Product, software, and practical AI

How to use Claude Code or Codex to test an MVP before investing more

Use an AI coding agent to test one product question through a narrow end-to-end flow, then record what users actually do.

Edo Ceder23 July 20266 min read

Claude Code and Codex can help turn an idea into software that people can try. That makes it possible to test a product question before every feature and requirement has been settled. The strategic opportunity is to learn earlier.

An MVP should help you make a decision. It does not need to contain the future company, every user role, a complete automation layer, or the architecture for years of growth. It needs to reveal whether a specific user can get meaningful value from a specific workflow—and what you misunderstood before they tried.

Once a first flow works, it is tempting to keep adding features. The discipline is deciding what still does not need to be built.

Begin with the decision, not the feature list

Before opening a coding agent, write one sentence:

After people use this MVP, what decision will I be better able to make?

Useful examples include:

Do the intended users recognize this problem as important?
Can they complete the proposed workflow without my guidance?
Will they provide the information the product requires?
Does the result help them make or complete a real decision?
Which part of the process creates enough value to justify further investment?

“Can I build it?” may not be the uncertainty that matters most. Claude Code or Codex may show that a screen and workflow are technically possible, while the business question remains untouched.

Choose one uncertain product assumption and design the MVP around exposing it.

Pick one user and one complete job

An early prototype can become a small collection of incomplete features. There is a dashboard, an AI chat, settings, an onboarding screen, and several buttons—but no single task a user can finish from beginning to end.

A stronger MVP is narrow but complete.

Define:

One primary user. Not “businesses,” but a recognizable person in a recognizable situation.
One triggering moment. What has just happened that makes them seek help?
One job. What outcome should they reach?
One evidence point. What behavior will indicate that the flow was valuable?

This does not mean ignoring the larger vision. It means choosing the smallest real slice through it.

For example, to test a better approval process, build the intake, review, decision, and notification path for one approval. Surrounding administration can remain manual.

Make the flow thin, but do not make it fake

An MVP may use manual work, support limited cases, and postpone automation, but the user should still experience a real outcome. State which cases are supported, what is manual, when a result will arrive, what data is stored, and what users should not rely on yet.

If the product touches financial, medical, legal, employment, or other sensitive decisions, keep human review visible and avoid presenting experimental output as authoritative advice.

For AI features, give the model a defined role. It may summarize, classify, extract, draft, or propose. Critical changes to business data should follow explicit application rules and, where appropriate, user confirmation. The AI systems approach matters even in a small prototype because the boundary affects what you are actually testing.

Give Claude Code or Codex enough context to be useful

Give the coding agent specific context and clear success criteria rather than only asking it to “build an app.” Prepare a compact brief covering the user, the core flow, required information, known rules, realistic examples, explicit exclusions, device and language needs, privacy constraints, and the test you want to run.

Ask the agent to state assumptions and unresolved questions. Review the plan before accepting a large implementation. Work in checkpoints you can run and inspect, so a misunderstanding is found before it spreads through the implementation.

Test behavior, not enthusiasm

Positive comments about an idea are not evidence that a user can complete the task or get value from it.

Give a user a realistic task and allow them to try without narrating. Observe where they begin, what they misinterpret, which information is unavailable, when they seek reassurance, what they expect next, and whether they recognize success.

Ask about the experience after the task. Use open questions such as “What did you expect here?” and “What would you do instead?” alongside observation of the task.

If you must guide the user, record exactly where and why. Your explanation may be compensating for a missing product decision.

Preserve the evidence as you iterate

Keep a learning log with the assumption tested, the participant’s context without unnecessary personal data, what they attempted, where they hesitated, their own language, new rules or exceptions, blocking bugs, resulting decisions, and the next question.

Separate bugs from product discoveries. A broken button tells you little about demand. A user refusing to provide the required information may challenge the entire workflow.

Keep versions of important prompts, schemas, sample data, and screen flows. They explain the product’s reasoning to a future team.

Know when the MVP has done its job

An MVP should not become an indefinite substitute for making a decision.

You may be ready for the next phase when:

users complete the central flow with decreasing guidance;
important exceptions and repeated friction are clearer;
the value can be described without relying on the technology;
people return, continue, provide data, or involve colleagues;
the next limits concern reliability, access, integrations, or capacity—not basic comprehension.

Contradictory findings may require another small experiment. Consistent indifference or a clearly preferred alternative may require a change of direction. Stopping is also useful if the MVP prevents a larger investment in the wrong product.

Prepare for a professional handoff before you need one

Do not hand over only a repository and feature list. Prepare the user and problem, validated flow, test observations, rules and exceptions, screen map, data and integrations, known failures, open decisions, and account ownership.

The development team can then inspect the implementation and decide what to keep, strengthen, replace, or rebuild. The goal is not to reward or punish the original code. It is to preserve the product learning while creating a dependable path forward.

Build just enough to create better evidence

Claude Code and Codex can help a founder cross the distance between an idea and a testable experience. Use that advantage. Build something narrow, put it in front of people, and let their behavior challenge your assumptions.

But remember what the MVP is for. It is not a smaller version of every future feature. It is an instrument for reducing uncertainty.

A useful prototype can leave you with more than code. It leaves you with a clearer user, a better-defined workflow, documented business rules, evidence of where value appears, and a much more intelligent basis for the next investment.