How to stop your AI coding agent from building the wrong product

Anchor the task in a customer outcome

To stop an AI coding agent from building the wrong product, define the customer outcome, the current release boundary, and observable acceptance criteria before implementation. Ask the agent to separate required work, technical prerequisites, and optional improvements. Review meaningful additions as proposals and save the approved scope where later sessions can find it.

The agent shows you a polished feature. You recognize the general idea, but the process is different from what your customer needs. Perhaps a simple request form became an elaborate scheduling system. Perhaps an internal review step disappeared because the agent assumed automation was preferable. The implementation can be impressive while the product decision is wrong.

Scope control begins with describing the problem well enough that the agent does not have to invent the business process. “Build a dashboard” gives it many plausible directions. “Help the owner identify requests awaiting approval” gives you a concrete outcome to review, even when the implementation details change.

This article uses a hypothetical service-request app. The workflow is founder guidance, not a measured claim about how often agents drift. Its purpose is to make expansion visible while preserving your ability to accept good ideas deliberately.

Before implementing, state the customer, the problem, the intended outcome, and the current release boundary. Identify assumptions you are making about the business process. Propose observable acceptance criteria and explicit exclusions. Do not choose unresolved product behavior on my behalf.

Make the current release smaller than the whole ambition

Your long-term product idea and your current release are different planning objects. You may eventually want a complete operating system for a service business. The first release may only capture a request and let the owner approve it. Record both without letting the ambition become permission to implement every adjacent feature.

For the service-request example, a customer submits the service needed and preferred date. The owner reviews the request and confirms availability. Payments, automatic staff allocation, and customer subscriptions are outside this release. Those exclusions define where the agent should stop, not what the business will never do.

Write down why the boundary exists. Perhaps the founder needs to learn whether requests are sufficiently complete for the owner to act on them. Adding complex scheduling before answering that question changes the experiment and the work required. The reason helps you evaluate suggestions against what you are trying to learn.

Keep exclusions specific enough to recognize. “Keep it simple” expresses a preference but leaves the agent to interpret simplicity. “Do not add payment collection in this task” is a boundary you can inspect. Pair it with the outcome so the agent knows what useful progress still looks like.

Separate prerequisites from improvements

A prerequisite is work needed to achieve the approved outcome. An improvement adds value beyond it. The distinction depends on the task: saving a submitted request is required for owner review; an animated dashboard is optional. Ask the agent to explain the relationship rather than accepting a label without reasoning.

Some prerequisites surface during implementation. For example, a request may need an owner association before the correct owner can review it. That dependency could justify additional work. Ask how it affects the plan, the areas changed, and verification. The founder should understand the consequence even if the agent chooses the technical approach.

Optional ideas should be recorded rather than silently implemented or discarded. A reminder email could improve response time later. Capturing the proposal keeps it available for a future decision while protecting the task you are trying to finish now.

If an addition changes who uses the product, how approval works, what data it collects, or how it earns money, treat it as a product decision. A technical-sounding explanation does not remove its business consequences. Ask for a concrete before-and-after description you can review.

Classify each proposed addition as required for the approved outcome, a prerequisite discovered during implementation, or an optional improvement. Explain the reason and scope impact. Flag changes to the audience, business process, data collection, or commercial model for review. Record optional ideas as pending proposals.

Turn a broad request into a reviewable task

Start with “the owner can review a submitted request.” Then specify what the owner must see: customer contact details, service requested, preferred date, and current status. Specify the action: approve or decline. Specify what happens afterward: the status is saved and visible when the owner returns.

Now add the failure case that matters. A missing required field should prevent submission with an understandable message. A user should not be able to review another owner’s requests. The agent can propose checks suited to those criteria; you do not need to invent a technical testing framework.

This task has a natural stopping point. It does not require a complete analytics dashboard, customer billing, or scheduling automation. When the review journey works and relevant checks pass, you can accept it and decide what the next customer problem is.

Avoid making acceptance depend on vague qualities such as “professional” or “production-grade.” Translate them into what you can inspect: clear status labels, a usable empty state, persistence after refresh, and appropriate access. A task becomes reviewable when both you and the agent can recognize its success.

Turn this outcome into one reviewable task: [outcome]. Specify the user actions, information needed, saved result, relevant failure path, and verification evidence. Define where the task stops. Explain any criterion that cannot be checked in the current environment.

Handle a good idea without letting it take over

An agent may propose instant approval because the current process involves a waiting step. That could be a useful improvement, or it could undermine the owner’s need to confirm availability. Ask what user evidence supports the change and which approved decision it would replace.

Give the idea a small proposal: the problem, suggested behavior, expected benefit, dependencies, and uncertainties. You can accept it, defer it, or ask for more evidence. Keep its status visible so a later session does not mistake the proposal for an instruction.

If you accept the change, update the brief and affected task criteria together. Otherwise, the implementation may follow the new direction while the next agent reads the old one. Record the reason for replacing the previous decision so the project does not repeatedly reopen it.

If you defer it, explain the condition for reconsideration. “After we observe how owners handle the first requests” gives the proposal a meaningful trigger. “Later” can become an ever-growing backlog that obscures the current work.

Write a product change proposal for this idea. Include the customer problem, proposed behavior, evidence available, decision it would replace, dependencies, uncertainties, and effect on current release scope. Leave it pending until reviewed. If deferred, record the condition for reconsideration.

Review the result against the original boundary

At the end of the task, ask what changed for the user and compare it with the agreed outcome. Identify additions and omissions. You may accept a small implementation detail while declining an unapproved change to the business process. Keeping that review explicit prevents the final demonstration from rewriting the goal.

Try the journey yourself when possible. In the service-request app, submit a request, review it as the owner, approve it, and return to check the status. Look for both functionality and meaning: does “approved” communicate what the owner actually committed to?

Ask the agent to connect its completion report to verification evidence. If the interface works locally but access behavior remains unchecked, record that gap. A release decision should reflect what is known rather than the enthusiasm of the final response.

Close with one next task. A focused sequence is easier to review than several parallel promises to improve everything. The next task can be a missing check, a customer-facing correction, or an accepted proposal. Its reason should connect back to the customer outcome.

Compare the completed work with the approved task and exclusions. Show the user-visible result, additions, omissions, and verification evidence. Flag unapproved product changes. Record the outcome and unresolved gaps, then recommend one next task tied to the customer problem.

Keep scope consistent when sessions and agents change

Persistent instructions can tell an agent to inspect approved scope before working. Native context mechanisms for Claude Code, Codex, Cursor, and Gemini CLI are described in their official documentation. Keep changing approvals and task status in a project record with a clear update process.

RAAV is persistent product and project memory for coding agents. Its proposals, decisions, and tasks provide structure for distinguishing a suggestion from current approved work. The founder still needs to review consequential choices; saving a proposal does not establish that the idea is right.

You can begin without a new tool. Write the outcome, exclusions, and criteria for the next task, and ask the agent to report any expansion. If keeping that record consistent across sessions becomes the friction, evaluate a shared workflow on a real project.

The goal is a product you can explain and a task you can accept. When a feature grows, you should be able to identify the decision that expanded it and why. If you cannot, the next useful step is to recover and review the scope before more implementation.

Continue the non-coding founder series

Start with who this approach is for, why the work needs product management, and why now. Then use the practical guide that matches the next problem in your project.