That data goes into pretraining the initial model. The agentic post-training relies on the model making stochastic exploration. So in a sense it learns via trial and error. By the accounts I have read, this second stage is the dominant reason we have seen the increase in model capabilities in the past year. It is still not clear how innovative the models can be, but they are not just relying on static data.