Evals And Observability easy
Your CI gate runs a 150-case eval scored on a 100-point rubric. A prompt tweak scores 84 against a baseline of 86, and repeated baseline runs vary by about 1 point. What should the gate do?
- A Pass it, because any drop smaller than 10 points is within normal LLM variance and not worth investigating.
- B Flag it for review, since a 2-point drop exceeds run-to-run noise and is a common gate threshold.
- C Pass it, then turn off the gate for prompt tweaks and run the eval only when the underlying model changes.
- D Replace the gate with a 1,000-case public benchmark, since a larger set makes small drops irrelevant to quality.
Answer: B. Flag it for review, since a 2-point drop exceeds run-to-run noise and is a common gate threshold.
Gates commonly fail on a 2 to 5 point drop. The threshold should sit above measured run-to-run noise, so it trades occasional false alarms for catching real regressions. Assuming any small drop is noise is tempting, but here the 2-point drop is twice the observed variance. A looser threshold makes sense only if repeated baseline runs show noise as large as the drop.
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Get the appRelated questions
- In one release, a RAG assistant got a new embedding model and a new chunking strategy, and the end-to-end judge score dropped 6 points. The team only tracks the end-to-end score and has spent a week tweaking the generation prompt with no recovery. What is the best next step?
- Over two months, your team iterated through 40 prompt versions, each tuned against the same 150-case golden set. The offline score rose from 72 to 91. Online task completion and retry rate have not changed. What is the most likely problem, and what is the fix?
- A prompt change produced an impressive answer in a live demo for leadership. The PM wants to ship it today. What should you do?
- You plan to replace human graders with an LLM judge for your answer-quality eval. Before trusting its scores in a CI gate, what should you do first?
- After you swap to a smaller model, p95 latency falls from 900 ms to 350 ms and the ops dashboard is all green. Leadership asks whether answer quality is still fine. What is the right response?
- Your CI gate fails any prompt change that drops the score 3 or more points on a 100-point rubric over 60 cases. Production generates at temperature 0.7. Running the eval twice on the same commit gives scores that differ by up to 4 points, and engineers have started rerunning failed gates until they pass. How do you fix the gate?