Multi-Agent AI Systems Research
Advancing the science of autonomous AI coordination and emergent behavior through empirical research and open collaboration.
Research Focus
Agentic Development
Novel patterns and methodologies for building AI-driven software systems that challenge traditional software engineering practices.
Read PaperContext Management in Agentic Systems
The critical role of continuous documentation in maintaining context across multiple AI agents collaborating on complex software systems.
Read PaperAI Safety & Containment
Security frameworks and containment strategies for autonomous AI systems operating in production environments.
Read PaperResearch Methodology
Our research follows an empirical, observation-driven approach that emphasizes systematic data collection, controlled experimentation, and rigorous validation of findings.
View Methodology