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Most people who want to build a voice AI agent start in the wrong place. They pick an LLM, write a system prompt, and wonder why it breaks in production. A voice AI agent is an architecture, not a prompt. This guide covers all 6 components, the latency budget, common mistakes, and the build vs platform decision.
500 milliseconds separates a voice AI conversation that feels natural from one that feels broken. LLM latency is the biggest variable in that equation, and the most controllable. This guide covers where latency comes from and the 7 specific techniques that get production voice AI systems under 500ms.
Callers don't read transcripts. They listen. And within the first five seconds, they've already judged the voice they're hearing. This guide explains how TTS works in voice AI, what makes a voice sound human, and why voice quality is one of the highest-ROI improvements in any voice AI deployment.
Every voice AI agent starts with a problem: the caller is speaking and the system needs to understand what they said, accurately, in real time. That's the STT engine's job. This guide breaks down exactly how it works, what makes one engine better than another, and what you should measure in production.
Everyone wants to build or buy a voice AI agent. Far fewer people understand what's actually inside one. This guide breaks down all 7 components that every production voice AI agent needs, what each one does, why it matters, and what happens when it's weak or missing entirely.
Most people still picture a robotic phone menu when they hear "voice AI agent." That's not what this is. A real voice AI agent listens, understands, and actually resolves the call, no button presses, no transfers, no script. Here's exactly how it works, what's inside it, and where businesses are already running it at scale.
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