Building a single AI agent is relatively straightforward. Building a team of agents that collaborate effectively to complete enterprise workflows is an order of magnitude more complex.
In this technical deep dive, we explore the architecture patterns that make multi-agent orchestration work in production. We cover agent role definition, communication protocols, task decomposition strategies, error handling, and the orchestration layer that ties everything together.
The key insight is that multi-agent systems aren't just about having multiple models — they're about designing an organizational structure for AI, complete with roles, responsibilities, communication channels, and escalation paths.