by Stefan Wolpers|FeaturedAgile TransitionLean and Product
TL; DR: The “Agile to the Product Operating Model” Survey Results
Between August 2 and August 10, 2026, 48 practitioners participated in my Agile to Product Operating Model (POM) survey, which tries to shed light on what is actually changing.
Let me summarize the answers for you: the reported transformations change decision-making less than the Cagan framework suggests. Where respondents report improvements, they appear in delivery and collaboration rather than in business results. Unfortunately, the human side of the transition is the least encouraging part of the answers.
Take all the following information with a grain of salt, given that the sample size is so small. (I recall the good times when 1,000 to 2,000 people would participate in a Scrum master salary report, but those times seem to be over, despite my asking 39,000 people for their contributions via a newsletter.)
Thesis: Product operating model transformations mostly change vocabulary and organizational structure while leaving the decision system, who decides what gets built, on what evidence, at what speed, largely untouched. AI is changing product decisions independently of POM transformations.
Your team already delegates work to AI: reports, research, customer feedback analysis, stakeholder communication, or parts of operational workflows.
But can you answer these questions without improvising?
What may AI decide, and what must remain a human decision?
What does “good enough” mean for this particular work?
Who verifies the result before somebody acts on it?
Who checks whether the delegation still works after the model or workflow changes?
If those answers live in one person’s head, or nowhere, your problem is no longer prompting. You have a delegation problem.
The A3 Delegation System gives you a practical way to decide what AI may do, hand over the work clearly, define acceptable results, and inspect the delegation over time.
During two hands-on sessions, you will apply the system to a workflow. You will leave with a clear understanding of how to apply the A3 Delegation System to your workflows so that team members or stakeholders can understand, challenge, and continue your AI delegation work. Everything you learn is directly applicable to your situation the next day. The class is in English.
You learned to prompt, and your organization learned to spend. Unfortunately, few organizations have learned to connect the two. That is where the AI4Agile online course comes in.
An AI operating capability exists when delegated work can be reproduced without its original creator, meets an explicit quality standard, follows a defensible execution path, has a named owner, and is inspected often enough to detect drift. The AI4Agile Online Course V3 teaches practitioners how to build one, independent of a particular AI model, and still, there is no coding required. The course is in English. 🇬🇧
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.
by Stefan Wolpers|FeaturedAgile and ScrumAgile Transition
Using AI at Work Does Not Mean You Understand It
Many agile practitioners use ChatGPT at work. That does not mean they understand AI well enough to trust your own judgment. The problem is not that agile practitioners ignore AI. The problem is that many already use it confidently without knowing where their judgment breaks down. The free AI4Agile Foundational Assessment measures precisely this skill gap. (Download your access file below.)
The assessment comprises 40 scenario-based questions. It does not ask for definitions, but puts you into situations that agile coaches, product managers, and Scrum Masters face every week: weak prompting producing generic output, misleading data analysis, questionable agent output, and, possibly, organizational pressure to treat AI output as “good enough” to go with it.
Most people who use AI do not fail because they lack knowledge, but because they cannot distinguish between plausible outputs and trustworthy judgment. But see for yourself!
by Stefan Wolpers|FeaturedAgile and ScrumAgile Transition
TL;DR: The A3 Handoff Canvas
The A3 Framework helps you decide whether AI should touch a task (Assist, Automate, Avoid). The A3 Handoff Canvas covers what teams often skip: how to run the handoff without losing quality or accountability. It is a six-part workflow contract for recurring AI use: task splitting, inputs, outputs, validation, failure response, and record-keeping. If you cannot write one part down, that is where errors and excuses will enter.
The Handoff Canvas closes a gap in a useful pattern: from an unstructured prompt to applying the A3 framework to document decisions with the A3 Handoff Canvas, to creating transferable Skills, potentially leading to building agents.
by Stefan Wolpers|FeaturedAgile and ScrumAgile Transition
TL; DR: The A3 Framework
The A3 Framework categorizes AI delegation before you prompt: Assist (AI drafts, you actively review and decide), Automate (AI executes under explicit rules and audit cadences), or Avoid (stays entirely human when failure would damage trust or relationships). Most AI training teaches better prompting. The A3 Framework teaches the prior question: Should you be prompting at all? Categorize first, then prompt.
by Stefan Wolpers|FeaturedAgile and ScrumAgile Transition
TL; DR: Why the Brand Failed While the Ideas Won
Your LinkedIn feed is full of it: Agile is dead. They’re right. And, at the same time, they’re entirely wrong.
The word is dead. The brand is almost toxic in many circles; check the usual subreddits. But the principles? They’re spreading faster than ever. They just dropped the name that became synonymous with consultants, certifications, transformation failures, and the enforcement of rituals.
You all know organizations that loudly rejected “Agile” and now quietly practice its core ideas more effectively than any companies running certified transformation programs. The brand failed. The ideas won.
TL; DR: The Scrum Master Interview Guide to Identify Genuine Scrum Masters
In this comprehensive Scrum Master Interview guide, we delve into 97 critical questions that can help distinguish genuine Scrum Masters from pretenders during interviews. We designed this selection to evaluate the candidates’ theoretical knowledge, practical experience, and ability to apply general Scrum and “Agile “principles effectively in real-world scenarios—as outlined in the Scrum Guide or the Agile Manifesto. Ideal for hiring managers, HR professionals, and future Scrum teammates, this guide provides a toolkit to ensure that your next Scrum Master hire is truly qualified, enhancing your team’s agility and productivity.
If you are a Scrum Master currently looking for a new position, please check out the “Preparing for Your Scrum Master Interview as a Candidate” section below.
So far, this Scrum Master interview guide has been downloaded more than 25,000 times.
TL; DR: 82 Product Owner Interview Questions to Avoid Imposters
If you are looking to fill a position for a Product Owner in your organization, you may find the following 82 interview questions useful to identify the right candidate. They are derived from my sixteen years of practical experience with XP and Scrum, serving both as Product Owner and Scrum Master and interviewing dozens of Product Owner candidates on behalf of my clients.
So far, this Product Owner interview guide has been downloaded more than 10,000 times.
TL; DR: Upcoming AI 4 Agile Workshops, Scrum Training Classes, and Events
Age-of-Product.com’s parent company — Berlin Product People GmbH — offers Scrum training classes authorized by Scrum.org, Liberating Structures workshops, and hybrid training of Professional Scrum and Liberating Structures. The training classes are offered both in English and German.
Check out the upcoming timetable of training classes, workshops, meetups, and other events below and join your peers.
TL; DR: Engineering Culture Trends 2026 — Food for Agile Thought #556
Welcome to the 556th edition of the Food for Agile Thought newsletter, shared with 35,389 peers. This week, Shane Hastie, Ben Linders, and the InfoQ panel present the Engineering Culture 2026 survey, including Jim Highsmith’s warning that Agile failures forecast AI failures. Teresa Torres suggests testing assumptions rather than ideas, while Adrienne Tan separates capability frameworks for humans and machines. Sayash Kapoor and Arvind Narayanan gave agents six days to conduct real research and watched as experts rejected the papers. Also, Dror Poleg translates 50 AI terms, and Tim O’Reilly asks Dan Guido how he moved staff who resisted changing to an AI-native organization.
Next, Nigel Thurlow argues that organizations struggle to see problems, not to solve them, because workarounds become normal. Ranjan Dash and Suresh Chandran fight the same blind spot in B2B innovation, sharing an approach that maps problems before anyone ideates. Zvi Mowshowitz then widens the frame, ranking AI beliefs by three pills. Also, Shlok Khemani reverse-engineers ChatGPT Work, while Giles Edwards-Alexander cuts agent token costs by 83% through refactoring.
Lastly, Patrick Collison asks you to record six forecasts on the US economy in 2031, since predictions get uncomfortable once written down. Jeff Gothelf offers three questions to address the AI-written roadmap your VP presented, and Vaughn Tan calls AI a mirror rather than a rival, warning that we hand over meaning-making. Finally, John Cutler suggests better maps hide organizational incoherence, while Paweł Huryn found a $1.80 run beat a $104 one across 105 hidden bugs.
The debate over the product operating model (POM) has a data problem. Most of us, including me, argue from the organizations we know.
When I interviewed Marty Cagan, see the article below, he called a Scrum team “quite amateur compared to a professional product team.” I later called the theater version of the shift from Scrum/Agile to POM product washing, a form of “transformation by reprinting business cards.” Consultants generalize from their clients and bloggers from their respondents.
I have not seen a dataset showing what changed across several hundred organizations after they moved beyond Scrum as they had practiced it. That is what this survey is for. And it takes only three minutes.
Organizations are moving away from “good enough Agile,” while AI reduces the cost of producing software. That change seems uneven, as engineering is hardly free, but a team today can, indeed, build the wrong thing faster and with fewer people, provided a valid credit card is available.
Making product decisions, or having product sense, therefore, matters more than ever.
A POM is supposed to move those decisions closer to customers and give teams problems to solve rather than feature lists to deliver. “Product washing” produces different results: roles are renamed, Scrum events disappear, and approval power stays with the same stakeholders as before.
We have strong opinions about which version is more common. Too bad, we have little comparable data. This is why I ask you to invest 3 minutes of your time and join the “From Agile to the Product Operating Model: What Is Actually Changing?” survey.
The survey asks, for example:
Who is pushing the move toward a product operating model, and what role does AI play?
What changed in delivery speed, customer value, business results, and team morale since switching to a product operating model?
What happened to Scrum or agile events: abandoned, repurposed, or relabeled?
Who decides what gets built today: leaders assigning features or teams investigating problems?
When nobody knows whether an idea is worth building, what settles the question: debate, research, a disposable prototype, or simply shipping it, now that agentic coding has become affordable?
Who Should Answer the “From Agile to the Product Operating Model: What Is Actually Changing?” Survey
I encourage you to take part in the “From Agile to the Product Operating Model: What Is Actually Changing?” survey if you work in or around product development as a product owner, product manager, Scrum master/agile coach, project manager, developer, designer, (product) leader, or consultant.
Your organization does not need to be adopting a product operating model. The survey includes a short route for organizations that are not making that move, and I want those responses, too. (The product operating model already has enough cheerleaders.)
I am particularly interested in organizations that tried a product operating model and later abandoned or reversed the change. Failed experiments rarely appear in conference talks, but they may tell us more than another transformation success story.
What Happens to Your Answers
The survey is anonymous and requires no registration. I will publish the results openly on this blog; the resulting report will be free to everyone.
Learn more about AI Builders with our AI and Scrum training classes, workshops, and events. You can secure your seat directly by following the corresponding link in the table below:
You can book your seat for the training directly by following the corresponding links to the ticket shop. If your organization’s procurement process requires a different purchasing approach, please contact Berlin Product People GmbH directly.
✋ Do Not Miss Out and Learn More about the Product Operating Model — Join the 20,000-plus Strong ‘Hands-on Agile’ Slack Community
I invite you to join the “Hands-on Agile” Slack Community and enjoy the benefits of a fast-growing, vibrant community of agile practitioners from around the world.
TL; DR: Rogue AI Agents — Food for Agile Thought #555
Welcome to the 555th edition of the Food for Agile Thought newsletter, shared with 35,412 peers. This week, Hugo Larcher and colleagues, along with Anthropic’s Frontier Red Team, demonstrate how weak containment enables rogue AI agents to turn tests into real breaches. At the same time, Ethan Mollick reframes agent use as management through permissions, verification, and limited access. Jason Knight and Pavel Samsonov separate faster building from actual learning, Tanner Kohler explains how experiments and reflection develop product sense, and Mark Graban dismantles unsupported claims that most Lean transformations fail.
Next, Richard Mironov argues that AI pushes product work toward choosing what deserves to be built and prepared for sale, while John Cutler warns that redistributed capabilities may weaken judgment, apprenticeship, context, and resilience. Andon Labs shows Claude Opus 5 outperforming rivals while deceiving and overreaching, and Christina Wodtke frames design careers as choices among compromise, resistance, departure, or reinvention. Also, Neale Mahoney, Erika McEntarfer, and Karsen Wahal find job losses limited but entry-level hiring softer.
Lastly, Jeff Gothelf grounds AI discovery in current workarounds and decisions, while Drew Breunig warns that hand-tuned prompts create brittle systems unless teams use evaluations, modular specifications, and automation. Dwarkesh Patel expects soaring compute demand to reward efficient models, as Tomasz Tunguz examines Microsoft’s flexible but OpenAI-dependent strategy. Finally, Joost Minnaar shifts the lens from infrastructure to organization, showing how repeated daily commitments sustain cohesion without middle managers.
TL; DR: Reusing Agile Artifacts to Avoid Accumulating AI Debt
In this video from the 76th Hands-on Agile Meetup, I walk you through the A3 Delegation System and show how it helps avoid AI debt by borrowing artifacts and practices from Agile, such as the Definition of Done and Retrospectives. If you’d like to download the corresponding canvases (the artifacts of the A3 Delegation System), you can do so below.
You will get a full set of PDFs, along with the guide to the A3 Delegation System, so that you can run the system with your own teams. Enjoy the video and let me know whether you consider the A3 Delegation System useful.
TL; DR: Toyota Production System — Food for Agile Thought #554
Welcome to the 554th edition of the Food for Agile Thought newsletter, shared with 35,428 peers. This week, Nigel Thurlow presents the Toyota Production System (TPS) as a disciplined whole, a lesson Pavel Samsonov and Ash Maurya extend to product work: faster AI delivery only magnifies incoherence without workflow thinking, customer evidence, and validation. Zvi Mowshowitz shows the darker side of unchecked AI optimization, while Steve Newman questions its societal impact to date. Barry O’Reilly ties these concerns to leadership, urging redesign of workflows, judgment, decision rights, and accountability before scale amplifies weak systems. (Again, history rhymes; remember “Agile?”)
Next, Leah Tharin reframes activation as the full path from first touch to lasting habit, a view that challenges vanity metrics. Also, Michele Zanini and Gary Hamel question inflated AI claims, and Zanna Iscenko and Scott Strand add evidence of broad but shallow adoption. Chris Chinchilla’s Nokia history warns of what happens when execution lags behind change, and Johanna Rothman brings the remedy to focus: visualize work, expose delays, finish one thing, and reject the rest.
Lastly, Ant Murphy separates strategic leverage from strategy labels, while Steven Sinofsky argues that restricting AI model distillation would entrench incumbents, when more competition should be the goal. David Burkus turns to management, showing how leaders can shield teams from chaos without hiding uncertainty. Addy Osmani warns that AI-automated code creates comprehension debt, and John Cutler connects the themes: AI succeeds only when teams understand the work, retain human judgment, and trust leaders not to weaponize productivity gains.
