What is LangGraph?
LangGraph is a framework by LangChain for building stateful, multi-step AI agent applications using directed graphs, where nodes represent computation steps and edges define the flow between them.
WHY IT MATTERS
Most agent tasks aren't simple request-response. They involve branching logic, cycles (retry loops), state that persists across steps, and human-in-the-loop checkpoints. LangGraph models these as computational graphs.
Each node in a LangGraph is a function that takes state and returns updated state. Edges connect nodes — including conditional edges that route based on state. This makes complex workflows explicit and debuggable, unlike black-box agent loops.
LangGraph's key differentiator is built-in persistence and human-in-the-loop support. You can pause execution at any node, inspect state, get human approval, and resume. For financial agents, this means inserting policy checkpoints at critical points in the workflow.
HOW POLICYLAYER USES THIS
LangGraph agents that handle payments can include PolicyLayer as a node in their graph — a policy checkpoint that validates spending before the transaction node executes. If the policy check fails, the graph routes to an alternative path (e.g., human approval).