Lesson 2087 of 2116
AI Multi-Agent Orchestration Patterns: Supervisors, Swarms, and Pipelines
Design patterns for coordinating multiple AI agents on shared goals.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2supervisor pattern
- 3agent swarm
- 4pipeline
Concept cluster
Terms to connect while reading
Section 1
The premise
Multi-agent systems organize via supervisors (one delegator), swarms (peer messaging), or pipelines (fixed handoffs) — each pattern has distinct failure modes and observability needs.
What AI does well here
- Routing tasks to specialized sub-agents based on capability tags
- Aggregating sub-agent outputs into unified responses
- Detecting when a sub-agent has stalled and reassigning
- Maintaining role boundaries when given role descriptions
What AI cannot do
- Resolve genuine disagreement between two equally-confident sub-agents
- Prevent infinite delegation loops without architectural caps
Key terms in this lesson
End-of-lesson quiz
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