langgraph-pipeline

To build a LangGraph pipeline with intent routing, create a StateGraph, add nodes for specific tasks, configure edges for dynamic routing, compile it with a checkpointer, and invoke it with an initial state to execute the workflow.

Subagent orchestration in LangGraph workflows involves integrating modular agents into a pipeline to coordinate complex tasks, utilizing persistent state and checkpointing to enable resumable execution across multiple runs.

Yes, you can use the Send API for parallel processing in a LangGraph pipeline by applying reference-guided patterns that support advanced graph execution, alongside annotated reducers and subgraphs for complex workflows.

Checkpointing in multi-agent LangGraph pipelines works by integrating a checkpointer during graph compilation, saving the persistent state to allow execution to pause and resume across different runs without losing context.

You need annotated reducers to manage state in LangGraph subgraphs when combining multiple agent outputs, as they provide the reference-guided patterns necessary to merge data correctly within complex workflow structures.