Product ownership in practice.
Notes from building products, governing AI-assisted delivery, and deciding how evidence from the work should shape what happens next.
The harness: product ownership when production is cheap
AI makes producing output inexpensive, and plausible output can look like progress. The product owner's job shifts from directing each piece of work toward designing the structure it runs inside and deciding what deserves to exist at all.
One-off or pattern: where a lesson belongs
How FLIP captures delivery findings, gives each one a disposition, keeps project-specific lessons local, and escalates broader patterns for portfolio decisions. Only some findings become shared rules.
What Prodacity taught me about the governance gap
Reflections from three days at Rise8's Prodacity conference on software craft, workflow design, verification, and the governance questions raised by AI-assisted delivery.
CH(Ai)SE and LEAD: the methodology behind the machine
How the Collaborative Human-AI Standards Environment provides the governing methodology, and how Lineage-Enforced Agentic Delivery implements its principles for agentic product delivery.
What I mean by LEAD
An introduction to Lineage-Enforced Agentic Delivery: defined responsibilities, explicit boundaries, verification gates, human product authority, and a learning loop that continues to evolve.