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Multi-agent system

As explained in The Art of AI Product Development

A multi-agent system is an AI system in which multiple agents perform specialized tasks and coordinate toward a shared goal.

A multi-agent system combines specialized agents that coordinate toward a shared goal. Instead of asking one agent to handle every domain, it assigns focused work—such as discovery, prioritization, or roadmap planning—to different agents and orchestrates their collaboration. section 9.4.1

Product-management supervisor

A product-management system can delegate customer discovery, opportunity prioritization, and roadmap planning to specialized agents. An overarching product-management agent supervises the subtasks and combines their contributions into a broader workflow. section 9.4.1

Figure 9.15 The “supervisor” pattern in agent collaboration: an overarching agent coordinates the execution of subtasks by specialized agents.
A diagram of a product management agent

AI-generated content may be incorrect.

The supervisor pattern shows how an overarching agent coordinates execution across specialized agents. section 9.4.1

Use the pattern when:

  • A workflow spans several domains and a single agent becomes mediocre at complex, multitask work. section 9.4.1
  • The product needs flexibility, scalability, communication, collaboration, and adaptation across changing business workflows. section 9.4.1
  • Teams can begin with manageable tasks, monitor gaps, and expand scope as confidence grows rather than attempting full autonomy immediately. section 9.4.3 section 9.5

How The Art of AI Product Development covers it

How deep it goes
Explains specialization, orchestration, communication, and supervision, but stops short of implementation details.
Examples
Uses product discovery, prioritization, roadmap planning, customer-feedback analysis, and future-scenario generation as collaborative tasks.
What you can do after
Operate/configure specialized agents incrementally, monitor gaps, and add human review when confidence is low or errors could be catastrophic.
How it connects
Connects multi-agent systems with agentic AI, single-agent systems, human-in-the-loop processes, and autonomous enterprises.

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This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.