I thought exactly the same at first. But then i wondered if that still holds true with today's advanced thinking, RLHF involved, frontier models. I guess to a certain extend it did indeed behave better, as a reaction to his self description into account.

EDIT: I mean, those systems accumulated so much complexity around the attention based next token predictor.

Training the LLM to do things that the user didn’t explicitly ask for is a good way to get complaints from the users. Doesn’t matter if those things are best practices.