When a user finishes a sentence in a voice conversation, they expect to hear the agent start replying within roughly a second. Anything longer feels broken. The fastest way to hit that target isn't a faster LLM—it's not waiting for the LLM to finish before you start speaking. Streaming the LLM response, sentence by sentence, into a TTS engine is the trick that turns a 4-second response time into a sub-second one. And once you're streaming, you can layer on tool calling for real-world actions and structured outputs for predictable downstream code—all without giving up that latency budget. This tutorial walks through how to build that pipeline using AssemblyAI's LLM Gateway and Universal-3 Pro Streaming.…