Knowledge architecture
A product leadership library designed for machines and humans
Generic models know how language works. ProductManagerHub encodes how product work — prioritization, AI bets, exec narratives, operational traps — so answers can be specific, comparable, and accountable.
Frameworks
Named methods with when-to-use guidance and structured content — not loose paragraphs. Built for comparison and real-world context.
Decision criteria
Scorable conditions and thresholds that tie back to frameworks — the bridge between “interesting idea” and “decision-ready.”
Red flags
Severity-tagged risk patterns and mitigations — the “don’t ship this without addressing” layer that generic chat rarely pressures-test.
Hybrid retrieval
Queries blend lexical and semantic signals so both exact terminology (e.g. “RICE”, “build vs buy”) and messy problem descriptions surface the right entries. That is what powers natural discovery in MCP tools like search and comparison.
See how MCP exposes this library