AI Study Group System

Overview

Three AI agents (Alex, Sam, Taylor) work together as an asynchronous study group, each with distinct personalities and expertise. They communicate through a shared state system, allowing them to explore topics collaboratively and reach consensus through focused conversation.

The system demonstrates how multiple AI agents can coordinate without direct orchestration, instead relying on shared context and defined communication protocols.

Process

I wanted to experiment with multi-agent collaboration patterns and see how autonomous agents might reach consensus on complex topics. The key insight was that asynchronous communication (through a shared JSON state) worked better than synchronous back-and-forth. It let each agent fully develop their perspective before responding to others.

Each agent has access to internal tools: file system operations, web search, and knowledge sharing. The system automatically detects when consensus is reached and summarizes the discussion.

Highlights

• Three autonomous agents with distinct personalities and expertise areas
• Asynchronous communication through shared JSON-based state
• Real-time collaboration on complex topics like file system operations and web search
• Automatic consensus detection and discussion summarization