The ChiefProduct AI PM generates frame-anchored specs from five pilot templates — you paste a brief, get a structured spec back, and rate it from 1 to 5 so the library stays honest.
Choose one of the five below — success-metrics, competitive-research, discovery-plan, prioritization, or feedback-triage.
Drop a 1-3 paragraph product brief into the generator. The AI PM runs that one template, no other steps.
If the spec is useful, rate it. If it isn't, rate it low and tell us why. Either way, your rating feeds the public library.
Anchored on a 5-component test — Outcome, Attribution, Leading, Comparability, Memorability. The generator rejects any KPI that fails any component.
Axes chosen by relevance to the brief, concrete public sources per axis (G2, Crunchbase, ProductHunt, vendor docs), and honest gaps the AI cannot settle from public data alone.
Three-method mapping anchors every research question: interviews for WHY, surveys for HOW MANY, analytics for WHAT USERS DID.
Four-layer stack: every candidate passes a strategic filter, is MoSCoW-tagged at the initiative level, scored with the framework whose inputs the brief supplies, and reviewed for distribution dominance.
A 4-tier rubric — critical, strategic, noise, duplicate — weekly cadence, each item tiered in under 60 seconds.
Behind every template is a public library — the Product Instinct Library — that aggregates every spec generated across the five templates. Your 1-5 rating feeds that library so the next pilot sees what you saw.
Drop your email — we'll send the run-and-rate access link as soon as your spot opens.
ChiefProduct AI PM runs the same five templates with the same framing — pick one, paste a brief, rate the output so the library stays honest.
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