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From Theory to Production
Multi-agent orchestration has moved from research to production. This playbook covers the 5 patterns proven reliable in real production environments.
Pattern 1: The Assembly Line
Agents arranged in linear sequence. Each receives input from the previous agent, processes it, and passes output to the next. Best for content pipelines and data processing. Implement checkpointing, validation agents at each stage, and timeouts per step.
Pattern 2: The Specialist Pool
A router agent dispatches tasks to the most appropriate specialist based on task type. Best for customer support and multi-domain operations. Build robust classification, implement fallback routing, and track specialist performance.
Pattern 3: The Review Board
Multiple agents independently produce outputs. A judge agent evaluates and selects the best. Best for high-stakes content and code generation. Define clear evaluation criteria, use at least 3 competing agents, and log all decisions.
Pattern 4: The Hierarchical Manager
A manager agent decomposes projects, delegates to workers, monitors progress, and synthesizes output. Best for complex multi-step projects. Give managers visibility into worker status, implement escalation, and set clear success criteria.
Pattern 5: The Self-Improving Loop
Agents produce output, receive feedback, and improve future outputs. Best for content optimization and personalization. Implement feedback collection, store feedback structurally, and run A/B tests.
Common Production Pitfalls
Cascading failures (build in isolation and retry logic), infinite loops (set maximum iteration limits), context loss (implement shared context stores), and cost explosion (use complexity classifiers).
Conclusion
These 5 patterns have been proven in production across content operations, customer support, DevOps, and business intelligence. Start with the pattern that matches your use case and iterate from there.