By Ali Najafzadeh · Last reviewed
What an AI-enabled MVP should prove
An MVP is not a smaller list of features. It is the smallest reliable product experiment that can show whether a specific user receives enough value to continue.
AI belongs in the scope when
- the task benefits from classification, extraction, generation or assisted decisions;
- representative data and evaluation examples are available;
- uncertain outputs have a safe review or fallback path.
Start with a classic workflow when
- the rules are stable and deterministic;
- errors cannot be reviewed safely;
- the data or business process is still undefined.
How a proposal becomes defensible
After a short needs assessment, the proposal should name the in-scope workflow, exclusions, responsibilities, acceptance evidence, data and integration assumptions, AI evaluation method, operating constraints and the decision for the next stage. Price and timing follow that scope; they are not generated from a generic calculator.
Primary sources
Method reviewed on . This tool is decision support, not legal or conformity advice.