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# You Cannot Benchmark a Coworker

**[Medium](https://daily.dev/sources/medium_js)** · 32 min read · 0 upvotes · 0 comments

## Summary

A benchmark result is not a deployment decision. This essay argues that evaluating AI agents requires answering four distinct questions in order: capability (can it do the task?), reliability (how consistently across repeated realistic trials?), autonomy fitness (which specific actions are safe to run without human approval?), and governance readiness (does every run produce auditable evidence?). The pass^k metric — requiring an agent to succeed on every one of k repeated trials — is introduced as a more honest reliability measure than single-run accuracy. The essay walks through a concrete customer support scenario showing how a capable agent can still fail on reliability, autonomy, and governance dimensions. It also covers defenses against coaching an in-house evaluation suite, the danger of correlated failures across agent fleets, and how emerging AI regulations in the EU, US, UK, and Canada are converging on the same pairing of logged reliability evidence and repeated-trial measurement.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/@peter.mccann.strain/you-cannot-benchmark-a-coworker-5d9b8f0fe063>

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---

Tags: [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#ai-governance](https://daily.dev/tags/ai-governance)

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