I don’t see Tao suggesting what you have suggested there. Instead he suggests that humans responsibly disclose AI use, and that mathematicians develop a set of norms to deal with an overabundance of AI generated results. For example, he suggests that authors should be able to discuss their results in detail to demonstrate understanding before publication.

I can't help but wonder about the human motivation there though. For instance as it became increasingly clear that LLMs were capable (and becoming ever more capable) of competently solving meaningfully complex software development tasks, suddenly then there came to be a lot of talk of 'prompt engineering' as a skill. The chronology doesn't make a ton of sense unless you consider that the main motivation may have been simply looking for a way to keep software engineers in the loop.

Pure math is relatively outside my domain, so I find it difficult to grok the exact relevance of the various published discoveries beyond that they are not insignificant, and LLM competence is expanding quite steadily across the field. If this trend continues to the point of LLMs being able to competently expand pure math, it seems somewhat predictable to expect there to be a number of people aiming to find ways to try to keep human mathematicians in the loop.

I've no idea what I think about this one way or the other, beyond that it's certainly a phenomena and one that's going to drive motivated reasoning that may not be entirely sound.