MVPs fail when teams skip validation and ship the thing they wanted to build. These 15 prompts design pre-build validation experiments that cost days, not months. Coverage: landing-page tests, fake-door buttons, concierge MVPs, Wizard-of-Oz prototypes, smoke campaigns, and the always-needed kill-criteria so a failed experiment actually kills the idea instead of being explained away.
Who this is for
Founders deciding what to build next, PMs at growth-stage companies running idea validation, indie devs picking among 5 ideas, and innovation teams inside larger companies running structured tests.
When not to use these prompts
Skip these for features that are part of an already-validated roadmap — those just need a PRD. Skip too for compliance or infrastructure work where validation is about reliability, not desirability.
Prompt anatomy / structure formula
An MVP validation prompt should always carry six elements:
- Role: who the AI plays (senior PM / solo founder / product designer / indie dev / growth lead).
- Context: stage (idea / MVP / growth / scale), team size, traffic or ARR, platform (web / iOS / Android), audience, constraints.
- Goal: one concrete deliverable — one PRD section, one user-story set, one experiment design, one launch post.
- Constraints: timeline (this sprint / this quarter), scope cuts, must-not-break (existing flows, billing, compliance).
- Output format: table, checklist, ticket-ready JSON, or labeled blocks you can paste straight into Linear / Notion / Jira.
- Examples / signal: 1-2 reference docs or competitors you like, plus 1 anti-example you want to avoid.
Best for
- Pre-build idea validation
- Picking among 3-5 ideas
- Fundraising-stage proof of demand
- Pivot decision experiments
- Hackathon / sprint idea testing
15 copy-ready prompt templates
1. Landing-page demand test
The cheapest, highest-leverage validation. Days to build, falsifiable in a week.
You are a startup validation coach. Design a landing-page demand test for {idea}: (1) headline + subhead, (2) 3 outcome bullets, (3) email-capture CTA, (4) success metric (conversion rate from cold traffic), (5) sample size needed, (6) traffic source ({reddit / X / paid ads / cold email}), (7) kill criterion (what conversion below which we kill the idea). Total budget: less than $300 and 5 days.
Idea: {paste}Variables to swap: idea, audience, budget
Optimization: If success criterion is squishy, add: “Pick a numeric kill criterion — for example, less than 5% email capture from 500 visits — and commit before launching.”
2. Fake-door button test
Design a fake-door button test for {feature inside existing product}: button placement, copy, what users see when they click ("coming soon" page or interview signup), click-through threshold for greenlight, threshold for kill, ethical disclosure approach. Include the 1-line message shown after click.3. Concierge MVP
Design a concierge MVP for {idea} where humans manually deliver the value before any product exists. Define: target customer to recruit (first 5), what value we deliver manually, how we measure satisfaction, how long we run it ({4-8 weeks}), what we learn that automation would not show. End with success criteria for moving to a real build.4. Wizard-of-Oz prototype
Design a Wizard-of-Oz prototype for {idea}: user-facing UI that looks automated, human backend that fakes the response, success criteria (does the user behave as if it were real?), ethical caveat (when to tell them), and how to transition to real backend.5. Smoke-test campaign
Design a smoke-test ad campaign for {idea}: 3 ad creative variants targeting different angles, exact target audience, budget allocation ({$50-150 per variant}), landing page measurement, success threshold per variant. Define what would prove "no one wants this".6. Pre-sale validation
Design a pre-sale validation for {idea}: pricing offered, refund policy, how many pre-sales needed to confirm demand, delivery timeline, what data we collect from buyers. End with the boundary between "validated" and "should refund".7. 5-customer commitment test
Design a "5 customers commit before we build" test for {idea}: how we recruit the 5, what commitment we ask for (money / time / signed letter of intent), timeline, what counts as confirmation. End with the disqualifier — what would invalidate this evidence.8. Manual workflow demo
Before building, design a manual workflow that solves {problem} using existing tools ({Notion + Zapier + email}). Demo to 3 target users. Measure: would they pay, would they switch tools, would they wait for us to automate it. Success criteria: at least 2 of 3 say yes to all three.9. Falsifiable hypothesis writing
Convert {idea} into a falsifiable hypothesis: "{Target users} have {problem} so badly that they will {specific action} when shown {minimal offer}." For each clause, explain how it would be measured and what would falsify it. End with the experiment that tests it most cheaply.10. Idea triage across 5 candidates
I have 5 product ideas. For each: 1-line problem, 1-line solution, target user, the cheapest validation experiment, expected time and cost, what specifically would kill it. Output as a 5-row comparison table. Recommend which to validate first.
Ideas: {paste}11. Customer-interview design
Design a 30-minute customer interview to validate the problem behind {idea}: 8 open questions (no leading), what behavior to observe, what to NOT mention until they bring it up, success signal (they describe the pain unprompted). End with red flags (interviewer-leading questions) to avoid.12. Build-vs-buy-vs-validate decision
For {feature/idea}, decide: build now, buy a third-party, or validate further. For each path: cost, time, reversibility, learning. Recommend one with reasoning. Add a tripwire: "if X happens we reconsider".13. Validation post-mortem
Below is the data from a validation experiment we ran. Write the post-mortem: (1) hypothesis tested, (2) what we measured, (3) result, (4) honest read (succeeded / failed / inconclusive), (5) what we will do now, (6) what we would do differently if rerunning.
Data: {paste}14. Avoid-survey-bias pass
Below is a customer survey designed to validate {idea}. Audit for leading questions, social-desirability bias, "would you pay" trap, vague metrics. Rewrite the 3 most biased questions and explain why each rewrite is more reliable.
Survey: {paste}15. Validation roadmap (3-month)
For {idea cluster}, design a 12-week validation roadmap with 4 experiments. Each experiment: hypothesis, method (landing / fake-door / concierge / pre-sale), cost, success criterion, kill criterion, what we move to next. Output as a Gantt-style table.Common mistakes
- Building first, validating after — every team thinks they are the exception. They are not.
- No kill criterion — without it, every failed test gets explained away.
- “Would you pay” surveys without actual payment — answers lie.
- Cherry-picking validation traffic (friends, network) — they always say yes.
- Treating excitement as validation — excitement decays, behavior does not.
- Skipping concierge MVPs because they “do not scale” — at validation stage, scale is irrelevant.
- Stopping after one successful experiment — replicate before committing.
How to push results further
- Always write the kill criterion BEFORE running the experiment.
- Validate the problem, then the solution, then the price — in that order.
- Recruit validation users outside your network; friends bias results 3x.
- Use behavior (clicks, payments, time spent) over stated preference.
- Pre-commit to one cheap experiment; pre-mortems prevent scope creep.
- Track learnings in a /validation log per idea — most teams forget what they tried.
- Concierge / Wizard-of-Oz beat full-build MVPs at the validation stage almost every time.
FAQ
- What is the cheapest validation I can run?: A landing-page test with $100-300 of cold traffic and a one-week window. Use template 1.
- How much traffic do I need?: At least 300-500 unique visitors to a landing page for meaningful conversion data. Less is noise.
- Are customer interviews enough?: No. Interviews validate the problem, not the solution or willingness to pay. Pair with template 7 (5-customer commitment).
- When should I stop validating and start building?: When you have payment commitments or behavioral signals from at least 5-10 target users, plus a kill criterion that was not triggered.
- Can AI tell me if my idea is good?: No. AI can help design cheap experiments. Goodness is determined by real customers, not models.