The product brief your AI coding assistant actually needs.

Better context turns a vague request into a change you can review.

Describe behavior before technology

Start with the person, the task, and the result. “Let a designer paste feedback, review an editable summary, and export a revision list” gives clearer direction than “build a modern SaaS app.” Add the conditions that matter: long inputs, failed requests, and whether work must survive a page refresh.

Give the assistant boundaries

State the existing framework, the files or components involved, and what should remain unchanged. Include relevant project instructions. Avoid sharing secrets or sensitive customer data. A focused change is easier to reason about, test, and reverse than a large rewrite that combines several unfamiliar systems.

Write acceptance criteria

Describe observable outcomes. Empty input should produce an inline explanation. A failed request should preserve the original text. The main action should work with a keyboard. Acceptance criteria turn a subjective “looks done” into a set of behaviors you can check.

Request a small implementation plan

Ask which files will change, which assumptions are unresolved, and how the result will be verified. Review the plan before letting scope expand. If an integration is not available, choose an honest placeholder or defer the feature; do not disguise a simulated response as a working service.

Close the loop yourself

Run the flow and inspect the change. Ask the assistant to explain unfamiliar code and identify risks. Commit a working checkpoint. AI can accelerate implementation, but the speed only helps when you retain the ability to understand failures and maintain what you ship.