Lance Martin
speaker
624 appearances
1 recordings
1 series
first heard Sep 2025
last heard Sep 2025
Lance Martin’s voice in public audio — every appearance, attributed to the second.
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And then when you try to compile the full result, in your example of coding, there could be tricky conflicts.
I found this to be the case as well.
And I think a perspective I like on this is use multi-agent in cases where there's very clear and easy parallelization of tasks.
Cognition and Walden Jens spoke on this quite a bit.
He talks about this idea of kind of read versus write tasks.
So, for example, if each sub-agent is writing some component of your final solution, that's much harder.
They have to communicate like you're saying.
And agent-to-agent communication is still quite early.
But with deep research, it's really only reading.
They're just doing context collection.
And you can do a write from all that shared context after all the subagents work.
And I found this worked really well for deep research.
And actually, Anthropic reported on this too.
So their deep researcher just uses parallelized subagents for research collation, and they do the writing in one shot at the end.
So this works great.
So it's a very nuanced point that what you apply context isolation to in terms of the problem, yes, you can see this is their work, matters significantly.
Coding may be much harder.
In particular, if you're having each subagent create one component of your system, there's many potentially implicitly conflicting decisions each of the subagents are making.
When you try to compile a full system, there may be lots of conflicts.
With research, you're just doing context gathering in each of those sub-agent steps, and you're writing in a single step.
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