Comment by lossolo

And they didn't monitor what was going into the training data, so if one instance achieved its results through RL reward hacking (in other words, cheating), it just went into the training data, and other agents later used that pattern. I'm not sure whether that's a lack of preparation, negligence or incompetence, but they literally trained later checkpoints on the rollouts from the HF hack.

So it seems that OpenAI hacked so many systems not because they have superior models, but because of how poor their training, sandboxing and evaluation pipeline was compared to Anthropic's.