How to Debug and Test AI-Generated Code

AI can suggest a fix quickly, but without a reproducible example it may hide the real cause. A small verification loop makes regressions less likely.

Reproduce the failure first

Write down the expected result, actual behavior, and exact steps. Save the console message and the sample input that triggers the issue. Concrete evidence gives the model something specific to reason about.

Narrow the cause and change less

Ask AI to explain likely causes before editing. Recreate the issue in the smallest scenario you can, then change only related code so the fix does not introduce new defects.

Verify the fix and nearby flows

Add a check that fails before the change and passes after it. Review the code diff, run the project’s existing checks, and manually repeat the important user actions.