Langchain is for model-agnostic composition. Claude Code only uses one interface to hoist its own models so zero need for an abstraction layer.
replyLanggraph is for multi-agent orchestration as state graphs. This isn't useful for Claude Code as there is no multi-agent chaining. It uses a single coordinator agent that spawns subagents on demand. Basically too dynamic to constrain to state graphs.
You may have a point but to drive it further, can you give an example of a thing I can do with langgraph that I can't do with Claude Code?
replyI'm not an supporter of blindly adopting the "langs" but langgraph is useful for deterministically reproducable orchestration. Let's say you have a particular data flow that takes an email sends it through an agent for keyword analysis the another agent for embedding then splits to two agents for sentiment analysis and translation - there is where you'd use langgraph in your service. Claude Code is a consumer tool, not production.
replyI see what you mean. Maybe in the cases where the steps are deterministic, it might be worth moving the coordination at the code layer instead of AI layer.
replyWhat's the value add over doing it with just Python code? I mean you can represent any logic in terms of graphs and states..
Use Gemini or codex models
replynobody serious uses langchain. The biggest agent products are coding tools, and I doubt any of them use langchain
replyBiggest issue is that you need api keys which are extremely expensive. Unusable for normal business.
replyYou didn't even use it yet.
replyI've tried to use langchain. It seemed to force code into their way of doing things and was deeply opinionated about things that didn't matter like prompt templating. Maybe it's improved since then, but I've sort of used people who think langchain is good as a proxy for people who haven't used much ai?
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