Search RAG Evaluation
Search RAG - Human Oversight and Stress Testing
Human review is not a substitute for metrics. It is how you find the failures metrics do not know yet.
Why this matters in production
Automated checks catch format, trace, and grounding patterns. Humans catch meaning, risk, misleading wording, and domain-specific nuance.
This works in demos but fails in production: random spot checks with no annotation guide and no path back into tests.
What breaks
Reviewers disagree. Feedback stays in tickets. Edge cases are fixed once and forgotten. High-risk answers are sampled at the same rate as low-risk answers.
Human oversight without stress-test conversion is expensive memory loss.
What works
Sample by risk. Give reviewers a rubric: evidence support, citation correctness, missing evidence, ambiguity handling, permission concerns, and user usefulness.
Do not ask humans whether they 'like' the answer. Ask what failed in the trace and what test should exist forever because of it.
Practical guidance
Turn every serious human finding into a regression case, stress test, or metric improvement. Otherwise the same failure will return under a different prompt.
What happened
Reviewers repeatedly found answers that were technically cited but operationally misleading, especially when context was partial.
Why retrieval failed
Automated checks verified citation presence but did not understand whether the answer overstated weak evidence.
Why it was hard to detect
The issue was subjective enough that metrics missed it, but consistent enough that humans recognized the pattern.
What fixed it
The fix was an annotation category for 'overstated evidence,' a stress-test set for partial context, and prompt rules for caveated answers.
Practical Guidance
Sample by risk.
Use review rubrics.
Convert human findings into tests.