Noam Brown says multi-agent systems can speed up work by scaling test-time compute in parallel instead of purely serially, but this is less efficient because no individual agent has the full context.

“you know if you're if you're gonna found a company you want to get a group of people together so you can go faster so same thing with these AI models that it helps to just have multiple agents working on something because they can just go faster and so multi-agents is a way of scaling test time compute in parallel instead of purely serial and it is like less efficient because it doesn't have it's not like a single agent has all the context to itself but it is like”

“a very effective way of scaling test time compute if it's done well.”