What is a Multi-Agent System?

Rather than asking one large, generalist agent to plan, research, write, and verify everything itself, a multi-agent design splits the work: a planner agent decomposes the task, specialist agents (researcher, coder, reviewer) execute sub-tasks in their domain, and a coordinator or orchestrator agent merges results and resolves conflicts. This mirrors how a human team divides labor and often produces more reliable output than a single agent juggling every responsibility in one context window. Multi-agent systems introduce their own challenges: agents must share state without talking past each other, failures in one agent shouldn't silently corrupt downstream agents' work, and coordination overhead (message passing, waiting on dependencies) can add latency compared to a single-agent approach. Patterns like hierarchical delegation, blackboard architectures, and debate and critique loops, where one agent checks another's work, are common ways to structure the collaboration.