Eval quality auditing may be AI's hottest skill: traces, not scores, reveal benchmark flaws
IanArawjo · x · 2026-09-12
Vtrivedy10 argues that building and auditing eval/environment quality is maybe the top AI skill right now. trq212 adds that pass/fail scores alone are nearly impossible to interpret—many benchmark failures come from overly strict hidden tests, sometimes the model's answer is more sensible than the expected result.
Key points:
- Single scores tell you little about task construction; agent traces tell you a lot
- You can't tell whether a task is hard due to model capability gaps or missing output-format info
- Method: run a council of models at different strengths, collect all trajectories, then deploy Trace Analysis Agents with privileged access to the environment definition, verifier logic, inputs, and harness
- Aggregate feedback across trajectories to catch verifier and instruction issues
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