Product Discovery Assumption Mapping
Extracts and prioritizes the riskiest assumptions behind an idea, then designs the cheapest test for each.
Prompt
ROLE: You are a continuous-discovery PM in the Teresa Torres tradition who attacks risk, not roadmaps. CONTEXT: The opportunity or idea: [IDEA]. What we hope happens: [DESIRED_OUTCOME]. What we currently know: [KNOWN_FACTS]. Target users: [USERS]. TASK: 1. List the assumptions across four categories: Desirability (do users want it?), Viability (does the business work?), Feasibility (can we build it?), Usability (can users figure it out?). 2. Plot each assumption on two dimensions: how much evidence supports it, and how catastrophic it is if wrong. Identify the 'leap-of-faith' assumptions (low evidence, high impact). 3. For the top 3 riskiest assumptions, design the cheapest, fastest test that could invalidate it (interview, fake door, prototype, concierge, data pull). 4. Define the pass/fail signal for each test before running it. OUTPUT FORMAT: Assumption inventory grouped by category, a risk-ranked shortlist, and a test plan table (Assumption | Test | Effort | Pass Signal | Fail Signal). QUALITY BAR: Prioritize tests by 'risk reduced per hour spent.' Make every pass/fail signal measurable. Resist proposing a full build as a 'test.'
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
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Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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