If you want to learn:
How do I build my first ElevenLabs agent workflow with routing capabilities?
What are the steps to create a multi-agent voice AI system for customer service?
How can I set up specialized subagents with different knowledge bases in ElevenLabs?
How do I configure LLM conditions to route conversations between voice agents?
What's the difference between using system prompts and override prompts in agent workflows?
How do I deploy a conversational AI agent with handoff functionality?
Then this lecture is for you!
In this hands-on lecture, you'll build a complete ElevenLabs agent workflow from scratch using the Agent Workflows editor. You'll start by creating custom knowledge bases containing product information and stock data, then configure a multi-agent system with three specialized voice AI agents: a main routing agent, a Product Support specialist, and a Stock Specialist. You'll learn how to override system prompts for precise agent behavior, assign different voice settings to each subagent, and attach specific knowledge bases to control what information each agent can access. The lecture demonstrates how to set up LLM conditions on workflow edges to enable intelligent routing based on user intent, allowing seamless conversation flow between agents without requiring users to repeat questions. You'll see a live deployment and testing session where the voice agent successfully handles both product inquiries and stock availability questions by automatically transferring to the appropriate specialist agent. This practical deep dive into ElevenLabs agent workflows provides the foundation for building conversational AI systems with complex routing logic, preparing you to create sophisticated voice agents for real-world customer service use cases.