How to Stop Shipping Low-Quality RL Environments (with Examples)

Broken RL harnesses can actively degrade model behavior instead of improving it.

The post argues that low-quality RL environments are not harmless infrastructure bugs; they can make models worse by feeding them broken learning signals. Based on years of inspecting trajectories, the author highlights recurring environment and harness failures that teams need to fix. The practical lesson is to debug the training environment, grader, and interaction traces before blaming the model or scaling training.

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