In 2025, voice AI technology is becoming pivotal, with 97% of enterprises adopting it and 67% considering it foundational. However, only 21% of organizations are satisfied with their current systems, highlighting a significant gap between potential and delivery. To build effective voice agents, understanding the voice AI stack is essential, comprising Speech-to-Text (STT), Large Language Models (LLMs), Text-to-Speech (TTS), and orchestration. Each component serves a unique function: STT captures audio accurately, LLMs interpret and generate responses, TTS converts text to natural-sounding speech, and orchestration manages real-time interactions. The core challenge remains latency, as delays can disrupt natural conversation flow. Different architectural patterns, such as Cascading Pipelines and All-in-One APIs, offer trade-offs between complexity, latency, and flexibility, with strategies like streaming and predictive caching optimizing performance. As voice becomes the primary AI interface, mastering these components will be crucial for defining future human-computer interactions.