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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Latent Space: The AI Engineer Podcast · Context Engineering for Agents - Lance Martin, LangChain · 11 Sep 2025 podcast

In this case, they're talking about agent-to-agent boundaries and summarizing, for example, message history.

But the same challenges apply to summarizing, for example, the full contents of token-heavy tool calls so the model knows what's in context.

I basically spent a lot of time prompt engineering to make sure my summaries capture with high recall what's in the document, but compress the content significantly.

That's exactly right.

And actually, one of the other big themes I hit and talk about quite a bit is context isolation with multi-agent.

And I do think this does link back to the cognition take, which is interesting.

So their argument against multi-agent

It's literally called don't build multi-agent.

Correct.

And what they're arguing is a few different things.

One of the main things is that it is difficult to communicate sufficient context to sub-agents.

They talk a lot about spending time on that summarization or compression step.

They even use a fine-tuned model to ensure that all the relevant information is

So they actually show it a little bit down below as kind of a linear agent.

But even at those agent-agent boundaries, they talk a lot about being careful about how you compress information and pass it between agents.

That's one of the most important points about this context isolation kind of bucket.

So Cognition argues, which actually I think is a very reasonable argument, they argue don't do subagents because each subagent implicitly makes decisions and

And those decisions can conflict.

So you have sub-agent one doing a bunch of tasks, sub-agent two doing a bunch of tasks.

Those kind of decisions may be conflicting.

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