Building sophisticated applications often requires coordinating multiple AI agents, each with specialized capabilities. Claude-Flow provides a framework for this orchestration.

The Problem

Single-agent systems hit limitations when tasks require:

  • Different expertise domains
  • Parallel processing
  • Complex state management
  • Tool coordination

Claude-Flow Architecture

The orchestration layer manages agent lifecycles, message routing, and state persistence. Each agent operates independently but coordinates through a central message bus.

# Example agent definition
class CodeReviewAgent:
    def __init__(self):
        self.capabilities = ["code_analysis", "security_review"]
    
    async def process(self, task):
        # Agent-specific logic
        pass

Results

Using this pattern, I’ve built:

  • Genomic analysis pipelines
  • Enterprise security systems
  • Automated documentation generators

The key insight is that specialization beats generalization for complex workflows.