In this post
What they do
- LangChain provides building blocks: model wrappers, prompt templates, retrievers and tool interfaces.
- LangGraph models an application as a graph of steps with shared state, which suits agents that loop, branch and wait for people.
What they save you
Common plumbing: connecting to many model providers, loading documents, calling tools and managing state between steps.
What they cost you
- Another layer to learn and to keep up with as it changes.
- Abstractions can hide what is actually sent to the model, which makes debugging harder.
A sensible rule
Start with the model provider’s own client and plain code. Adopt a framework when you are repeating the same plumbing, and make sure you can still see every prompt and tool call. The skill that transfers is the design: tools, state, limits and evaluation.
Sources and further reading
- LangChain documentation. python.langchain.com.
- LangGraph documentation. langchain-ai.github.io/langgraph.
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