G2

AS

aditya s.

Software Engineer

Information Technology and Services

Mid-Market (51-1000 emp.)

9/22/2026

"LangChain Makes LLM Workflows Easy with Flexible RAG and Agent Building Blocks"

4.5/5

What do you like best about Langchain?

What I like most about LangChain is that it saves me from having to build everything from scratch when I’m working with LLMs. It makes it fairly easy to connect different models, tools, APIs, and data sources, and it gives me a solid starting point for workflows like RAG and agents. It’s been especially helpful when I’m experimenting with different approaches and want the flexibility to avoid getting locked into a single model provider. Review collected by and hosted on G2.com.

What do you dislike about Langchain?

Langchain can sometimes feel unnecessarily complicated. There are a lot of abstractions to learn, and when something goes wrong, it isn’t always clear where the issue is coming from. I’ve also noticed that changes between versions can take extra effort to accommodate, especially when updating existing code. Review collected by and hosted on G2.com.

What problems is Langchain solving and how is that benefiting you?

It mostly saves me from having to write all the boilerplate needed to connect LLMs to different tools, APIs, and data sources. I use it for things like RAG and for experimenting with different models, and having those building blocks already in place makes it much faster to put together and test AI features. Review collected by and hosted on G2.com.