It's not really a problem. We're out of natural tokens anyway. The future is synthetic verifiable traces (already the way we train coding agents).
What does it mean, Is it like when somebody used some coding agent to develop a feature and later input prompts and a resulting PR can be used for training by a presumption that final PR was a correct implementation of a prompt?
The trick is to find the examples that are just in between too difficult and too easy for the existing agent, these have the strongest training signals