I think I'm a bit on the "golden age" side of the question.

The math slopocalypse isn't useful without being able to turn it into math that can be taught to actual humans by finding the underlying unifying principles.

All those O(n log(n)^(1-delta)) results suggest that there's probably a unifying "trick" behind all of them and that there's going to be an upper bound on delta for any problem. You should really be able to teach that in a textbook and then have any human student replicate any of the LLM results as worked problems.

For anything that an LLM manages to prove with thousands or millions of lines of Lean code, there's likely a missing branch of mathematics sitting there somewhere.

Actual humans need to beat on the problems and the LLM-generated solutions until they come up with the underlying principles, probably using AI to help them do it.

You probably won't get there by just asking an LLM to invent a new branch of mathematics and "don't make any mistakes"; the mathematicians who get good at directing LLMs to search for unifying principles, and then synthesizing (and double-checking) the results, will likely be very successful in their field.