendas and stalled change. Len Greski declares the “Agile” brand broken but defends its principles, while David Pereira’s chat with David J. Bland highlights lessons learned and why systems thinking now takes center stage.

Next, Maarten Dalmijn highlights how delaying decisions can preserve options and reduce regret. Raghav Sethi critiques AI bloat in products, eroding trust. Richard Mironov warns of inflated AI valuations and urges sharper judgment. At the same time, Eli Pariser reports from a private AI summit where hype meets unease. Also, Johanna Rothman reminds us that truth-telling requires cultural permission and consistent leadership.

Lastly, Jeremy Korst, Stefano Puntoni, and Sonny Tambe show that generative AI delivers ROI at scale, though skills still lag. Teresa Torres explains how Claude Code lets non-technical users build reusable AI workflows, and Maik Seyfert exposes the illusion of team autonomy rooted in structural control. Also, Mark Levison targets bloated backlogs with story maps. Finally, Nadzeya Stalbouskaya urges leaders to treat architectural debt as a strategic risk rather than hide it under the label of technical debt.

Food for Agile Thought #517: AI Boom-or-Bust Situation, Project vs. POM Debate, Testing Business Ideas, Agile’s Future? Age-of-Product.com

AI 4 Agile v2 — I Need Your Input on What to Build Next

by Stefan Wolpers | 2025-10-26 Agile and Scrum

TL; DR: What AI 4 Agile Topics Shall I Cover in Version 2?

Version 1 of the AI for Agile Practitioners Online Course just closed its first two weeks with 250 new students. The feedback has been direct and useful: Practitioners value the realistic MegaBrain.io scenario work, the quiz design that tests judgment rather than memorization, and the focus on ethics and responsible AI alongside practical application. So far, that’s good, but AI 4 Agile v2 seriously needs your input: What topics shall I cover?

👉 Hence, please join the AI 4 Agile v2 Survey; it won’t take more than 3 minutes.

AI 4 Agile v2 — I Need Your Input on What to Build Next — Age-of-Product.com

Food for Agile Thought #516: Sabotaging AI, Feature Flags for Discovery, AI Slop Field Guide, Upskilling Teams

by Stefan Wolpers | 2025-10-24 News

TL; DR: Sabotaging AI — Food for Agile Thought #516

Welcome to the 516th edition of the Food for Agile Thought newsletter, shared with 40,359 peers. This week, Jenn Spykerman addresses unknowingly sabotaging AI according to a 1944 manual, masquerading endless committees, perfectionism, and cautious delays as good governance. Leah Tharin challenges claims that LLMs can stand in for real customer insight, warning that dashboards can fuel strategy theater, while John Cutler connects prioritization to strategic leverage and power dynamics. Jing Hu reframes AI failure stats as early-stage noise, and Duncan Brown warns that AI favors the visible over the messy, human glue that makes effective teams work.

Next, Chetan Kapoor shows how eBay uses feature flags as discovery tools to validate demand early and surface usability issues. Kyle Poyar critiques popular SaaS pricing models and shares fixes that avoid complete overhauls. Ethan Mollick maps the current AI landscape with practical guidance on tools, tiers, and tactics. At the same time, Zvi Mowshowitz highlights key takeaways from Karpathy’s AGI views, and James Shore reframes engineering accountability through product bets instead of features and deadlines.

Lastly, Anthropic’s Claude receives “skills” as modular guides for specialized tasks, now open-sourced on GitHub. One author explores how great teams grow through targeted support and bold delegation, and Jeff Sauro and Jim Lewis dissect NPS claims, separating useful signals from misleading noise. Charlie Guo calls out the creeping signs of AI-generated content and its cost to authenticity. Finally, Karen Dahut presents Google Skills, a vast new learning platform for AI and tech upskilling.

Food for Agile Thought #516: Sabotaging AI, Feature Flags for Discovery, AI Slop Field Guide, Upskilling Teams — Age-of-Product.com

The Dangerous Middle: Agile Roles That AI Will Erode First

by Stefan Wolpers | 2025-10-19 News

TL; DR: Dangerous Middle and the Future of Scrum Masters and Agile Coaches

Peter Yang, a renowned product leader, argues that AI will split product roles into two groups: Generalists who can prototype end-to-end with AI, and specialists in the top 5% of their fields. Everyone else in the dangerous middle risks being squeezed.

How does this apply to agile practitioners: Scrum Masters, Product Owners, Agile Coaches, and transformation leads? It does, with important nuances.

The Dangerous Middle: Peter Yang's Product Role Framework Reveals About the Future of Agile Practitioners — Age-of-Product.com