You pull out Einstein when you need a breakthrough.

To extend this metaphor or the "million monkeys typing at a million keyboards", it occurs to me that if you can just slightly increase the intelligence of each sub-agent by a tiny amount, the overall end product can shoot up in quality tremendously.

If I can make my small fast AI model just a tiny, tiny bit more capable, and still run 100 of them or 1000 and run an evaluation model on top of that, the overall system capability will scale quickly with tiny increases in base model intelligence.

But some (Meta, Anthropic) suggested that optimizing and extending the "<think>" process can produce extra value. (I do not know if that requires an improved underlying architecture - frontier models architectures are sometimes not public.)