Restore the Service Without Losing the Clue

When an AI workflow changes unexpectedly, getting it running again matters—but a fast restart can also erase the clue about what changed.

Consider a prompt revision followed by a shift in outputs. A useful incident review would preserve the last-known version and the evaluation cases that previously mattered, then isolate the changed prompt or dependency. Compare the old and new behavior on the same cases, with human review where judgment is needed. That gives the team something concrete to learn from, rather than a vague label like “the model got worse.”

If restoring the earlier version is the safest bounded step, keep the revised version for investigation. Set a review point and agree what evidence would justify trying it again. Recovery should restore useful service; it should not quietly discard the lesson.