Designing Multi-Agent AI Systems That Actually Work

Architecture Patterns

1. Orchestrator-Worker

Best for: Clear task decomposition, parallel subtasks

Orchestrator (GPT-4o)
├── Researcher Agent (Perplexity/Tavily)
├── Writer Agent (Claude)
└── Editor Agent (GPT-4o-mini)

2. Peer-to-Peer (Debate)

Best for: High-stakes decisions requiring multiple perspectives Agents critique each other's outputs until consensus.

3. Hierarchical

Best for: Enterprise workflows with approvals CEO Agent → Manager Agents → Worker Agents

Communication Protocol

Use structured JSON handoffs between agents:

{
  "task_id": "uuid",
  "agent_from": "researcher",
  "agent_to": "writer",
  "context": {...},
  "output": {...},
  "confidence": 0.92
}

Failure Recovery

Always implement: retry with backoff, fallback agents, timeout circuits.