You have expressed a few different ideas, so I will address them separately.

> It's not about whether the conjectures themselves are interesting or not, or whether people simply have enough time.

Tao seems to think otherwise, if I am reading him correctly:

I wrote recently about how the collection of good, fruitful open problems is now being mined in a non-renewable fashion, leading to the potential scenario of these problems becoming scarce [0]

Often these solutions are announced in a rush, leaving no time for a proper writeup, the isolation of new methods and ideas, and citing relevant previous work of others. As in all creative professions, this raises severe attribution and plagiarism questions. [1]

> It's that a bare proof made by a machine doesn't actually do much for us.

I get it, and I think the same can be said about all sorts of human endeavors.

> There is not some set of problems that, once finished, will amount to some kind of final, correct system and we can call it a day and, like, utilize it.

Sure. Although there are certainly practical applications to be found along the way. E.g. proving P=NP would be potentially very significant in the real world. I think we agree.

> "Mathematics" is the people doing it (the "mathematical community" Tao references below)

Sure. And the same can be said again about all sort of human endeavors. But I don't see how that is a reason to stop using AI in those fields, either. It doesn't subtract anything, in the same way that chess engines didn't destroy the love of the game for chess.

And just like in chess, these AIs can be used to gain a deeper understanding. Including, but not limited to, explaining to humans the proof they just came up with.

[0] https://mathstodon.xyz/@tao/117237320796901560

[1] https://terrytao.wordpress.com/2026/09/11/a-severe-misalignm...