Equation 27 · Measuring AI Agent Reliability: What the Evidence Actually Supports
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Symbol k
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superscript
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A single successful run is evidence that a task is solvable, not evidence that a system solves it reliably, and the statistics that separate the two claims already exist: pass@k for whether at least one of several attempts succeeds, pass ^k for the much stricter question of whether every one of them does, confidence intervals for whether an observed difference is more than noise, time-horizon curves for how reliability changes as a task grows, and a clear accounting of how a number was elicited before it is compared against how a system actually behaves once deployed. None of this is a call for more skepticism in the abstract. It is a call to ask, of any reported agent capability, which of…
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A single successful run is evidence that a task is solvable, not evidence that a system solves it reliably, and the statistics that separate the two claims already exist: pass@k for whether at least one of several attempts succeeds, pass ^k for the much stricter question of whether every one of them does, confidence intervals for whether an observed difference is more than noise, time-horizon curves for how reliability changes as a task grows, and a clear accounting of how a number was elicited before it is compared against how a system actually behaves once deployed. None of this is a call for more skepticism in the abstract. It is a call to ask, of any reported agent capability, which of these specific measurements was actually taken — and to treat a claim that skips all of them as an anecdote wearing a percentage sign.
For background, read the article’s source list.
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