Lesson 640 of 1596
Multi-Agent Coordination Patterns: Orchestration vs Choreography
Multi-agent systems can be orchestrated (central coordinator) or choreographed (peer-to-peer). The choice shapes failure modes, observability, and operational complexity.
Creators · Agentic AI · ~24 min read
The premise
Multi-agent systems require explicit coordination patterns; the choice between orchestration and choreography shapes long-term operational characteristics.
What AI does well here
- Choose orchestration for use cases needing strong observability and centralized control
- Choose choreography for use cases needing scale, fault tolerance, and loose coupling
- Implement explicit handoff protocols between agents (not implicit through shared state)
- Build observability that traces requests across multi-agent boundaries
What AI cannot do
- Get distributed-systems benefits without distributed-systems complexity
- Substitute for clear ownership of each agent's behavior
- Avoid the operational cost of coordination (always present in some form)
Key terms in this lesson
End-of-lesson quiz
Check what stuck
10 questions · Score saves to your progress.
Tutor
Curious about “Multi-Agent Coordination Patterns: Orchestration vs Choreography”?
Ask anything about this lesson. I’ll answer using just what you’re reading — short, friendly, grounded.
Progress saved locally in this browser. Sign in to sync across devices.
Related lessons
Keep going
Creators · 11 min
Multi-Tool Coordination: When Agents Use 20+ Tools
Production agents may have many tools. Tool coordination — selection, sequencing, recovery — is its own discipline.
Creators · 11 min
Agentic AI: Pick a Multi-Agent Pattern (Or Decide You Need One Agent)
Compare orchestrator-worker, peer-debate, and pipeline patterns and choose based on the failure mode you most want to avoid.
Builders · 40 min
Multiple AI Agents Working Together
Splitting one big task across specialized agents (planner, coder, reviewer) often beats one agent doing everything.
