Building AI Voice Agents for Production

In a world moving toward natural interface experiences, voice-first applications are reshaping how we interact with technology. This text-based course guides you through the foundational concepts and engineering practices required to build reliable, production-ready conversational voice agents. You will start by understanding the core architecture of voice systems, from speech-to-text (STT) and large language model (LLM) orchestration to text-to-speech (TTS) synthesis. By following this structured material, you will transition from basic concepts to managing the real-world complexities of voice interfaces, such as latency reduction, state management, and interruption handling. What you'll learn: - Understand the core pipeline of modern AI voice agents, including STT, LLM processing, and TTS systems - Manage latency and optimize connection protocols such as WebSockets for real-time audio streaming - Design context-aware conversational flows that handle interruptions and background noise gracefully - Configure prompt engineering strategies specifically optimized for fast, conversational LLM responses - Implement basic testing and observability patterns to monitor agent performance and audio quality in production This course begins with essential terminology and structural overviews before guiding you through practical design patterns, system architecture decisions, and deployment considerations. You will read through detailed code examples and conceptual walkthroughs that prepare you to build robust systems. This course is designed for software developers, product builders, and technology enthusiasts who want to enter the field of conversational AI. No prior experience with voice technology is required, though a basic understanding of programming concepts will help you get the most out of the material. Start reading today to build the next generation of voice-enabled applications.