Snapshot-and-fork baselines for reproducible AI agent evaluations
This story is from 2026-09-17. It is preserved in the archive; the latest stories are on the live feed.
An agent evaluation is only as reproducible as its least-documented input. Snapshots and forks reset the environment between runs, but a snapshot does not tell a later reader which code revision, fixture version, task definition, or scoring rubric a run used. That has to live beside the run, in a b…
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- 2026-09-17 15:51 · DEV Community — Machine Learning
Snapshot-and-fork baselines for reproducible AI agent evaluations