TL; DR: OpenClaw/Clawdbot Fad — Food for Agile Thought #529
Welcome to the 529th edition of the Food for Agile Thought newsletter, shared with 35,753 peers. This week, Jing Hu and Klaas Ardinois unpack OpenClaw/Clawdbot and the real tradeoffs and risks of always-on self-hosted agents, while Stephanie Leue shows how AI exposes broken product operating models and why builder teams beat bolt-on AI. Maarten Dalmijn reframes roadmaps as a choice between Red predictability and Blue adaptability, and Dario Amodei sketches near-term AI risks and safeguards. John Cutler calls out metrics theater and pushes outcome signals.
Next, Ant Murphy suggests product-tech teams can drop roles like BAs and Scrum Masters by pulling engineers into discovery, reducing dependencies, and shipping small batches with decoupled deploy and release. Wes Bush frames product-led growth as table stakes for AI software, with fast time-to-value, agents as users, and per-task pricing. Zvi Mowshowitz reviews Claude’s Constitution and its values-first stance, and Ethan Mollick treats management as the most critical AI skill. Also, Casey Newton repeats a crucial truth: AI creates work slop, so measure outcomes.
Then, Federico Viticci shows OpenClaw/Clawdbot, an LLM-based agent on a Mac mini that chats via Telegram, stores Markdown memory, adds MCP skills, and runs shell tasks, while raising app store policy questions. Mike Fisher links speed to focus, trust, and psychological safety, not pressure; Sean Goedecke treats estimates as political and replaces dates with options and risks, and Aakash Gupta, interviewing Sachin Rekhi, pushes AI prototyping to validate problem solution pairs fast. Lastly, Kieran Klaassen suggests that AI coding fails when planning disappears.
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🏆 The Tip of the Week: The OpenClaw/Clawdbot Fad
: I Changed My Mind About Clawdbot Three Times
Jing Hu and Klaas Ardinois describe Clawdbot, a self-hosted always-on agent, and swing from hype to caution: setup, costs, and security risks are real; usability may matter more than novelty.
🎯 Product
: Your Product Operating Model is Broken (And AI is Making it Obvious)
Stephanie Leue warns that AI exposes product operating models. Feature factories with bolt-on AI accelerate waste and become legacy magnets. She proposes carving out builder teams to prototype fast, learn, and improve outcomes.
: Red Vs Blue Roadmaps: Why Most Roadmaps Suck
Maarten Dalmijn suggests most roadmaps fail because they chase false predictability. He contrasts Red roadmaps, inside-out and operationally heavy, with Blue roadmaps, outside-in and adaptive, and urges choosing deliberately.
: How product companies operate without BAs, Scrum Masters, Release Managers, etc.
Ant Murphy suggests product-tech companies skip roles like BAs and Scrum Masters by treating teams as problem-solvers, involving engineers in discovery and delivery, reducing dependencies and cognitive load, and shipping in small batches with decoupled deploy, release, and launch.
(via ProductLed): PLG Predictions For 2026: The Playbook is Being Rewritten. Fast.
Wes Bush suggests product-led growth is the baseline for AI software: hybrid self-serve plus sales, agents as users, under-60-second time-to-value, per-task pricing, tighter free tiers, and renewal-driven ROI proof matters.
🧠 Artificial Intelligence
(via MacStories): Moltbot (Formerly Clawdbot) Showed Me What the Future of Personal AI Assistants Looks Like
Federico Viticci describes OpenClaw, a local Claude-powered agent on his Mac mini that he chats with via Telegram, which stores memory in Markdown, adds skills, MCP servers, and shell access to automate tasks, and raises app-store questions.
: Management as AI superpower: Thriving in a world of agentic AI
Ethan Mollick suggests management becomes the key AI skill: scoping outcomes, delegating clearly, and reviewing fast. His MBA class built startup-grade prototypes in days by treating prompts like PRDs and improving success odds through feedback.
: The Adolescence of Technology: Confronting and Overcoming the Risks of Powerful AI
Dario Amodei warns that powerful AI could arrive soon, like a country of geniuses in datacenters. He maps autonomy, misuse, authoritarianism, and economic risks, proposing pragmatic safeguards, transparency, and limited regulation.
: Claude’s Constitutional Structure
Zvi Mowshowitz reviews Claude’s Constitution as a public, philosophy-heavy guide for training values and judgment over rigid rules. He praises its virtue-ethics approach, flags a lack of clarity in decision theory, and previews posts on structure, ethics, and unresolved tensions.
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➿ Agile & Leadership
: The Seduction (And Folly) Of Rollups, Points, and (Most) Time Tracking
John Cutler warns that rollups, story points, and time tracking seduce leaders with faux certainty. Complex work resists neat categories, so teams game reports. Focus on outcomes, signals, and measurements.
: Speed Is Never Just Speed: What rugby can teach us about leadership
Mike Fisher suggests speed is not a command but an outcome of focus, collaboration, continuous improvement, and psychological safety. Rugby shows teams earn “going wide” through fundamentals, trust, repeatable systems, and learning without fear.
: The AI productivity paradox
Casey Newton contrasts studies showing AI can slow output while boosting perceived speed. Executives report savings, workers little, partly due to reviewing work slop and job fears. Therefore, track outcomes, not vibes.
📯 Agile’s AI-Driven Paradigm Shift
The paradigm shift is here. Andrej Karpathy, former Tesla AI director and OpenAI co-founder, recently admitted he has never felt this far behind as a programmer. If Karpathy feels overwhelmed, how should the rest of us feel?
This article maps the shift across three levels: strategic, product, and individual. Each level demands different responses, while “good enough Agile” no longer provides an income or perspective. The question is where you are on the journey.
Learn more: Agile’s AI-Driven Paradigm Shift.
🛠 Concepts, Practices, Tools & Measuring
: How I estimate work as a staff software engineer
Sean Goedecke says accurate software estimates are mostly fiction because unknown work dominates. He treats estimation as a political process, starts with leadership’s desired timeframe, and then proposes feasible approaches, risk mitigation, trade-offs, and escalation paths.
(via Every): Stop Coding and Start Planning
Kieran Klaassen suggests AI coding fails when planning disappears. He proposes planning agents that research patterns, outline options, and review results, so each plan teaches thinking, reducing debugging time and improving productivity.
and : 📺 Advanced Guide to AI Prototyping with Sachin Rekhi (Reforge)
Aakash Gupta interviews Sachin Rekhi about AI prototyping: build fast, functional prototypes to validate problem solution pairs before roadmaps. AI makes this cheap, but most results look generic, so consistency and iterative refinement matter.
📅 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 |
|---|---|---|---|
| 🖥 💯 🇬🇧 February 3, 2026 | Guaranteed: Hands-on Agile #71: A3 Framework — Assist, Automate, Avoid — Let’s Build a Playbook! (English; Live Virtual Meetup) | Meetup | FREE |
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| 🖥 💯 🇬🇧 February 19, 2026 | Guaranteed: Hands-on Agile #72: Become Your Organization's AI Champion: A Crowdsourced Playbook (English; Live Virtual Meetup) | Meetup | FREE |
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| 🖥 🇩🇪 March 24-25, 2026 | Professional Scrum Product Owner Training (PSPO I; German; Live Virtual Class) | Live Virtual Class | €1,299 incl. 19% VAT |
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 the Real Value Journey:
- Hands-on Agile #68: How to Analyze Unstructured Team Interview Data with AI.
- Fabrice Bernhard: The Lean Tech Manifesto.
- Maarten Dalmijn: The 5 Obstacles to Empowered Teams.
- Roman Pichler: The Top Reasons Why a Product Strategy Fails.
- Johanna Rothman: How to Instill Agility, not Agile Practices.
- Hands-on Agile EXTRA: How Elon Musk Would Run YOUR Business with Joe Justice.
✋ Do Not Miss Out: Learn more about the OpenClaw/Clawdbot — Join the 20,000-plus Strong ‘Hands-on Agile’ Slack Community
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Help your team to learn about Career Success Factors by pointing them to the free Scrum Anti-Patterns Guide:
🗞️ Last Week’s Food for Agile Thought Edition
Read more: Food for Agile Thought #528: The Real Value Journey, Product Discovery Coding, Shadow IT, AI Shopping?
