Single AI agents are powerful. Multiple agents working together can be transformative—or a complete disaster. The difference lies in the orchestration patterns you choose.

The Orchestration Challenge

Multi-agent systems introduce complexity that doesn't exist with single agents:

• How do agents communicate without creating tight coupling?
• What happens when one agent fails mid-workflow?
• How do you prevent agents from stepping on each other?
• How do you debug when things go wrong?

Pattern 1: Supervisor Architecture

One agent coordinates others. The supervisor receives requests, breaks them into subtasks, delegates to specialized agents, and synthesizes results. This works well when you have clear task hierarchies.

Pattern 2: Pipeline Orchestration

Agents are arranged in stages, each processing and passing results to the next. Works for linear workflows where each step has clear inputs and outputs.

Pattern 3: Event-Driven Coordination

Agents publish and subscribe to events. No central coordinator—agents react to events they care about. Best for loosely coupled systems where agents can work independently.

How Lumina Helps

Teals Lumina provides built-in support for these patterns through its orchestration engine. You define the coordination model declaratively, and the harness handles the mechanics—including failure handling, retry logic, and observability.