With 10,000 agents and $20M of compute this is just brute force search.
It's a bit like telling 10,000 kids there's an easter egg hidden over there, pointing to one corner of your yard (or having "heard a rumor" it was hidden in that corner).
If you have $20M to spend on your problem, then yes, AI brute force search is an option, but unless you know a solution is possible (as OpenAI did here), you may still be wasting your money.
You jest and that is OK. Brute force search is not something you can do over math problems of that difficulty or anything with combinatorial complexity.
To me it feels closer to taking the top 10k human mathematicians on a large retreat for a year and having them self organize to collectively solve this problem—not kids and easter eggs.
I'm not joking. Compare to a super-human MCTS system like AlphaGo or Stockfish - once you condense the expertise of your top 10K world experts into a board evaluation or policy function, then the rest is brute force.
Whether this type of agentic swarm approach can be considered closer to MCTS (search), or closer to a less structured GOFAI blackboard type approach (perhaps more like your mathematician retreat) I'm not sure - I don't think they've released any details of the prompt(s) and how these agents were collaborating and building on each others work.
The other part of my easter egg analogy is the direction to "look over there", corresponding to OpenAI specifically asking their hoard of mathematicians to work on Navier-Stokes since they knew it was solvable/determinable, and they certainly had the public work that Buckmaster/Levant were building on as further direction, as well as perhaps their prompts. Unlike Buckmaster/Levant, this wasn't just a couple of humans with a university research grant budget, this was apparently a not-so-small team at OpenAI (says Buckmaster, per a group call he had with OpenAI), with an unlimited budget, so it's hardly surprising (or in the least bit impressive) that they were able to duplicate and surpass their work.