LangChain was basically the default starting point for anyone building LLM apps back in 2022-2023, and tbh it still has the widest integrations of anything out there. Connecting LLMs to vector stores, APIs, memory modules, custom tools, it handles all of that without you having to stitch libraries together yourself.
The honest pain point is the learning curve once you go beyond hello-world. The docs have improved a lot but they can still lag behind new releases, and if you pin versions poorly, upgrades can break things in weird ways. For teams who know what they're doing it saves real dev time. For newcomers, the abstraction can feel like too much magic happening under the hood.
Also worth flagging: parts of LangChain are being sunset in favor of LangGraph, especially for agent use cases. Not a dealbreaker, but something to be aware of before you build something production-critical on the older chains.
