Descriptions:
Latent Space launches its Forward Deployed Engineering podcast with a panel recording featuring engineers and founders from Decagon, Vapi, Retell, Daily, and Smallest AI — all actively building production voice agent systems. The discussion is structured around the real tradeoffs practitioners face in 2026, starting with the dominant cascaded pipeline architecture: speech-to-text, LLM inference, then text-to-speech. Despite the theoretical appeal of end-to-end speech-to-speech models, the panel explains why these haven’t displaced the three-stage approach — primarily because speech-to-speech systems still trail on accuracy, interpretability, and reliability despite gains in naturalness.
The Smallest AI representative describes their Hydra speech-to-speech model and the architectural philosophy behind it: that truly human-like conversation requires asynchronous inference — forming responses while still listening — rather than the synchronous sequential pipeline most systems use today. The panel also covers latency-intelligence tradeoffs (more capable LLMs improve response quality but increase round-trip time), waterfall model routing for resilience when primary providers go down, and turn-taking as a deceptively hard engineering problem — distinguishing a thinking pause from a completed utterance. A real-world deployment for the World’s Fair is briefly discussed. For engineers evaluating or building conversational AI products, this episode provides a grounded, jargon-light map of where voice AI engineering actually stands.
📺 Source: Latent Space · Published August 25, 2026
🏷️ Format: Podcast
