The AI Product Discovery Review helps product teams move faster without confusing generated synthesis with customer evidence. It makes the source of every product belief visible before the team commits to a roadmap decision.
Separate evidence from plausible output
Start with direct user evidence: interviews, behavior, support conversations, sales objections, or product data. Put AI-generated themes, summaries, and hypotheses in a separate column. Then identify the unknowns and risks that matter most and choose the next validation step.
This board is useful because AI can accelerate discovery work while also making weak assumptions sound unusually complete. The structure keeps speed and epistemic discipline together.
So moderierst du
- 1Attach a source. Every evidence card should point to a customer, observation, or metric.
- 2Label synthetic insight. AI output is a hypothesis until a user or behavior supports it.
- 3Prioritize the riskiest unknown. Validate what could most change the product decision.
- 4Choose a cheap test. Prefer an interview, prototype, concierge test, or data check before a build.
Wann du diese Vorlage nutzt
Ideal für Produktmanager, die Forschung und Discovery mit KI beschleunigen
