auto: 2026-08-29T17:32:52Z [skip ci]
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@ -75,6 +75,11 @@ models, execute models against them, debug agent scaffolds when they fail, and
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analyze the failures that result. I have led environment design and evaluator
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analyze the failures that result. I have led environment design and evaluator
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calibration; most of it is built in [Harbor](https://github.com/harbor-framework/harbor).
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calibration; most of it is built in [Harbor](https://github.com/harbor-framework/harbor).
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Calibration passes often reveal that a rubric is measuring something other than
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what the task was designed to measure: a task-design failure, not a grading one.
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I calibrate before a task is scaled, because redesigning a task is cheap and
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rescoring a finished run is not.
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For a similar methodology on public data, see [The Specification
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For a similar methodology on public data, see [The Specification
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Dilemma](/essays/specification-dilemma/) — pre-registered, matched-pairs, with
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Dilemma](/essays/specification-dilemma/) — pre-registered, matched-pairs, with
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its instrumentation failures reported in full.
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its instrumentation failures reported in full.
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