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Introduction to Multi-Agent Systems

Introduction

While a single agent is powerful, giving one LLM too many tools and a complex goal often leads to confusion and failure. The solution is Multi-Agent Systems.

Specialization and Collaboration

Just like a human company is divided into specialized roles (Researcher, Writer, Quality Assurance), a Multi-Agent System breaks down a massive task and assigns different parts to distinct AI agents. Each agent has a specific persona, a narrow set of tools, and a clear goal. They collaborate, pass data between each other, and review each other's work.

Assignment

  1. Read case studies on platforms like AutoGen or ChatDev to see how teams of AI agents can build entire software applications from scratch.

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