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Your agent-gym score rises when you add workers. Is the agent better?

A frozen policy jumps from 70% to 90% after parallelizing its evaluation. Reconstruct the denominator, separate runner faults from policy behavior, and design the experiment that could invalidate the gain.

Updated Oct 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.

A frozen policy jumps from 70% to 90% after parallelizing its evaluation. Reconstruct the denominator, separate runner faults from policy behavior, and design the experiment that could invalidate the gain.

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FEDITOR'S NOTE

An original diagnostic exercise with synthetic counts. Company tags describe relevance. The interviewer is scoring experimental control and trustworthy accounting, not recognition of a published benchmark result.

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