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auto: 2026-08-29T17:32:52Z [skip ci]

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Levi Neuwirth 2026-08-29 19:32:52 +02:00
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@ -75,6 +75,11 @@ models, execute models against them, debug agent scaffolds when they fail, and
analyze the failures that result. I have led environment design and evaluator
calibration; most of it is built in [Harbor](https://github.com/harbor-framework/harbor).
Calibration passes often reveal that a rubric is measuring something other than
what the task was designed to measure: a task-design failure, not a grading one.
I calibrate before a task is scaled, because redesigning a task is cheap and
rescoring a finished run is not.
For a similar methodology on public data, see [The Specification
Dilemma](/essays/specification-dilemma/) — pre-registered, matched-pairs, with
its instrumentation failures reported in full.