Building LLM-Powered Multi-Agent Systems

Agentic Collaborative Patterns

Single-agent systems hit a ceiling. Multi-agent systems, where one agent specializes in planning and another in execution, can tackle tasks previously thought impossible for AI.

Core Patterns

• The Supervisor Pattern: A controller model dictates the strategy and critiques the outputs of the "worker" agents, ensuring alignment.
• The Feedback Loop: Agents should be able to review their own work or that of their peers, iteratively improving until the result meets a quality threshold.

Operationalizing Agents

Communication is the bottleneck. Use strict, schema-driven protocols for agent-to-agent communication to ensure that "Worker" agents never receive ambiguous instructions, keeping the system stable under load.