Tutorial LangGraph: From Zero to Multi-Agent System in 21 Days
A structured 21-day tutorial to master LangGraph, a production-ready framework for building AI agents.
Why it matters
This tutorial provides a structured approach to mastering a production-ready framework for building advanced AI agents, which is valuable for developers and AI researchers.
Key Points
- 13-week structured tutorial covering fundamentals, intermediate concepts, and production-ready multi-agent systems
- 2LangGraph is chosen over other agent frameworks due to its robust state management, native multi-agent support, and debugging tools
- 3Project goal: Build a functional AI Research Assistant using LangGraph
Details
The article presents a 21-day tutorial to learn LangGraph, a framework for building AI agents. The tutorial is divided into 3 weeks: Week 1 covers fundamentals like graphs, state, and tools; Week 2 dives into intermediate topics like memory, errors, and reasoning; and Week 3 focuses on production-ready multi-agent systems and deployment. The goal is to build a functional AI Research Assistant by the end of the tutorial. LangGraph is chosen over other agent frameworks like AutoGPT, BabyAGI, and CrewAI due to its production-readiness, robust state management, native multi-agent support, excellent debugging tools, and adoption by large enterprises.
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