agent-designer

Multi-agent architecture patterns include Single Agent, Supervisor, Swarm, Hierarchical, and Pipeline models. These patterns provide structured approaches for agent role specification, communication protocols, and orchestration to build scalable multi-agent systems across prototypes and production environments.

Design agent roles using a Role Definition Framework that specifies Coordinator, Specialist, Interface, and Monitor functions. Communication protocols are established alongside these roles to ensure structured interaction, safety guardrails, and orchestration across the multi-agent architecture.

Use a supervisor pattern for hierarchical task delegation with centralized control, or a swarm pattern for decentralized, self-organizing agent coordination. Pattern selection depends on scalability needs, task complexity, and the required level of safety guardrails and evaluation planning.

Yes, these multi-agent design principles apply to software engineers, researchers, and product teams building scalable AI agent ecosystems. The architecture patterns, role definitions, and guardrails support both rapid prototyping research experiments and robust production deployments.

Implement safety guardrails through validation rules, logging, and auditability mechanisms integrated into the multi-agent architecture. Evaluation planning ensures monitoring and performance assessment across agent roles, communication protocols, and orchestration patterns during execution.

Provide an initial task description to generate a baseline agent architecture and starter implementation plan. This quick start approach applies architecture pattern selection, agent role specification, and tool design principles to establish the multi-agent system foundation.