This method is for training. They are using a stop-gradient to 'shield' some tokens from contributing to prediction of the immediate next token, and thus producing a stream of tokens that are only used for longer term prediction.

This is a bit more low level than the usual prompt engineering approaches, and to my mind, a bit more promising. There's more easily measurable results, and I've seen other context where a well placed stop-gradient does wonders...