Harrison Chase of LangChain on Deep Agents, LangSmith, and Earning Trust | NVIDIA AI Podcast Ep. 297

And so I think, like, these always on asynchronous event driven agents, that will be a really big productivity unlock. And especially at enterprises, there's so many events that are just triggering, triggering, triggering. And so if you can have agents listening to those and firing off, I think that will be a massive game. Welcome to the NVIDIA AI podcast. I'm Noah Kravitz. Our guest today is Harrison Chase. Harrison is CEO and cofounder of Langchain, one of just the most incredible stories of this whole generative AI era that we're in. As Harrison will get into in a minute, Langchain was founded about three years ago, over a billion downloads. The whole point is to help developers build applications with LLMs and now getting into agents and Ingentic frameworks and all that great stuff. So we're gonna get into it in a moment. Harrison, thanks so much for joining the AI podcast, and welcome. Thanks for having me. Excited to be here. So let's start about three years ago. You started Langchain with this premise of building tools so developers could build apps with LLMs. What did you see back then that either others didn't or even if they did, you saw and just thought, this is where things are going. This is where where I'm headed. What what got us really interested was seeing the applications that people were building on top of the LLMs Right. And the systems they were building around the LLMs in order to power those applications. And those systems had a lot of similarities with with each other even early on. And and even early on, we could tell that they would get quite complex over time. And so a lot of what we built is tools to help people build these systems, these agents, which we now call agents around around these LLMs, and and figuring out what the common patterns are and the common's tooling is and making it really easy for anyone to do so. Right. And so now you've coined this I don't wanna say this term, but I Langshan, talk you talk about, deep agents. Yeah. So what is a deep agent? And then maybe we can get into talking about the enterprise, and why would an enterprise in particular care about that distinction? Yeah. So about a year ago, we saw, a few really interesting things. So maybe even backing up, like, you know, three years ago. Great. Like, LLMs, you wanna connect data, you wanna connect these other things to them. Fantastic. How do you do that? Turns out it's really hard, and and the best way to do that for for different types of agents was actually pretty different. You would build different scaffolding. You would build different workflows around the LLMs. About a year ago, we saw Cloud Code come out. We saw Manus come out. We saw Deep Research come out. And under the hood, all of these had the same kind …