What problem does it solve?
LangGraph Fundamentals teaches how to design, implement, and run stateful agent workflows so you can manage complex multi-step orchestration, conditional routing, parallel work, and state merging without brittle code or lost data.
Core Features & Use Cases
- StateGraph construction: Define state schemas, reducers, and compile-time validation to ensure safe state updates.
- Nodes & Edges: Implement nodes that return partial updates, use static and conditional edges, and combine updates with routing via Command.
- Parallelism & Fan-out: Use Send to spawn parallel workers and ReducedValue/reducers to safely accumulate results.
- Streaming & Error Handling: Stream values, updates, messages, or custom progress; apply retry policies and ToolNode patterns for recoverable errors and human-in-the-loop interrupts.
- Use Case: Build an LLM orchestrator that classifies input, fans out tasks to workers, aggregates results with reducers, and streams token-level progress to a chat UI.
Quick Start
Invoke the skill to design a StateGraph with explicit state schema, add nodes for each step, wire edges or conditional routing, compile the graph, and run it with graph.invoke to execute the workflow.
