Should passing AI evals be enough to merge changes?
are becoming common for AI changes, but many teams still do manual checks before approving . Those checks can include traces, prompts, , and production metrics. The main question is whether passing tests gives enough confidence that the AI change is safe for real users.
may not show every issue in how an answer was produced, how outside information was found, or how the change behaves after release. Teams still need to decide what humans should review when the automated checks pass.
Key points
- are now common in AI development workflows.
- Some teams still manually inspect traces, prompts, , and production metrics.
- The open question is whether passing evals is enough to merge an AI change.
- may still catch risks that automated checks miss.
- should include cost and token behavior in their .