Lance Martin

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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

So I basically wanted to allow different code agents to write Landgraf for me by retrieving from our docs.

I tested Cloud Code and Cursor.

I used three different approaches for grabbing documentation.

So one was I took all of our docs, around 3 million tokens.

I indexed them in the Vector Store, just a classical Vector Store search and retrieval.

I also use an lms.txt with just a simple file loader tool.

So that's kind of more like the agentic search.

Just basically look at this lms.txt file, which has all of the URLs of our documents with some basic description, and let the LM, or the code agent in this case, just make tool calls to fetch specific docs of interest.

And I also just tried context stuffing.

So take all the docs, 3 million tokens, and just feed them all to the code agent.

So these are some results I found comparing cloud code to cursor.

And interesting, what I actually found, this is only my particular test case, but I actually found that lm.txt

with good descriptions, which is just very simple.

It's just basically a markdown file with all the URLs of your documentation and like a description of what's in that doc.

Just that passed to the code agent with a simple tool just to grab files.

is extremely effective.

And what happens is the code agent can just say, okay, here's the question.

I need to grab this doc and read it.

I'll read it.

I need to grab this doc, read it, read it.

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