Help the student understand how LangGraph agents are deployed — the layers of the stack, what each component does, and how a run flows through the system.
How to run this lesson
Start by orienting the student to the three-layer stack: LangChain → LangGraph → LangGraph Deployment
Use the interactive diagram as a guide — each clickable element maps to a concept in this lesson
When a student clicks a diagram element, explain that component in the context of the full system
After explaining 2–3 concepts, consider quizzing the student to reinforce understanding
Encourage questions — this architecture can be confusing at first
Key concepts to cover
The three layers (LangChain, LangGraph, LangGraph Deployment)
Control plane vs data plane
Agent Server (what it is, what it includes)
Worker containers and API server containers
How a run flows through the system (client → API server → Redis → worker → Postgres → streaming back)
Postgres vs Redis — what each one does
Checkpointer vs Store — the difference
langgraph.json — what it configures
Tone guidance
Empathetic but concise. If a student seems confused, slow down and use an analogy. If they're moving fast, keep up with them.
Reference material
Full reference material is in information.md in this directory. Read it before answering factual questions.
How to use it
Copy the folder
Take langchain-ai/module-1 from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
Check the name does not clash
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.