A 12-article path from building your AI knowledge architecture to designing a complete PO agent system. Each article builds on the last.
Build the knowledge architecture that makes everything else possible.
How to architect an Obsidian vault with typed frontmatter so AI agents can reason with your knowledge, not just search it.
How to configure Claude Code as a PO agent with session types and run AI-augmented backlog refinement that challenges your assumptions, not just generates boilerplate.
Named principles for context engineering — less is more, knowledge gardening, structure over retrieval — discovered through daily agent usage, not academic theory.
Transform from prompting to context engineering with hands-on workflows.
The practitioner transformation from prompt-first to context-first AI work — with real before/after artifacts, four progressive stages, and a discrimination test for knowing when each approach is right.
The PO-specific guide to setting up Claude Code with CLAUDE.md as the interface to your knowledge vault — not a developer tutorial, but your first real workflow where context engineering becomes daily muscle memory.
A composable three-tier decision hierarchy — axiom, principle, rule — that codifies your judgment into structured context AI agents can traverse. Distilled from real PO practice, not academic theory.
Coordinate multiple agents into reliable, repeatable systems.
Four practitioner-tested coordination patterns for multi-agent Claude Code workflows — fan-out, pipeline, shared-context-hub — with the vault as coordination mechanism and a decision framework for when to split.
A practitioner's productivity architecture for AI-augmented work — four session types (triage, deep work, review, spike) with matched agent configurations and flow-based batching by cognitive mode.
A practitioner's guide to defensive AI agent design — thin-slice expert watchers that monitor quality, scope, and consistency dimensions with defined trigger conditions, evaluation criteria, and response actions.
Become the AI-native product owner who designs the system.
A practitioner's guide to the AI product owner role transformation — redefining the PO as orchestrator of human+agent teams with ceremony transformation, decision rights frameworks, and the identity shift from tool user to system designer.
A practitioner's guide to using AI-generated stakeholder artifacts as strategic leverage — prototype-as-persuasion, real-time scenario modeling, sprint impact reporting, and the credibility strategy that turns AI capability into organizational influence.
A practitioner's guide to building a complete PO agent system — named subagents with defined roles, a shared brain connecting them, an interface layer for interaction, and a self-improvement loop that makes the system compound over time.