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AI system security and observability

Judgments in this source concerning AI system security and observability. Explora 1 punto de vista con evidencias de 1 fuente.

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1 personas · 1 fuentes · 1 opiniones expresadas

Lilian Weng

Harness edits must be limited to editable surfaces, with read-only safeguards

Harness edits are restricted to the harness workspace only; the runs directory, tracer, verifier, and LLM configuration are read-only to prevent reward hacking—such as disabling the verifier, swapping the model, or raising the reasoning budget—ensuring gains remain attributable solely to harness changes.

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Harness Engineering for Self-Improvement

Extracto original

Edits are only applied to the harness workspace. the runs directory, tracer, verifier, and LLM configuration are read-only, which disables a set of reward hacking (e.g disabling the verifier, swapping the model, or raising the reasoning budget) and thus it can keep every recorded gain attributable to harness edits.
Contexto

Decision observability : every edit is paired with a prediction for the next round to validate. An agent (“Evolve agent”) reads the repo and decides which component to edit, and then produces the edit and the reasoning behind it. Every edit is a file-level, falsifiable claim and can be verified in the next round, under two constraints: (1) (2) Edits are evidence-driven, with a manifesto entry: the failure evidence’s name, the inferred root cause, the targeted fix, and a predicted impact comprising both expected fixes and at-risk regressions.

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