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Food for Agile Thought 554: Toyota Production System, Pressure-Testing Product Ideas, Nokia’s Demise, Drowning in Work?

by Stefan Wolpers | 2026-07-24 News

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.

Food for Agile Thought 553: Dangerous Agile Myths, Produce Evidence Quality, Running Experiments, Playing Politics?

by Stefan Wolpers | 2026-07-17 News

TL; DR: Dangerous Agile Myths — Food for Agile Thought #553

Welcome to the 553rd edition of the Food for Agile Thought newsletter, shared with 35,462 peers. This week, Henrik Mårtensson dismantles seven dangerous Agile myths, showing that fat-tailed cycle-time data invalidates the use of story points. Teresa Torres and Petra Wille question whether support tickets can replace story-based interviews, while Roman Pichler pushes visions beyond feature lists toward purpose. Turning to AI, Laura Summers finds LLM-assisted coding replaces building satisfaction with supervision fatigue, Benedict Evans sees foundation models becoming commodities, and Satya Nadella urges firms to own their learning loops before providers capture proprietary knowledge.

Next, John Cutler reframes software assets through a portfolio lens, asking whether AI makes you faster or moves you faster in the wrong direction. George Sivulka and Arvind Narayanan both place the bottleneck in management, not model capability. On the human side, Sean Goedecke redefines engineering politics as knowing who holds power and making contributions visible, while Steven Sinofsky compares Chicago Law School’s AI ban to Harvard’s 1982 computer ban, arguing such restrictions never last.

Lastly, Pavel Samsonov argues that product empathy rings hollow without respect, a gap LLMs deepen by pushing error correction onto users. Thomas Squeo and Matt Kamelman trace enterprise AI failure to missing governance, not weak models. Susan MacKenty Brady, Stuart Kliman, and Leslie Smith name four leadership traps quietly eroding trust. Finally, Dave Rooney rethinks story slicing when AI handles large tasks, and Tristan Kromer notes AI accelerates experiments but cannot pick the right question.

Food for Agile Thought 553: Dangerous Agile Myths, Produce Evidence Quality, Running Experiments, Playing Politics? Age-of-Product.com

Food for Agile Thought 552: AI Creates Jobs? Product Roadmaps & Leader Anxiety, Overthinkers, Measuring ≠ Learning

by Stefan Wolpers | 2026-07-09 News

TL; DR: AI Creates Jobs? — Food for Agile Thought #552

Welcome to the 552nd edition of the Food for Agile Thought newsletter, shared with 35,468 peers. This week, Ramp Economics Lab and Revelio Labs report that heavy AI adopters grew headcount by 10%, yet Charity Majors insists only honest feedback loops turn adoption into results. Alex Karp questions the economics entirely, calling token pricing fundamentally broken. Pavel Samsonov and Jerry Colonna both argue that speed without trust or judgment produces waste, while Janna Bastow reminds us that roadmap dates are comfort objects that mask the need for outcomes.

Next, Jeff Gothelf proposes that when AI makes building nearly free, teams should prioritize learning value and reversibility over effort. Kyle Poyar believes the resulting cost crisis is self-inflicted and offers a five-step spending fix. Yanli Liu warns that even working tools like Claude Skills silently rot without maintenance, while Addy Osmani suggests engineers must own accountability as agents handle execution. Also, John Cutler recommends that overthinkers disconnect self-worth from work entirely.

Lastly, Paweł Huryn frames the 2026 AI PM roadmap around whether agents run on your work or inside your product, while Alberto Romero raises a stranger question: why do AI models keep inventing their own languages? Fabian Metzeler and McKinsey colleagues distill seven truths from 15 AI-native companies, yet Cris Beswick warns most transformations stall when organizations skip differentiated innovation. Finally, Ant Murphy proposes a two-question test to tell actionable metrics from noise.

Food for Agile Thought 552: AI Creates Jobs? Product Roadmaps & Leader Anxiety, Overthinkers, Measuring ≠ Learning – Age-of-Product.com

Food for Agile Thought 551: AI Confidence Theater, GitHub for PMs, Product Alignments, We Tried Agile; Didn’t Work

by Stefan Wolpers | 2026-07-03 News

TL; DR: AI Confidence Theater — Food for Agile Thought #551

Welcome to the 551st edition of the Food for Agile Thought newsletter, shared with 35,473 peers. This week, Elena Verna calls out AI confidence theater and asks teams to show real workflows, which pairs well with Teresa Torres and Petra Wille’s advice to start AI adoption with one messy to-do item. Also, Janna Bastow brings the same discipline to alignment meetings: clarify decisions before vague input becomes commitment. Anthropic frames Fable 5’s return as governance, while Alberto Romero questions the safety bargain, and Mike Cohn redirects failed Agile blame toward broken conditions.

Next, Aakash Gupta and Shubham Saboo treat PM work like code, while Hamel Husain extends that discipline to AI evaluation: track changes, show provenance, and make review paths obvious, and Tomasz Tunguz adds the cost pressure that will force selective adoption. Joost Minnaar reminds teams that rituals without shared power rot into theater, and Anthropic frames Claude Fable 5 as a teammate needing clearer boundaries.

Lastly, Ethan Mollick sees AI work shifting toward agent management, while Peter Yang expects model portfolios to reshape software economics. Charity Majors argues that leaders must support learning rather than demand unpaid adaptation, and Gergely Orosz reminds us that reinvention beats nostalgia. Finally, Abraham Thomas ties lasting progress to data quality that delivers real business outcomes by matching fitness for purpose with measurable value rather than relying solely on checklists.

Food for Agile Thought 551: AI Confidence Theater, GitHub for PMs, Product Alignments, We Tried Agile; Didn’t Work - Age-of-Product.com

Food for Agile Thought 550: Make AI Boring, Everyone’s a Product Manager Soon, Fixing Procrastination, Agentic “Team” Topologies

by Stefan Wolpers | 2026-06-26 News

TL; DR: Make AI Boring — Food for Agile Thought #550

Welcome to the 550th edition of the Food for Agile Thought newsletter, shared with 35,481 peers. This week, Charity Majors rejects AI purity theater and urges disciplined workplace experiments, just make AI boring again, while Gojko Adzic warns that faster builders without product judgment will ship polished waste. Dave Hora names the organizational traps that keep teams from seeing reality, and Johanna Rothman brings the fix down to flow data and human judgment. Azeem Azhar and colleagues see AI demand rising, but Satya Nadella argues that a durable advantage comes from owning learning itself.

Next, Paweł Huryn moves AI work from prompt craft to agent loops with goals, guardrails, budgets, and independent checks, while Jeff Gothelf argues that AI pilots fail when firms bolt tools onto stale workflows. Joe Hudson adds that emotional clarity now beats knowledge hoarding, and John Cutler names fear, incentives, and executive fantasies as the real bottlenecks. David Burkus brings the pattern back to procrastination, where stress and ambiguity demand clarity without control.

Lastly, Elena Verna pushes experimentation beyond tiny UI tweaks toward larger monetization bets and longer engagement signals, as Zvi Mowshowitz warns AI policy needs calibrated safeguards rather than theater. Deborah Rim Moiso brings the same discipline to facilitation through communities that review real work, and Olivier Wulveryck applies Team Topologies to agentic platforms before shadow IT hardens. Finally, Itamar Gilad grounds the pattern in value, not misleading productivity counts.

Food for Agile Thought 550: Everyone’s a PM, Make AI Boring, Fixing Procrastination, Agentic "Team" Topologies - Age-of-Product.com

Food for Agile Thought 549: AI in Product 2026, Makers Manifesto, AI POM, Open Knowledge Format

by Stefan Wolpers | 2026-06-19 News

TL; DR: AI in Product 2026 — Food for Agile Thought #549

Welcome to the 549th edition of the Food for Agile Thought newsletter, shared with 35,498 peers. This week, Product Circle and Product Institute share the AI in Product 2026 survey show AI coding tools spreading faster than stronger operating models, while Elena Verna sees cheaper software creation opening a Mom-and-Pop SaaS lane for domain experts. Petra Wille counters AI possibilities with accountable product principles, and Sam McVeety and Amir Hormati tackle agent-ready context. Also, Isabel Juniewicz and Ed Zitron question whether increasing hyperscaler spending and the economics of generative AI can sustain the rush, or bubble?

Next, Janna Bastow warns that Slack loses product feedback once channels move on, and Sarah Guo argues that AI shifts durable advantage toward private data, judgment, and trust. Aakash Gupta and Rohan Varma push the logic further, describing AI-native teams that build before they coordinate as the AI way, while Matthew Hodgson adds that enterprises need persistent funding and governance to make AI product operating models work. Then, Gregor Ojstersek shows that top engineering teams are already reshaping structures around AI.

Lastly, Mark Graban warns that tone policing in teams drives bad news underground, while Barry O’Reilly argues that AI raises the premium on visible, codified judgment that requires transparency, not enforced harmony. Johanna Rothman and Sonya Siderova shift the focus from faster tasks to slower systems, where wait times and flow debt shape delivery. Finally, Matteo Tittarelli extends that logic to GTM, where context, skills, orchestration, and integrations must compound across cycles.