What is LangChain?

LangChain is a framework for building AI applications that can do real work, not just chat. It lets you connect an AI to databases, APIs, and web searches so the AI can look things up and take actions. It was created in 2022 and quickly became one of the most popular open source tools for building agentic AI systems.

The core idea is “chaining.” You break a complex task into smaller steps, and each step uses an AI model or a tool. For example, you might chain together: search a database for relevant info, pass that info to an AI model, have the model summarize it, and return the result. LangChain provides the connectors for databases, APIs, and file systems. It provides memory modules so your AI can remember past conversations. And it provides agent frameworks that let the AI decide which tools to use and in what order.

People use LangChain to build chatbots that can look up real information, document Q&A systems that search through your files, and automation workflows where the AI orchestrates multiple steps. If you want to build something where an AI does more than just answer questions, LangChain is one of the first tools you’d reach for.

More recently, the LangChain team released LangGraph, which takes the chaining concept further and lets you build more complex workflows with loops and branching. LangGraph is becoming the preferred choice for more advanced agentic applications.

I used LangChain on a prototype at my day job. I was trying to add end-to-end automation to a front-end product I’m working on. It was a good fit for performing various disparate tasks in a row, like a human would.