Prototype Evidence Operator
Generates scoreable evidence by exposing real users to a low-fidelity prototype without coaching or explanation.
Run operatorEvaluates whether a real, painful problem exists and whether the proposed solution is meaningfully desired.
Problem-Solution Fit is the first stage of the ProductBooks evaluation framework. It determines whether the problem you are solving is real, painful, and experienced by a defined user group, and whether the proposed solution generates genuine desire. Most product failures begin here: teams build solutions for problems that are assumed rather than validated. This evaluator forces that validation before resources are committed.
Evaluators apply strict evidence definitions.
Evidence that does not meet the definitions scores zero.
Typical flow
Optional overview (3 min)
Use the Problem-Solution Fit evaluator when you are in the earliest stages of product development and need to determine whether your core assumptions hold up against real evidence. This assessment is critical before committing to a solution direction, roadmap, or product build.
Decides
Whether a real, painful problem exists for a defined user
Does not do
Give advice
Decides
Whether the proposed solution is genuinely desired
Does not do
Improve your idea
Decides
Whether the problem and solution meaningfully fit together
Does not do
Help you "pass"
| This evaluator decides | This evaluator does not do |
|---|---|
| Whether a real, painful problem exists for a defined user | Give advice |
| Whether the proposed solution is genuinely desired | Improve your idea |
| Whether the problem and solution meaningfully fit together | Help you "pass" |
A high Problem-Solution Fit score means you have demonstrated, through verifiable evidence, that a real problem exists for a defined user and that your proposed solution generates genuine desire. A low score does not mean your idea is bad. It means the evidence is not yet strong enough to justify further investment.
The evaluator identifies specific evidence gaps so you know exactly what to test next. Use the operators below to generate the missing evidence, then re-run the evaluator to see how your score changes. This iterative process is how teams build confidence in their product decisions before committing resources.
If required evidence is missing, ProductBooks uses controlled operators to generate it.
Operators generate evidence. They do not decide fit.
Generates scoreable evidence by exposing real users to a low-fidelity prototype without coaching or explanation.
Run operatorForces users to choose between real alternatives to produce unambiguous preference or rejection signals.
Run operatorTests real economic commitment by asking users to accept or reject a concrete paid offer.
Run operatorObserves whether users re-initiate engagement without prompting after a pause.
Run operatorForces users to rank the tested problem against competing priorities under real constraints.
Run operatorOnce you have validated Problem-Solution Fit, the next step in the ProductBooks cascade is to evaluate whether your product achieves repeatable demand and retention. You can proceed to the Product-Market Fit assessment to determine whether users adopt and return without external prompting.
If you have completed all three stage evaluations, use the Fit Report Generator to produce a single, investor-grade summary of your product's current state.
Learn more about validating product ideas in our article on what Problem-Solution Fit really means.
Evaluator contract: This evaluator applies definitions strictly. Disputes do not change scoring.