LangGraph
An open-source framework for building AI agents as explicit state graphs, making control flow visible and debuggable.
LangGraph is an open-source framework for building AI agents as explicit state graphs, where each node represents an action or decision step and edges define the transitions between them. Unlike simpler chain-based approaches, it makes control flow visible and debuggable. You can inspect exactly what state the agent is in at any point and trace why it took a given path. It is designed for agents that need to loop, branch, or call themselves recursively, and has become the go-to framework for production agent orchestration as of 2026.
In practice, a LangGraph agent handling customer queries can be modelled as a graph with nodes for intent classification, tool retrieval, and response generation, making it straightforward to add a new branch for escalation without touching unrelated logic.
Related terms: model-context-protocol (a standard for the tool connections LangGraph agents often rely on), retrieval-augmented-generation (a common node-level pattern within LangGraph workflows).