Prompt optimization can significantly improve multi-agent systems, but gains vary dramatically depending on task complexity, team structure, and communication patterns—there's no one-size-fits-all approach.
This paper studies how to optimize system prompts for multi-agent LLM systems—where multiple AI agents work together with different roles and communication patterns. The researchers test prompt optimization techniques across different team sizes, workflows, and tasks to understand when and how much these optimizations actually improve performance.