Q: What is LangChain?

LangChain is the most popular open source framework for building LLM applications. It appeared in late 2022, right as the industry started building on top of LLM APIs, and it grew into the largest ecosystem in the space.

What it gives you is building blocks. Model wrappers, so you can swap one LLM provider for another without rewriting your code. Prompt templates. Document loaders that pull in PDFs, websites, and databases. Text splitters for chunking. Retrievers for RAG. Pre-built chains that connect these pieces into working pipelines. For almost any tool or service you want to connect, someone has already written the LangChain integration.

LangChain also sits inside a wider family. LangGraph, from the same team, handles agent workflows. LangSmith handles tracing and debugging. Together they cover most of what an LLM application needs.

Should you use it? It's a strong choice, and job postings mention it often, so it's worth knowing. But don't start there. LangChain abstracts away the fundamentals, and if you learn the abstraction before the fundamentals, you won't be able to debug your own system when it breaks. Learn raw API calls, RAG, and tool calling in plain Python first. Then LangChain becomes easy, because you'll recognize what every component is doing under the hood.