Episode Details

As alluded to on the pod, LangChain has just launched LangChain Hub: “the go-to place for developers to discover new use cases and polished prompts.” It’s available to everyone with a LangSmith account, no invite code necessary. Check it out!

In 2023, LangChain has speedrun the race from 2:00 to 4:00 to 7:00 Silicon Valley Time. From the back to back $10m Benchmark seed and (rumored) $20-25m Sequoia Series A in April, to back to back critiques of “LangChain is Pointless” and “The Problem with LangChain” in July, to teaching with Andrew Ng and keynoting at basically every AI conference this fall (including ours), it has been an extreme rollercoaster for Harrison and his growing team creating one of the most popular (>60k stars at time of writing) building blocks for AI Engineers.

LangChain’s Origins

The first commit to LangChain shows its humble origins as a light wrapper around Python’s formatter.format for prompt templating. But as Harrison tells the story, even his first experience with text-davinci-002 in early 2022 was focused on chatting with data from their internal company Notion and Slack, what is now known as Retrieval Augmented Generation (RAG).

As the Generative AI meetup scene came to life post Stable Diffusion, Harrison saw a need for common abstractions for what people were building with text LLMs at the time:

* LLM Math, aka Riley Goodside’s “You Can’t Do Math” REPL-in-the-loop (PR #8)

* Self-Ask With Search, Ofir Press’ agent pattern (PR #9) (later ReAct, PR #24)

* NatBot, Nat Friedman’s browser controlling agent (PR #18)

* Adapters for OpenAI, Cohere, and HuggingFaceHub

All this was built and launched in a few days from Oct 16-25, 2022.

Turning research ideas/exciting usecases into software quickly and often has been in the LangChain DNA from Day 1 and likely a big driver of LangChain’s success, to date amassing the largest community of AI Engineers and being the default launch framework for every big name from Nvidia to