*A true story from last month: *
I was building an intelligent agent using LangGraph + MCP, and I asked Claude for the latest code to implement a Multi-Node Agent.
It gave me a clean-looking code. I copied it, ran it… Import error.
I went to GPT-4o. Different code, but still outdated imports.
Tried Gemini. Same problem.
I lost over 4 hours tweaking imports, updating StateGraph, digging through LangChain's changelog… until I hit complete frustration.
That's when I said: Enough.
I decided to do something completely different.
I started collecting only the modern code that actually works in 2026, tested it myself, fixed what was broken, and organized everything in one place.
The result?
🔥 Agentic AI Tutorial
A complete, up-to-date reference for building Agentic AI using the latest versions of LangChain + LangGraph + MCP.
Why I built this repo
- To end the daily struggle of "outdated/copied-pasted-broken code"
- To help you build powerful agents without wasting hours on debugging
- To give you one trusted, updated reference where everything actually runs
What's inside?
| Chapter | Content |
|---|---|
| 1 | LLM basics + Streaming + Advanced Prompts |
| 2 | LangChain LCEL + Tools + Chains |
| 3 | Advanced Memory + Full RAG (Chroma & FAISS) |
| 4 | Advanced LangGraph (ReAct, Router, Multi-Agent, Self-Refine, Human-in-the-Loop) |
| 5 | Complete MCP + FastMCP Server + Multi-Node Agent System (Router → Execution → Summary) |
Everything is available as Jupyter Notebooks + Python files, ready to run.
Works locally (Ollama) and cloud (GPT-4o, Gemini).
A question for you:
Are you already at Chapter 5, or still at the beginning?
Drop a comment below 👇
Top comments (0)