@omarsar0: Highly recommended. I've often claimed there's huge alpha in building agent harnesses. Turns out harnesses are composit…
Summary
Discusses the concept of agent harnesses as compositional generalizers for scaling generalization in models, referencing the RLM harness.
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Cached at: 07/21/26, 02:46 PM
Highly recommended.
I’ve often claimed there’s huge alpha in building agent harnesses.
Turns out harnesses are compositional generalizers. The RLM harness is an instance of this. This could lead to interesting and efficient new ways to scale generalization in models.
Something really neat about this work that might not get picked up easily: for post-training, you may not need long-horizon rollouts to train long-horizon agents. You could train on short tasks where rewards are cheap and verification is easy, and let the harness carry it 8-32x further.
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