AI Multi-Agent Systems Tutorial: Roles + Handoffs

TL;DRMulti-agent systems split work across specialized agents that hand off to each other.

Instead of one agent doing everything, you compose several with distinct roles (researcher, coder, reviewer, planner) that collaborate — passing results, critiquing each other, or coordinated by an orchestrator. It can improve complex tasks via specialization and checks, but adds coordination overhead, cost, and new failure modes (agents looping, miscommunicating). Use it when a task genuinely decomposes into distinct roles.

Key points

Common mistakes

Try it: Design a 3-agent setup (roles + handoffs) for writing and reviewing code.

Example code

<!doctype html><html><head><meta charset="utf-8"></head>
<body style="background:#06040d;color:#e6e0ff;font-family:monospace;padding:20px"><pre>planner → coder → reviewer
each specialized, hands off results
gains: checks · costs: coordination</pre></body></html>
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Tool Use · Function Calling Memory · Short Term · Long Term · Episodic