@infoxiao

Xiao Ma @infoxiao · 21h

the airgap clip is such a distraction isn't the most juicy part where Noam basically spelt out oai multiagent training recipe? bitter lesson strikes again.

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[cut off] has to choose between, "Okay, do I just return and ask
the question instead of solving the problem?" or "Do I
solve the problem, make an assumption about what
the parent wanted me to do, and just solve it that
way?" [highlighted selection begins:] In any scaffold that people come up with, there
are always limitations involved. The approach that we
wanted to take was to just go toward the extreme end
of baking in as little structure as we could and give
the agents very primitive tools to use, and they figure
out for themselves how to use them effectively. So we
give the agents the ability to message another agent,
and when it messages another agent, it is inserted
into the context. It can do a few other similar things,
but that's basically the core of it. It can just send a
message whenever it wants — just a tool call — and it
can send that to other agents.

They figure out for themselves the best way to
coordinate around that. It turns out that if this is done
well, you get very sophisticated behavior. To me, it
looks a lot like how human collaborators work over
something like Slack, for example. [highlighted selection ends]

[text partly hidden by the Copy / Find Selection / Translate popup:] When [illegible] ... [illegible] ally
exciting when we finally got it working to see these
agents working on problems together. I remember one
[cut off]

multi-agentdwarkesh podcastopenaibitter lessonagent scaffolds