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We chose LangGraph to build our coding agent

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Re: We chose LangGraph to build our coding agent

#3
I read the article but have yet to understand why someone would want to use a framework that introduces meaningless abstractions that are not properly documented or well maintained -aka, they often introduce breaking changes.

I’m interested in a useful agentic framework but LangGraph doesn’t seem to cut it.

Re: We chose LangGraph to build our coding agent

#4
post #3

I read the article but have yet to understand why someone would want to use a framework that introduces meaningless abstractions that are not properly documented or well maintained -aka, they often introduce breaking changes. I’m interested in a useful agentic framework but LangGraph doesn’t seem to cut it.

fully agree that LangChain is a meaningless abstraction but I've found that the graph abstraction that LangGraph uses is a very useful mental model for thinking about an agentic flow

Re: We chose LangGraph to build our coding agent

#5
post #3

I read the article but have yet to understand why someone would want to use a framework that introduces meaningless abstractions that are not properly documented or well maintained -aka, they often introduce breaking changes. I’m interested in a useful agentic framework but LangGraph doesn’t seem to cut it.

Would you use different framework?

Re: We chose LangGraph to build our coding agent

#6
I found that the PydanticAI [0] framework strikes a perfect balance between control and abstraction.

I’m building a non trivial AI app and the validation and dependency injection is such a great addition compared to using the LLM libraries directly.

[0] https://ai.pydantic.dev/

Re: We chose LangGraph to build our coding agent

#7
post #3

I read the article but have yet to understand why someone would want to use a framework that introduces meaningless abstractions that are not properly documented or well maintained -aka, they often introduce breaking changes. I’m interested in a useful agentic framework but LangGraph doesn’t seem to cut it.

Pretty much this

Not to mention most of those frameworks were almost vibecoded.

They offer very little on top of what you could do it yourself

But of course some people think "if it exists we need to use it"

Re: We chose LangGraph to build our coding agent

#8
post #3

I read the article but have yet to understand why someone would want to use a framework that introduces meaningless abstractions that are not properly documented or well maintained -aka, they often introduce breaking changes. I’m interested in a useful agentic framework but LangGraph doesn’t seem to cut it.

I think the main thing LangGraph adds is a state machine framework for human in the loop with time travel.

So if you have an authoring workflow where a doc goes through a bunch of steps, and at some steps the analyst might want to fix some LLM output manually, and try a couple of things and then go back to the way it was before and try again, it will do that and you won't have to make your own state machine.

Re: We chose LangGraph to build our coding agent

#9
post #3

I read the article but have yet to understand why someone would want to use a framework that introduces meaningless abstractions that are not properly documented or well maintained -aka, they often introduce breaking changes. I’m interested in a useful agentic framework but LangGraph doesn’t seem to cut it.

I think the main thing LangGraph adds is a state machine framework for human in the loop with time travel. So if you have an authoring workflow where a doc goes through a bunch of steps, and at some steps the analyst might want to fix some LLM output manually, and try a couple of things and then go back to the way it was before and try again, it will do that and you won't have to make your own state machine.

Now is it actually a state machine or is it just well logged?

Re: We chose LangGraph to build our coding agent

#10
post #6

I found that the PydanticAI [0] framework strikes a perfect balance between control and abstraction. I’m building a non trivial AI app and the validation and dependency injection is such a great addition compared to using the LLM libraries directly. [0] https://ai.pydantic.dev/

They recently added MCP support: https://ai.pydantic.dev/mcp/

Have you tried it?

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