Your Kanban Board Ends Too Early
Does your board stop at deliverable and output, or does it go towards outcome — the changed behavior for somebody? Most boards stop at deployed, and that is what teaches people deployment is success.
Scaling with Agility: From Friction and Theater to High-Impact Value Flow Across Product and Beyond
Does your board stop at deliverable and output, or does it go towards outcome — the changed behavior for somebody? Most boards stop at deployed, and that is what teaches people deployment is success.
Flow metrics aren't useful because metrics are good. They're useful when important work is slow, blockers show up late, and forecasts keep missing.
Starting numbers for active work and queues, covering solo and multiplayer spec-driven development, pod topology, flow buffers, and replenishment cadence.
A new open-source AI agent skill to help teams rewrite their work items from output/activity language to outcome-oriented language using a simple taxonomy.
A minibook on portfolio agility: helping multi-product organizations see work clearly, improve flow, and steer investments with evidence instead of reported progress.
An AI coaching prompt from my "Product Orientation Through LPM" talk: pressure-test one real initiative, find the real gap, and get one experiment to run.
Most AI efforts start with tools and demos. Better to use product discovery to aim AI at a real business constraint and test the riskiest assumption first.
Claude's /goal feature lets agents work until a completion condition is met. Most examples are output-oriented: tests pass, backlog empties. Outcome is missing.
Most AI efforts are still stuck in personal productivity. Zoetis CTO Kumar Venugopal on what it takes for AI to change the process itself.
AI vibe coding gets frustrating inside the wrong operating system. It gets traction when the organization can turn experiments into business results.
Many orgs claim a Product Operating Model but keep stage-gate thinking under the surface. How to tell the difference and what to do about it.
How ARAS Software scaled from startup to 60+ engineers with SAFe, then moved past it when rigid PI Planning started dragging on throughput and innovation.
95% of AI projects fail — not because the models are wrong, but because organizations run high-uncertainty AI work in project mode.
An audio series for product and tech leaders who want concrete steps toward an empowered product organization — without the theory-heavy frameworks.
Show me your review sessions and I can tell you if you're a feature factory or a product lab. How to shift reviews from deliverables to outcomes and traction.
Most transformation programs fail not because people resist change, but because they're run like projects instead of learning systems. Here's what works.
Flywheels need consistent turns, not one-time framework installs. Three agility flywheels worth building — and the doom loops that destroy them.
AI initiatives die in the proof-of-concept stage when run as fixed-scope projects. Clemens Adolphs and I unpack why AI work needs real product discovery.
Adopting AI, Agile, or OKRs out of FOMO usually ends in JOMO. Five questions that tie any initiative to your most expensive problems first.
Selling a product transformation but managing it like a project — vanity metrics, no kill criteria, output measures — is exactly what you tell others to stop.