This only shows the lack of understanding the majority of readers have about post training LLMs. This capability did not emerge out of nowhere. There are problems in the post training datasets which are incredibly similar to the ones in TFA, where you essentially abstract out the 'jailbreak' or 'cheat' - in simple language - they are training the models to find short cuts or cheat. So it shouldn't be surprising that the model generalized that ability. But, both the writers and readers of this type of content act out surprised and mesmerized and it makes me think that we need to improve our understanding of how LLMs are trained and built.