A multi-agent system is an architecture where multiple AI agents work together, each handling different aspects of a workflow. Agents can specialize in specific tasks — one for frontend code, another for backend logic, another for testing — collaborating to accomplish goals that would overwhelm a single agent.
Multi-agent systems are the natural evolution of AI-assisted development. One agent is useful. A coordinated team of agents is transformative.
Single agents hit limits:
User Request → Router → Specialized Agents → Coordinated Output
↓
Frontend Agent → UI components
Backend Agent → API + database
Testing Agent → Tests + validation
| Pattern | Description | Best For |
|---|---|---|
| Specialist | Each agent owns a domain | Large projects |
| Pipeline | Agents work in sequence | Multi-step tasks |
| Collaborative | Agents review each other's work | Quality-critical code |
| Hierarchical | Manager agent coordinates workers | Complex workflows |
More agents mean more coordination overhead. The sweet spot depends on your project's complexity — most vibe coders benefit from 2-4 specialized agents rather than a swarm.