Why should developers test AI-generated features themselves?

Why should developers test AI-generated features themselves?

Developers should test AI-generated features because the assistant's implementation and its tests can share the same mistaken assumptions. Direct interaction with the application adds evidence about whether the product behaves as users expect.

Exercise the actual journey

For an event-management feature, sign in with a test organizer account, create an event, navigate away, and return. Refresh the page to confirm persistence. Edit the event and verify that the updated information appears wherever it is displayed.

Use realistic names and dates rather than only the shortest valid values. Long titles, empty collections, and multiple events often expose layout or state problems that a simple happy-path example misses.

Test roles and failure behavior

Try the relevant collaborator and guest roles as well as the organizer. Confirm that unavailable controls are handled appropriately and that the server rejects unauthorized operations. Hiding a button does not protect the underlying endpoint.

Check invalid input, an interrupted request, and expired authentication where those cases apply. The application should explain failures and allow a sensible recovery. Use controlled test data and environments rather than experimenting with real guest invitations.

Compare observations with the reported evidence

An assistant may report that a build and unit tests passed. That is useful, but it does not establish that browser navigation, real API wiring, or accessible focus behavior works correctly.

Record defects with steps, expected results, observed results, and the tested version. Pass these reports back to the assistant for focused fixes, then repeat the affected checks. Hands-on testing complements automated coverage and code review by evaluating the complete experience that the code is meant to provide.