voice-agents
3 free lessons tagged voice-agents across AI. Each one is a short sequence of focused steps with narration and a five-question quiz at the end — take them in any order, no signup required.
Building Voice Agents: Latency, Tools, and What Breaks
Turning a voice AI prototype into a real product means facing hard choices. Learn the two competing architectures (the debuggable cascaded pipeline versus end-to-end speech-to-speech models), how function calling lets an agent actually do things, why cost and observability drive real decisions, the failure modes that break voice agents in production, and how to evaluate whether one actually works.
Turn-Taking and Interruptions: Why Voice AI Feels Human
The hardest part of a voice agent is not understanding words, it is the rhythm of conversation. Learn how agents detect when you have finished speaking (endpointing), handle being interrupted mid-sentence (barge-in), fill awkward silences, and why converting speech to text throws away the emotion in your voice. This orchestration is what separates a natural agent from a robotic demo.
How Voice AI Agents Work: STT, LLMs, and TTS
A voice AI agent that you can call and talk to like a person is really three systems working together: speech-to-text ears, a large language model brain, and text-to-speech voice. Learn how the STT-LLM-TTS pipeline works, why latency is the central challenge, and the streaming trick that makes a machine respond fast enough to feel like a real conversation.