LANGCHAIN VS LANGGRAPH: WHAT'S THE DIFFERENCE?

LangChain is a library of integrations and abstractions; LangGraph is a way to express an agent's control flow as an explicit state machine. They come from the same people and are frequently used together, so "which should I pick?" is usually the wrong question. The real one is whether your control flow deserves to be a first-class, inspectable object.

What LangChain is for#

LangChain's value has always been breadth: a common interface over model providers, vector stores, document loaders, retrievers, output parsers and tools. When you need to talk to something and would rather not write the client yourself, that breadth is the product.

Its historical weakness is the same thing. Deep abstraction stacks are hard to debug when a prompt goes wrong three layers down, and the criticism that you end up reading library source to understand your own program is fair more often than its defenders like.

What LangGraph is for#

LangGraph asks you to declare the nodes and the edges — what steps exist, what state they share, and which transitions are legal. The agent loop stops being implicit in a framework's internals and becomes a graph you drew.

Three things fall out of that, and they are the reason to use it:

• Inspectable state. You can see what the agent knows at each step, which turns "why did it do that?" from archaeology into reading.
• Durability. Because state is explicit, a run can be checkpointed and resumed — which matters enormously the first time a long-running agent dies half-way.
• Deliberate human gates. A pause for approval is a node, not a hack.

Choosing#

Use LangChain's pieces when you want integrations. Reach for LangGraph when the cost of an unexpected step is high enough that you want the permitted steps written down — which, as we argue in What Is an AI Agent?, is the moment agency stops being a feature and starts being a risk.

If your control flow is genuinely linear, you need neither. See Do You Need an Agent Framework at All?

The comparison people actually mean#

Nine times in ten, "LangChain vs LangGraph" is really "LangGraph vs a team of role-playing agents" — that is, explicit graphs versus emergent coordination. That comparison is CrewAI vs AutoGen, and the trade is control against expressiveness.