Multi-Agents

Welcome to the third tutorial in our AI Agents Learning section. In this tutorial you'll learn how to make agents work together — combining specialists and an orchestrator to tackle complex, multi-domain problems.

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What you'll build

A travel planning system with three agents:

• Logistics Agent — handles practical details (costs, times, routes)
• Recommendations Agent — suggests experiences (attractions, restaurants, activities)
• Orchestrator Agent — coordinates both specialists to create complete trip plans

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Why multi-agent systems?

A single agent can do a lot — but some problems are too complex for one agent alone. Multi-agent systems solve this by dividing responsibilities: specialist agents each handle a focused domain, while an orchestrator coordinates them and combines their outputs into a coherent answer.

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Key patterns you'll learn

• Parallel — multiple specialists called simultaneously for independent tasks
• Sequential — one specialist's output feeds the next, creating a pipeline
• Conditional — only relevant specialists are called, avoiding unnecessary work
• Hierarchical — sub-orchestrators manage their own groups of specialists

Prerequisites: Completed Tutorials 01 & 02 (AI Agents + Tools).