An enterprise wants a multi-agent customer operations system where a central planner assigns work to billing, shipping, and returns specialists, enforces shared policies, and consolidates a single customer-facing answer. Specialists should not negotiate job assignment among themselves. Which logical orchestration pattern best matches this requirement?
Select an answer to reveal the explanation.
Short Explanation
The correct answer is A. You want a central planner assigning work, enforcing policy, and merging one answer—that is hub-and-spoke / orchestrator-subagent, not a peer swarm electing owners. A monolith throws away specialist decomposition. Human-only abandons the multi-agent goal.
Full Explanation
Option A is correct. Architecting multi-agent solutions includes choosing workflows and patterns such as hub-and-spoke and orchestrator-subagent when centralized assignment, policy enforcement, and answer consolidation are required and specialists should not self-organize work.
Option B is incorrect because peer-to-peer negotiation conflicts with the requirement that specialists do not assign work among themselves and complicates consistent policy enforcement.
Option C is incorrect because a monolith forgoes the specialist decomposition the enterprise needs for billing, shipping, and returns expertise.
Option D is incorrect because removing AI agents fails the stated multi-agent product goal.