Stefan Wolpers

The Scrum-to-POM Transition Is a Role Repositioning Event

by Stefan Wolpers | 2026-04-26 Agile and ScrumAgile Transition

TL; DR: Scrum-to-POM Is Not About Frameworks

Two weeks ago, I asked my audience whether they wanted a short course on moving from Scrum to a Product Operating Model, and 22 answered. That was not the Scrum-to-POM dataset I hoped for, but it was valuable for the conversations. Interestingly, one pattern ran through more than a quarter of the responses: The people writing back were not asking about transformation practices or operating models. They were asking what was about to happen to their jobs.

Let me paraphrase some of their replies: One Agile Coach wrote that their role had already been made redundant, and the internal training their employer offered was not enough. Another asked a blunt question: “What will happen to my role?” A third described leadership, saying they wanted this shift, while their behavior remained inconsistent. A fourth reported confusion about what a product coach actually is. A fifth dismissed the whole discourse as high-level fluff, transformational buzzwords, zero accountability, and vague systems thinking with no teeth.

My takeaway: While the organizational design debate appears to be the surface, the ongoing role repositioning is what the people on the ground are living through.

The Scrum-to-POM Transition Is a Role Repositioning Event; Many Practitioners Haven’t Yet Noticed — Age-of-Product.com

Food for Agile Thought #541: GPT-5.5, Product Managers in Trouble, Product on Speed, Wastes of Lean as a Chance

by Stefan Wolpers | 2026-04-24 News

TL; DR: GPT-5.5 & Product on Speed — Food for Agile Thought #541

Welcome to the 541st edition of the Food for Agile Thought newsletter, shared with 35,619 peers. This week, OpenAI’s GPT-5.5 signals another meaningful capability jump, with Ethan Mollick noting that stronger models and richer tool harnesses now handle serious work, even as creative judgment still exposes AI’s limits. Shopify CTO Mikhail Parakhin, interviewed by swyx, reports near-universal internal AI adoption where review and judgment now matter more than code generation. Cat Wu tells Lenny Rachitsky how Anthropic builds ahead of model readiness and treats mission alignment as real leverage. Stephanie Leue warns that AI magnifies existing product leadership debt, making weak trust and brittle confidence visible faster, while Mike Fisher argues that confident teams stop checking too early and calls for red-teaming as standard procedure, not an afterthought.

Next, James Maxwell argues for funding durable teams around value streams rather than fixed-scope projects, while Lenny Rachitsky and Nikhyl Singhal warn that AI now exposes PMs who manage process theater instead of creating real leverage. Ryan Greenblatt adds another concern: frontier AIs oversell incomplete work and reward-hack hard tasks, making verification unreliable exactly where the stakes rise. Sean Goedecke questions whether anti-AI activism maps onto historical Luddism, and Ian Vanagas proposes hackathons as a protected space where autonomous teams ship real products.

Lastly, Grant Harvey notes power users stack AI tools by job, not brand, with Claude leading on coding, while ChatGPT, Gemini, and Copilot survive on switching costs. Aakash Gupta shows how Claude Routines collapse infrastructure drag but force review discipline, and Mark Graban reframes Lean’s eight wastes as a lens for system problems, not blame. Finally, Lisa Crispin treats AI testing as capability-building, while Alex Singla and co-authors argue that transformation succeeds when leaders earn trust.

Food for Agile Thought #541: GPT-5.5, Product Managers in Trouble, Product on Speed, Wastes of Lean as a Chance – Age-of-Product.com

No More Cheap Claude: Four First Principles of Token Economics in 2026

by Stefan Wolpers | 2026-04-19 Agile and Scrum

TL;DR: Token Economics in the Era of Scarcity

Your Claude Pro subscription hits limits faster than it did in January, as Anthropic quietly re-priced the ceiling, and every AI provider is rationing compute. If you keep working with Claude the way you did six months ago, you are in for a rude awakening. This article gives you four principles that explain how Token Economics actually works, so you can stop accepting the black box and start using your budget deliberately.

No More Cheap Claude: Four First Principles of Token Economics in 2026, Separating Professionals from Amateurs - Age-of-Product.com

Food for Agile Thought #540: Change Needs Glue People, AI Tool FOMO, Product Builders, Stanford’s 2026 AI Report

by Stefan Wolpers | 2026-04-17 News

TL; DR: Change Needs Glue People — Food for Agile Thought #540

Welcome to the 540th edition of the Food for Agile Thought newsletter, shared with 35,625 peers. This week, John Cutler warns that replacing “glue people” with AI ignores the invisible judgment and political navigation that made their work valuable, while Teresa Torres and Petra Wille suggest that resisting AI tool FOMO and focusing on real problems leads to deeper learning. Tugce Erten adds that enterprise buyers pick indispensable products over cheap ones, and Grant Harvey notes that Claude Opus 4.7’s visual reasoning gains come with quietly inflating costs. Stanford HAI’s 2026 AI Index confirms that capability is accelerating rapidly while governance trust crumbles globally, a dynamic Tom Geraghty roots in history: the 1628 Vasa disaster shows that when steep power gradients silence the people closest to the work, avoidable failures become inevitable.

Next, Clay Parker Jones reminds us that good ideas fail because of flawed organizational systems, not flawed thinking, while Roman Pichler and Jeff Gothelf both caution that AI-assisted prototyping and vibe coding cannot replace the discovery judgment at the core of product management. On the infrastructure side, Tomasz Tunguz reports GPU prices up 48% in two months, squeezing startups toward smaller models, as Beatrice Nolan covers growing user backlash over Anthropic quietly dialing back Claude’s default effort. Sarah Gibbons and Kate Moran close the loop: AI agents are already navigating interfaces as users, making accessibility a hard business requirement overnight.

Lastly, a worldwide survey of 425 B2B product managers confirms what many already suspect: strategy loses to operational reactivity, and discovery stays neglected. University of Pennsylvania researchers add a sharper edge, finding that 73% of participants accepted faulty AI reasoning without pushback, a pattern they call “cognitive surrender.” Kevin Kelly captures AI’s paradox with “dumbsmarten,” while Jeff Crume warns that teams rushing AI into production accumulate technical debt across data, models, prompts, and governance. Finally, the Andon Labs team hands their San Francisco retail store to an AI named Luna, surfacing uncomfortable questions about transparency and AI managing humans.

Food for Agile Thought #540: Change Needs Glue People, AI Tool FOMO, Product Builders, Stanford’s 2026 AI Report - Age-of-Product.com

10 Scrum Master Interview Questions for the AI Era

by Stefan Wolpers | 2026-04-11 Agile and ScrumAgile Transition

TL; DR: AI & Scrum Master Interview Questions

AI tools are reshaping how Scrum Teams work, and Scrum Masters who cannot coach their teams through this shift are not ready for 2026. This article presents ten Scrum Master interview questions that test whether a candidate can facilitate AI adoption without losing self-management. As usual, each question includes guidance on answers and red flags. The questions are drawn from the seventh edition of the 97 Scrum Master Interview Questions guide.

10 Scrum Master Interview Questions for the AI Era — Age-of-Product.com

Food for Agile Thought #539: Sam Altmann? Bottom-Up Roadmaps, Cycles of Disruption, The Last Four Jobs

by Stefan Wolpers | 2026-04-10 News

TL; DR: Sam Altmann — Food for Agile Thought #539

Welcome to the 539th edition of the Food for Agile Thought newsletter, shared with 35,623 peers. This week, Ronan Farrow and Andrew Marantz investigate Sam Altman’s leadership at OpenAI, exposing a pattern of deception and safety trade-offs, while Ajeya Cotra predicts AI research parity could arrive by 2028, and Annie Vella reports from a retreat where nobody had AI figured out yet. On the product side, Stephanie Leue questions why leaders borrow other people’s styles instead of finding their own, and Janna Bastow warns that backlog-driven roadmaps create an illusion of progress. Also, Maarten Dalmijn proposes that fewer rules and better guardrails unlock real team performance.

Next, Packy McCormick warns against lazily comparing AI labs to Amazon, since these companies face direct competitors running nearly identical strategies. Tomasz Tunguz offers a 2×2 matrix that helps leaders sort AI strategy work by demand ceiling and loop type, and Itamar Gilad explores why product discovery keeps breaking down internally and proposes that teams time-box it but never skip it. On the technical side, Zvi Mowshowitz covers Anthropic’s Claude Mythos model, which found critical security vulnerabilities across every major OS and browser. Paweł Huryn breaks down Claude Code pricing after Anthropic cut third-party access, and Gergely Orosz hosts Kent Beck and Martin Fowler as they trace parallels between past tech disruptions and today’s AI shift, including why TDD matters more now than ever.

Lastly, John Cutler suggests that AI won’t fix broken product funnels but will amplify whatever dynamics already exist, and Jeff Gothelf warns that SAFe’s rigid ceremonies become catastrophic because AI development demands rapid hypothesis testing. Yoni Rechtman envisions AI-native companies organizing around four archetypes instead of traditional roles, and Kyle Poyar identifies five storytelling archetypes that cut through AI-generated noise. Finally, Jenny Wanger reminds us that offshore team frustrations run both ways and that trust, not process documentation, is the actual fix.