What is LangGraph?

LangGraph extends LangChain to model AI workflows as directed graphs where nodes are functions (LLM calls, tool executions, logic checks) and edges define how control flows between them. Unlike linear chains, graphs can loop, branch, and maintain persistent state across steps.

The key advantage over simple chain-based approaches is statefulness and cycles. An agent can loop to self-correct when its output doesn't pass validation, pause to await human review before taking an irreversible action, or branch into parallel sub-agents based on intermediate results — none of which is possible in a linear pipeline.

LangGraph is used in production for research agents, autonomous email agents, document processing pipelines, and any workflow where the execution path isn't fully determined in advance. It ships with built-in support for checkpointing (resuming interrupted workflows) and LangSmith integration for observability.