langgraph-fundamentals

To build stateful agent workflows with LangGraph, you need to design a StateGraph, implement state management schemas, create functional nodes, and define execution edges to control the flow.

Designing state management for a LangGraph application involves defining a clear state schema and selecting appropriate state update strategies to ensure data persists correctly across nodes.

You define the execution order in LangGraph by configuring edges between nodes, which dictates the precise sequence and routing logic of the stateful agent workflow.

Yes, LangChain is a required dependency to implement graph-based programming with LangGraph, as the framework relies on its underlying components for agent orchestration and stateful workflows.

LangGraph provides specific mechanisms for error handling during agent orchestration, allowing developers to manage exceptions and maintain workflow stability when executing complex state graphs.

You should use LangGraph for agent orchestration when you require fine-grained control over state management and cyclic execution flows, which standard sequential chains cannot easily handle.