Multi-Agent AI Workflow Orchestrator

Complex business tasks often require multiple types of expertise working together: research, writing, code generation, data analysis, and decision-making. This workflow implements a multi-agent architecture in n8n: a coordinator agent breaks down a complex task into subtasks, routes each to a specialized sub-agent (researcher, writer, coder, analyst, reviewer), collects outputs, synthesizes them, and delivers a complete result. Each sub-agent has its own system prompt, tool access, and output format. The coordinator uses GPT-4o to reason about task decomposition and synthesis. A reference implementation with 4 agents is provided; additional agents and new task types can be added without rebuilding the architecture.

• Tackle tasks that exceed single-agent capability in quality and scope
• Specialist agents outperform generalist agents on their specific subtask
• Parallel execution of independent subtasks reduces total completion time
• Extensible architecture — add new specialist agents as new task types emerge
• Reference implementation accelerates custom multi-agent development