langgraph-architect

LangGraph Architect provides six core graph patterns—Prompt Chaining, Parallelization, Routing, Orchestrator-Worker, Evaluator-Optimizer, and Agent—with guidance on when to apply each. Start with the core concepts pages, then implement a simple three-node graph using Prompt Chaining to understand how state flows across nodes.

LangGraph Architect covers memory strategy through checkpointer and store patterns. The Skill provides implementation guidance for graph structure and memory management to ensure state persistence across agent executions in production systems.

Tool integration patterns in LangGraph Architect show how to connect external tools within your graph nodes. The Skill includes practical implementation guidance and templates for adding tool-calling capabilities to agent patterns.

Yes. LangGraph Architect supports subgraph patterns for modular architectures and multi-agent collaboration. Subgraphs enable reusable components and cleaner separation of concerns in complex agent systems.

LangGraph Architect includes practical RAG implementation patterns alongside its core graph architectures. It provides templates and best practices for building retrieval-augmented generation into agent workflows.

Explicit control flow and type safety prevent silent failures and make agent behavior predictable at scale. LangGraph Architect satisfies these requirements through structured graph patterns and templates designed for production-ready systems.