Age-of-Product.com

To Switch, or Not to Switch the AI Model

by Stefan Wolpers | 2026-10-11 Featured Agile and ScrumAgile Transition

TL;DR: The Hidden Cost of Switching AI Models

A new AI model arrives that is cheaper per token, scores better on benchmarks, and seems to require nothing more than a setting change. However, the token bill shows only part of the cost of switching AI models. There is also the effort to check whether your workflows, for example, the one to create status reports for stakeholders, still produce outputs in line with your AI Definition of Done. More often than not, this task remains unaligned with the decision to switch AI models.

In the worst case, switching AI models behind a business workflow can raise operating costs despite cheaper tokens, because business cases can miss the revalidation effort.

Thesis: This article explains the recurring operational cost of switching AI models behind a business workflow: why the revalidation effort may disappear from upgrade decisions, how to screen a switch, and how Agile teams use an AI Definition of Done, test evidence, and an accountable owner to stay in control.

To Switch, or Not to Switch the AI Model, or: The Hidden Costs of Switching AI Models - by Stefan Wolpers, Age-of-Product.com

Food for Agile Thought 565: AI Age Manager, 10X Revenue by 10X Code? Budgeting AI Spending, Team Happiness a Goal?

by Stefan Wolpers | 2026-10-09 Featured News

TL; DR: AI Age Manager — Food for Agile Thought #565

Welcome to the 565th edition of the Food for Agile Thought newsletter, shared with 35,263 peers. This week, Camille Fournier calls middle management’s AI-era obituary premature, much as Gergely Orosz sees planning and tests outlasting handwritten code. The point that leaders confuse visibility with understanding fits AI transcripts, which Teresa Torres and Petra Wille fear can become weapons. Abundance misleads, too: more code isn’t more revenue for David Pereira and Rich Mironov, a refined backlog can mean the wrong product for Christopher Cummings, and Pavel Samsonov rejects synthetic users’ false certainty.

Next, Jillian Vordick and Stephanie Stamm find only 11% of businesses forecast AI spending accurately, and Kyle Poyar suggests how to make bills predictable. Clear plans are rare, too: Nick Graveline sees AI adoption stalling on storytelling, not tooling. Andrew Chen doubts agents inherently create network effects, yet as they do legwork, Andrej Karpathy sees human work shifting toward understanding, which anchors Alex Ewerlöf’s rejection of ‘coding is solved’: you can’t answer for code you don’t understand.

Lastly, Charity Majors ties psychological safety to uncomfortable learning, not comfort, and Maarten Dalmijn likewise raises the bar rather than designing for the least competent. Mark Levison blames situations instead: most ‘difficult’ colleagues are good people trapped by incentives or missing strategy. Jeff Gothelf sees this gap turning AI mandates into chaos and recommends spending one afternoon on goals and OKRs. Andi Roberts similarly reads matrix power beyond titles, mapping who can affect an outcome.

Food for Agile Thought 565: AI Age Manager, 10X Revenue by 10X Code? Budgeting AI Spending, Team Happiness a Goal? Age-of-Product.com

From Agile to the Product Operating Model: What Practitioners Say Is Actually Changing

by Stefan Wolpers | 2026-08-10 Featured Agile 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.)

Agile to the Product Operating Model Survey Results: What Practitioners Say Is Actually Changing – Age-of-Product.com

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.

A3 Delegation System Founding Workshop — September 28-29, 2026

by Stefan Wolpers | 2026-07-22 Featured Agile and Scrum

Turn An AI Workflow Into an Explicit Delegation

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.

A3 Delegation System Founding Workshop — September 28-29, 2026 — by Stefan Wolpers Berlin-Product-People.com

From Prompting to Operating Capability: The AI4Agile Online Course Release v3

by Stefan Wolpers | 2026-07-19 Featured Agile and Scrum

TL; DR: AI4Agile v3 Is Live

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. 🇬🇧

📺 Watch me walk you through the AI4Agile online course, pointing to the new modules.

AI4Agile Course v3: Master AI for Agile Practitioners — Berlin-Product-People.com

👉 AI4Agile V3 launches today, July 20, 2026, at the introductory price of $149, including a 14-Day Money Back Guarantee. (On July 28, it will be $249.)

The AI4Agile Foundational Assessment: A Free Practical Judgment Benchmark for Agile Practitioners

by Stefan Wolpers | 2026-03-28 Featured Agile 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!

AI4Agile Foundational Assessment: A Free Practical Judgment Benchmark for Agile Practitioners - Age-of-Product.com

The A3 Handoff Canvas: Six Questions That Turn AI Delegation Into a Repeatable Workflow

by Stefan Wolpers | 2026-02-15 Featured Agile 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.

The A3 Handoff Canvas: Six Questions That Turn AI Delegation with the A3 Framework Into a Repeatable Workflow — Age-of-Product.com

The A3 Framework: Assist, Automate, Avoid — A Decision System for AI Delegation

by Stefan Wolpers | 2026-01-11 Featured Agile 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.

The A3 Framework: Assist, Automate, Avoid — A Decision System for AI Delegation to Preserve Professionalism — Age-of-Product.com

Agile Is Dead, Long Live Agility

by Stefan Wolpers | 2025-12-07 Featured Agile 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.

So why are we still fighting about the label?

Free Ebook: 97 Scrum Master Interview Questions to Identify Suitable Candidates

by Stefan Wolpers | 2022-06-17 Featured Agile and Scrum

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.

Scrum Master Interview — How to Prepare Yourself to Stand Out — Age-of-Product.com

Hiring: 92 Scrum Product Owner Interview Questions to Avoid Agile Imposters

by Stefan Wolpers | 2021-09-26 Featured Agile and Scrum

TL; DR: 92 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 92 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.

82 Product Owner Interview Questions to Avoid Imposters — Age-of-Product.com

📅 Upcoming AI 4 Agile Workshops, Scrum Training Classes, and Events

by Stefan Wolpers | 2020-10-10 Featured Workshops

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.

Upcoming Scrum and Liberating Stuctures training classes and workshops — Berlin Product People GmbH

How to Catch AI Delegation Drift Before Your Board Does

by Stefan Wolpers | 2026-10-07 Agile and ScrumAgile Transition

TL;DR: The AI Delegation Audit Webinar Recording

When AI-assisted output still looks fine, it is tempting to conclude the delegation is fine. In my October 6 webinar with Scrum.org on the AI Delegation Audit, I walked through a fictional case in which that belief held for months, then fell apart in a board meeting, and showed the check that would have caught it.

How to Catch AI Delegation Drift Before the Board Does: The Recording of the AI Delegation Audit Webinar - Age-of-Product.com

Thesis: The AI Delegation Audit is a 45- to 60-minute review in the A3 Delegation System, run like a Sprint Retrospective, that checks whether a team’s AI delegations still hold; the post explains its four checks with a fictional case and shares the Scrum.org webinar recording.

Food for Agile Thought 564: AI Pace Accelerating, Product Trio Future, Career Traps for Smart People, Aggregation Theory & Agents

by Stefan Wolpers | 2026-10-02 News

TL; DR: AI Pace Accelerating — Food for Agile Thought #564

Welcome to the 564th edition of the Food for Agile Thought newsletter, shared with 35,278 peers. This week, Simon Willison suggests that the current AI pace exceeds even his predictions, while Jenny Wanger believes it has made the product trio single-player, creating product debt in the process. Dan Shipper proposes a labs team expecting to discard 90% of its work, whereas Teresa Torres and Petra Wille treat innovation as a byproduct, not a goal. Ben Thompson suggests whoever owns your agent becomes the ultimate gatekeeper, yet Madeline Renbarger, M. Sriram, and Tom Dotan report even agentic commerce enthusiasts still want control.

Next, Dror Poleg suggests delegation ties his AI glossary together, and Casey Newton shows its price: OpenAI’s Dots saves him two hours but wants your email and bank account. For delegated code, Addy Osmani fears that the engineer approving it without independent checks becomes the moral crumple zone. Arvind Narayanan and Sayash Kapoor propose AI extinction probabilities are guesses wearing numbers, whereas Paweł Huryn’s analysis of AI subscription benefits rests on API list rates: SuperGrok buys 190x its price.

Lastly, John Cutler suggests your virtues lure you into career traps, while Jonny Miller points out that white-knuckled grinding ends in burnout; let go. Tim Ottinger hopes AI kills ticket culture and revives XP, whereas Viktor Cessan proposes automating internal requests only once volume justifies it. Finally, Fran Noto favors pairing over documentation; the latter captures only a fraction of what experienced people know, and Anuja Karnik and Sumeet Gayathri Moghe suggest trust grows in everyday work, not by orchestrated events.

Food for Agile Thought 564: AI Pace Accelerating, Product Trio Future, Career Traps for Smart People, Aggregation Theory for Agents - Age-of-Product.com

The Jobs Matrix for AI: Four Boxes Instead of Forty Tools

by Stefan Wolpers | 2026-09-27 Agile and ScrumAgile Transition

TL;DR: A 2×2 Matrix on AI for Agile Practitioners

You probably think making sense of AI means keeping up with every new tool, agent, and pricing tier. Steve Jobs faced a similar mess at Apple in 1997, with a dozen versions of the Macintosh, and he fixed it with a two-by-two grid on a whiteboard. Almost 30 years later, the “Jobs Matrix for AI” sorts the AI tool market and, more usefully, the AI use cases of Scrum Masters, Product Owners, Agile Coaches, and anyone else in agile product development.

Replace Consumer and Pro with Team and Organization, and Desktop and Portable with Chatbot and Agent, and you get four boxes that show where a use case belongs, what it takes to move it, and which box should stay empty.

The Jobs Matrix for AI: 4 Boxes Instead of 40 Tools for Agile Practitioners on Delegation and Judgment - Age-of-Product.com

Thesis: This article applies Steve Jobs’ 1997 Consumer/Pro, Desktop/Portable matrix first to the 2026 AI tool market, and then to agile practices, producing a 2×2 matrix that sorts AI use cases by required decision rights and by delegated authority.

Food for Agile Thought 563: Survival of High-impact Ideas, Friction Is Good, Surrendering Agency to AI, AI in Dysfunctional Systems

by Stefan Wolpers | 2026-09-25 News

TL; DR: Survival of High-impact Ideas — Food for Agile Thought #563

Welcome to the 563rd edition of the Food for Agile Thought newsletter, shared with 35,293 peers. This week, Jason Knight and Rich Mironov explore why faster AI-generated code does not create faster revenue, and Itamar Gilad sees a similar limit: output-maxing won’t rescue high-impact ideas from prioritization politics. John Cutler believes AI strips the positive friction forcing teams to think, while Roman Pichler suggests its sprawl lets teams hit targets as the business stagnates. Martin Eriksson would assumption-map leadership’s untested strategy, whereas Pavel Samsonov believes “Claude wrote it” launders slop.

Next, Artificial Analysis finds Claude Opus 5.5 tops its Intelligence Index, while Simon Willison reports that Opus on “Max” thinks so hard it never delivers the Pelican, Simon’s famous test. Addy Osmani suggests deleting “think carefully” prompts and naming when to stop. Diogo Almeida wants models to return typed decisions instead of text, creating Jev, while Charity Majors suggests chatbot answers erode trust when colleagues want your opinion. Also, Mustafa Suleyman believes Anthropic’s constitution fuels anthropomorphism and makes containing AI harder.

Lastly, Nigel Thurlow and Mike Fisher learn from Toyota: Thurlow believes AI visibility changes nothing unless leaders act, while Fisher shows performance is largely systemic. Tim O’Reilly likewise believes going AI native is a human problem. Steve Blank watched day-one AI demos turn MVPs into evidence theater, and James Shore believes AI speed gains can evaporate. Finally, Jeff Gothelf suggests key results track the humans deploying or receiving an agent’s work, not API calls.