https://alexzhang13.github.io/blog/2026/harness/
> A good harness is a harness that reduces unfamiliar problems to familiar ones and reduces complex problems to simple ones. In other words, even if the state s is out-of-distribution (OOD) to what any individual language model call was trained for, a good harness produces observations o that are locally in-distribution (LID), which we define as every individual LM call over this observation being in-distribution with respect to the training data.
> A good harness is a harness that reduces unfamiliar problems to familiar ones and reduces complex problems to simple ones. In other words, even if the state s is out-of-distribution (OOD) to what any individual language model call was trained for, a good harness produces observations o that are locally in-distribution (LID), which we define as every individual LM call over this observation being in-distribution with respect to the training data.
Alex L. Zhang
Language model harnesses are compositional generalizers
Modern post-training brute-forces ever more environments and ever longer horizons, because frontier Transformers are still poor at compositional generalization. A good harness makes every model call locally in-distribution, so what it learns carries across…
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