LangGraph Explained in 30 Seconds — When Chains Aren't Enough

LangChain made it easy to chain LLM calls. But chains are linear —
they can't loop, branch, retry, or remember.

LangGraph fixes that. You define your agent as a typed graph:
🧩 Nodes — pure functions over a shared state
🔗 Edges — static or conditional transitions
🧠 State — schema-validated, checkpointed, resumable

The 4 building blocks:
1️⃣ Define nodes (functions over typed state)
2️⃣ Wire edges (conditional routing supported)
3️⃣ Compile + checkpoint (every step persists)
4️⃣ Run, pause, resume (human-in-the-loop ready)

Real example: a research agent that searches → summarizes → critiques
its own answer → and loops back if there are gaps. The critic node
decides when the work is done.

This is how serious agents are built in 2026.

Видео LangGraph Explained in 30 Seconds — When Chains Aren't Enough канала The Dev Knight 데브 나이트