Final Scores Lie: How to Evaluate Long-Horizon Agents
This story is from 2026-09-28. It is preserved in the archive; the latest stories are on the live feed.
Originally published on AI Tech Connect . What you need to know One number is not an evaluation. Two agents that both score 40 per cent on a long-horizon task can be failing for entirely different reasons, and those reasons need entirely different fixes. Variance is a first-class metric. Running an…
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- 2026-09-28 16:37 · DEV Community — Machine Learning
Final Scores Lie: How to Evaluate Long-Horizon Agents