TL; DR: Slowing Down with AI — Food for Agile Thought #542
Welcome to the 542nd edition of the Food for Agile Thought newsletter, shared with 35,608 peers. This week, Mario Zechner advocates for slowing down with AI, warning that unsupervised coding agents compound errors faster than teams can fix them. Stephanie Leue shows how AI-driven speed tempts teams to skip discovery, incurring a hidden “Alignment Tax,” while Jenny Wanger and Michael Goitein find lasting advantage in internal capabilities, not copyable features. Mark Nottingham flags AI agents bypassing browser-level protections, Wharton’s Blueprint examines barriers to adoption, and Joost Minnaar uses the Titanic to show how silos filter critical signals.
Next, Teresa Torres and Petra Wille challenge the reflex to centralize decisions when uncertainty hits, arguing that real leadership sets direction and builds trust. Pawel Brodzinski extends that theme to AI-generated specs that look complete yet erode the human communication that teams need. Maxim Massenkoff shares Anthropic’s survey of 81,000 users, revealing that early-career workers worry most about displacement. Matthew Littlehale recounts replacing Scrum with Shape Up, and Andrej Karpathy reframes LLMs as a new computing paradigm requiring human judgment throughout.
Lastly, Steven J. Vaughan-Nichols warns that enterprise AI lock-in runs deeper than executives admit, with failed migrations and rising costs compounding quickly, while Kevin Kelly frames this instability as part of a broader “Age of Ambiguity” that demands radical adaptability. Dave Snowden surfaces a foundational tension within the CRP tradition between facilitated practice and radical process ontology. On the practical side, Michael Crist guides non-technical professionals through setting up Claude Cowork, while OpenAI’s GPT-5.5 prompt guidance shifts toward outcome-first instructions over process-heavy prompts.
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🏆 The Tip of the Week: Slowing Down with AI
: Thoughts on slowing the fuck down
Mario Zechner proposes that coding agents compound errors at unsustainable rates when left unsupervised, and that developers need to slow down, stay in the code, and maintain discipline instead of delegating all decisions to AI.
🎯 Product
: Why your team keeps shipping products nobody buys
Stephanie Leue proposes that AI-powered speed tempts teams to skip discovery, killing the go-to-market alignment that used to happen naturally. She introduces the “Alignment Tax” as the hidden cost of that shortcut.
and : 📺 Command and Control
Teresa Torres and Petra Wille explore why companies default to command-and-control leadership in times of uncertainty, and why strong leadership means setting direction and building trust rather than centralizing every decision.
: Build an AI edge your competitors can’t copycat
Jenny Wanger and Michael Goitein propose that a lasting AI advantage comes from enhancing internal capabilities across speed, consistency, scale, and skill rather than shipping customer-facing AI features that competitors can quickly copy.
: Conway’s Law Teaches a Grim Lesson About AI in Product Development
Pawel Brodzinski suggests that AI-generated specs can give the impression of completeness, potentially reducing the human communication that teams need. Conway’s Law predicts one result: more fragmented, incoherent products.
🧠 Artificial Intelligence
: What’s Missing in the ‘Agentic’ Story
Mark Nottingham proposes that AI agents lack the user protection that Web browsers provide through standards and collective bargaining, leaving users exposed to unchecked corporate interests without transparency or accountability.
(via Knowledge @ Wharton): The Wharton Blueprint for AI Agent Adoption
Wharton’s Blueprint identifies three psychological frictions blocking AI agent adoption: perceived competence, trust, and willingness to delegate control, offering behavioral science strategies to help organizations overcome each barrier.
(via The Register): Locked, stocked, and losing budget: AI vendor lock-in bites
Steven J. Vaughan-Nichols suggests that enterprise AI vendor lock-in is far worse than executives realize, with most migrations failing and rising prices turning yesterday’s cheap AI experiments into tomorrow’s budget problem.
: Sequoia Ascent 2026 summary
Andrej Karpathy proposes that LLMs represent a new computing paradigm where the context window becomes the program. He emphasizes that professional agentic engineering requires human judgment, taste, and understanding to stay involved throughout the process.
(via Anthropic): What 81,000 people told us about the economics of AI
Maxim Massenkoff shares findings from Anthropic’s survey of 81,000 Claude users, revealing that workers in AI-exposed roles worry most about job displacement, especially early-career professionals, while both high- and low-wage workers report significant productivity gains.
🖥 💯 🇬🇧 AI4Agile BootCamp #7, May 28 to June 25, 2026
The job market’s shifting. Agile roles are under pressure. AI tools are everywhere. But here’s the truth: the Agile pros who learn how to work with AI, not against it, will be the ones leading the next wave of high-impact teams.
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Learn more: 🖥 💯 🇬🇧 AI4Agile BootCamp #7, May 28 to June 25, 2026.
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➿ Agile & Leadership
: Dropping sprints: a year with Shape Up
Matthew Littlehale shares how his team replaced Scrum with Shape Up over eight cycles, moving from expected maintenance mode to consistent delivery, reduced interruptions, and reinvigorated engineers with real autonomy.
(via The Cynefin Company): Stacey Unresolved
Dave Snowden examines an unresolved tension within the CRP tradition: Mowles’ facilitated group practice presupposes bounded entities that Stacey’s radical process ontology explicitly rejects, demanding a methodological realignment.
(via Corporate Rebels): Organizational silos: what the Titanic teaches us about information that never arrives
Joost Minnaar uses the Titanic’s ignored ice warnings to illustrate how organizational silos filter out critical information by design, proposing autonomous, cross-functional teams as the alternative to centralized structures.
📯 The Scrum-to-POM Transition Is a Role Repositioning Event
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.
Learn more: The Scrum-to-POM Transition Is a Role Repositioning Event.
🛠 Concepts, Practices, Tools & Measuring
: Our Uncertain Uncertainties
Kevin Kelly proposes that AI, geopolitical shifts, and eroding trust will create not a brief fog but a decade-long “Age of Ambiguity,” requiring radical adaptability and comfort with changing your mind.
: How to Build an AI Chief of Staff (Tutorial)
Michael Crist walks non-technical professionals through setting up Claude Cowork as a chief of staff by creating a sandbox folder, writing context files, and delegating real work instead of just prompting.
(via OpenAi): Prompt Guidance GPT-5.5
OpenAI’s GPT-5.5 prompt guidance recommends shorter, outcome-first prompts over process-heavy instructions, letting the model choose its own path while developers define success criteria, constraints, and stopping conditions.
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📅 Scrum Training & Event Schedule
You can secure your seat for Scrum training classes, workshops, and meetups directly by following the corresponding link in the table below:
| Date | Class and Language | City | Price |
|---|---|---|---|
| 💯 🇩🇪 May 19-20, 2026 | Guaranteed: Professional Scrum Product Owner Training (PSPO I; German; Live Virtual Class) | Live Virtual Class | €1,299 incl. 19% VAT (If applicable.) |
| 💯 🇬🇧 May 28 to June 25, 2026 | Guaranteed: AI4Agile BootCamp #7 (English; Live Virtual Cohort) | Live Virtual Cohort | €499 incl. 19% VAT (If applicable.) |
| 🖥 💯 🇬🇧 June 1, 2026 | GUARANTEED: Claude Cowork: Stop Prompting. Start Delegating. (English; Self-paced Online Course) | Self-Paced Online Course | $129 incl. 19% VAT (If applicable.) |
| 🖥 💯 🇬🇧 June 10-July 2, 2026 | GUARANTEED: Claude Cowork BootCamp #2 (English; Live Virtual Cohort) | Live Virtual Cohort | $249 incl. 19% VAT (If applicable.) |
| 🇩🇪 June 30-July 1, 2026 | Professional Scrum Product Owner Training (PSPO I; German; Live Virtual Class) | Live Virtual Class | €1,299 incl. 19% VAT (If applicable.) |
| 🖥 💯 🇬🇧 July 1, 2026 | GUARANTEED: AI 4 Agile Course v3 — Master AI for Agile Practitioners (English; Self-paced Online Course) | Self-Paced Online Course | $149 incl. 19% VAT (If applicable.) |
See all upcoming classes here.
You can book your seat for the training directly by following the corresponding links to the ticket shop. If the procurement process of your organization requires a different purchasing process, please contact Berlin Product People GmbH directly.
📺 Join 6,000-plus Agile Peers on Youtube
Now available on the Age-of-Product YouTube channel to improve learning, for example, about Slowing Down with AI:
- Stop Writing Prompts. Let AI Do It for You — Hack #01, AI4Agile Online Course v2.
- Socratic Prompting — Hack #10, AI4Agile Online Course v2.
- Check Your AI’s Plan Before — Hack #7, AI4Agile Online Course v2.
- From Product Requirements to Experiments to Learnings — Supported by Generative AI.
- Never Accept an LLM’s First Offer — Improve GenAI’s Usefulness w/ Feedback Loops and Challenges.
✋ Do Not Miss Out: Learn more about Slowing Down with AI — Join the 20,000-plus Strong ‘Hands-on Agile’ Slack Community
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If you would like to join, all you have to do now is provide your credentials via this Google form, and I will sign you up. By the way, it’s free.
Help your team to learn about how AI Intensifies Work by pointing them to the free Scrum Anti-Patterns Guide:
🗞️ Last Week’s Food for Agile Thought Edition
The post Food for Agile Thought #542: Command & Control Returns, Slowing Down with AI, Alignment Tax, 81k Workers on AI appeared first on Age-of-Product.com.
