Multi-agent systems can outperform single agents, but they also introduce complexity, cost, and risk. This session breaks down product-ready patterns for agent-to-agent collaboration, including role-based agents, planner-executor loops, routing, and memory strategies. From an AI Product Manager viewpoint, I share frameworks for making multi-agent systems dependable, including evaluation harnesses, guardrails, latency and cost management, and operating metrics that tie agent performance to business outcomes.