What AI can do well
- Turn a broad idea into customer, trigger, outcome and risk hypotheses.
- Compare possible alternatives and value propositions.
- Draft interview questions, offers and seven-day experiments.
- Expose missing evidence and logical jumps.
- Organize results into continue, change or stop conditions.
What AI cannot prove alone
- A target customer will pay the proposed price.
- A channel can acquire customers repeatedly and economically.
- Customers will complete adoption and continue using the product.
- One payment represents a repeatable market.
- The product satisfies every legal or professional requirement.
Why AI answers can sound too certain
Language models produce coherent explanations even when evidence is missing. A complete answer is not complete proof. Customer, price, competitor and conversion claims should be marked as assumptions until supported by observable behavior.
A safer division of work
- AI proposes hypotheses and prepares test materials.
- The founder chooses prospects, performs outreach and presents a real price.
- Customers supply evidence through action, refusal, payment and use.
- The system records evidence levels and the next decision.
Four questions for evaluating an AI validator
- Does it separate AI inference from market fact?
- Does it produce a falsifiable next step?
- Does it disclose limits and avoid revenue guarantees?
- Does it connect conclusions to real customer evidence?