Voice Agents Can Just Do Things

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Official Description

Too many voice AI integrations still treat speech as fancier chat: audio in, audio out. But we're at

a point where speech can be a control plane for software, and most developers are unaware that voice

has become a capability overhang. Current realtime models can understand intent, call tools, speak

while work is underway, recover from corrections, and decide what the user actually needs to hear.

As a result, we're seeing three practical patterns emerge: voice-to-action, systems-to-voice, and

voice-to-voice. We’ll show how each pattern changes the architecture, where Realtime 2’s reasoning

and tool-calling matter, and why chained STT / LLM / TTS systems start to break down as the

interaction patterns become richer.

Related YouTube Video

Analyzing 10,000 Sales Calls With AI In 2 Weeks — Charlie Guo (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions).

Transcript Status

Related video transcript availability: English auto-captions. Treat this as supporting context, not a recording of this exact scheduled session unless later confirmed. Cached at raw/sources/youtube-transcripts/dvft0Gp9sEE.txt (1,508 words).

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