Use AI to shorten the work between decisions. Keep the product boundary, review, and release criteria in human hands.
Define the question your first release must answer
An MVP is useful when it helps you decide what to do next. Before discussing tools, write down the user, the task they struggle with, and the behavior that would show your product is helping. “Launch an AI platform” is too broad. “Let a small team turn incoming enquiries into a reviewed shortlist” gives the first release a testable purpose.
For that example, the essential journey might be receiving an enquiry, preparing a draft, reviewing it, and recording the outcome. A custom analytics suite or a marketplace can wait. Faster code generation does not make those extra features less expensive to maintain. Scope remains a product decision.
Put assistance where the work is repeatable
AI assistance can draft interface variations, suggest test cases, explain unfamiliar code, or turn agreed rules into an initial implementation. These are starting points for review. Give the tool bounded tasks and the relevant constraints: existing conventions, data shapes, error states, and acceptance criteria.
A request to “build the entire product” makes assumptions difficult to spot. A request to implement one reviewed form with explicit validation rules is easier to inspect. Keep changes small enough for a person to understand the result and explain why it belongs in the codebase.
- Define the task
- Draft a change
- Review and test
- Observe real use
Budget for verification, not only generation
A working demo can hide authorization errors, missing recovery states, or data assumptions that fail outside the happy path. Review generated changes just as you would any contribution. The person approving a release still owns the behavior of the system.
Use a concrete acceptance checklist for the core journey. Test what happens when an upstream service is unavailable, input is invalid, or a user tries to access another account’s records. Keep secrets and customer data out of prompts unless the approved tooling and data policy explicitly permit that use.
- Review permissions at the server boundary.
- Exercise failure and retry paths as well as successful actions.
- Check that tests express requirements rather than repeat the implementation.
- Record deployment and recovery steps before the first real users arrive.
Measure the whole delivery loop
Typing speed is a weak measure of delivery. Track the time from an agreed change to a reviewed release, the amount of rework, and the issues that escape into real use. Faster drafting is only helpful if it does not create a longer review or support queue.
After release, look at whether users complete the intended workflow and where they abandon it. The next iteration might be a clearer explanation or a simpler step, rather than another feature. A focused product boundary, assisted implementation, and accountable review work together; none replaces the others.
