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> The multi-agent coordinator mode in coordinatorMode.ts is also worth a look. The whole orchestration algorithm is a prompt, not code. So much for langchain a

> The multi-agent coordinator mode in coordinatorMode.ts is also worth a look. The whole orchestration algorithm is a prompt, not code. So much for langchain and langraph!! I mean if Anthropic themselves arent using it and using a prompt then what’s the big deal about langchain

rolymath 7mo ago
You didn't even use it yet.
- simianwords 7mo ago
  ?
- space_fountain 7mo ago
  I'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?
ossa-ma 7mo ago
Langchain is for model-agnostic composition. Claude Code only uses one interface to hoist its own models so zero need for an abstraction layer. Langgraph 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.
- simianwords 7mo ago
  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?
  - ossa-ma 7mo ago
    I'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.
    - simianwords 7mo ago
      I 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. What's the value add over doing it with just Python code? I mean you can represent any logic in terms of graphs and states..
      - chaos_emergent 7mo ago
        Most of the value I’ve gotten out of is has been observability. Graph and DAG workflow abstractions just help OTel structure your LLM logs in a clean hierarchy of spans. I could imagine figuring out a better solution to this than the whole graph abstraction. Other than that I’m not too sure.
  - edgyquant 7mo ago
    Use Gemini or codex models
peab 7mo ago
nobody serious uses langchain. The biggest agent products are coding tools, and I doubt any of them use langchain
- holoduke 7mo ago
  Biggest issue is that you need api keys which are extremely expensive. Unusable for normal business.

rolymath 7mo ago

You didn't even use it yet.

simianwords 7mo ago
?
space_fountain 7mo ago
I'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?

ossa-ma 7mo ago

Langchain is for model-agnostic composition. Claude Code only uses one interface to hoist its own models so zero need for an abstraction layer. Langgraph 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.

simianwords 7mo ago
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?
- ossa-ma 7mo ago
  I'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.
  - simianwords 7mo ago
    I 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. What's the value add over doing it with just Python code? I mean you can represent any logic in terms of graphs and states..
    - chaos_emergent 7mo ago
      Most of the value I’ve gotten out of is has been observability. Graph and DAG workflow abstractions just help OTel structure your LLM logs in a clean hierarchy of spans. I could imagine figuring out a better solution to this than the whole graph abstraction. Other than that I’m not too sure.
- edgyquant 7mo ago
  Use Gemini or codex models

peab 7mo ago

nobody serious uses langchain. The biggest agent products are coding tools, and I doubt any of them use langchain

holoduke 7mo ago
Biggest issue is that you need api keys which are extremely expensive. Unusable for normal business.