Treat generated code as a proposed change
A snippet that compiles may still misunderstand your business rule. Start by writing the intended behaviour in plain language. For a supplier editor, specify who may edit, which fields are optional and what must happen when saving fails. Review the code against those requirements rather than judging it by how plausible it looks.
Keep the change small enough to inspect
Ask for a focused modification and examine the diff. Look for unrelated rewrites, deleted checks and new dependencies. If the assistant changes several layers at once, require an explanation of why each change is necessary. Small, coherent changes are easier to verify and reverse if a problem appears.
Check trust boundaries
A disabled button is not a permission check. Verify that the server enforces access to the underlying records. Look for secret values in client files and excessive logging of request data. Confirm that user input is handled safely where it reaches storage, HTML or external services. Ask for evidence rather than accepting a statement that the code is secure.
Test meaningful scenarios
Exercise a normal request, invalid input, a user without permission and a network failure. For destructive actions, verify exactly which record is affected. Tests should prove a business expectation, not merely repeat the implementation. Review the rendered interface too; automated checks cannot tell you whether the workflow is understandable.
Publish with a recovery path
Commit the reviewed change and know how to restore the previous version. After deployment, repeat the important journey in the actual environment. AI assistance can shorten the drafting stage, but ownership of the result stays with the team shipping the product. Use it to support engineering judgment, not replace it.
Published by DevMania with AI assistance. Examples illustrate planning approaches and do not claim client results. Check current provider documentation before implementing product-specific features.