Current large language models powering voice interfaces rely on relatively basic architectures, and they're often programmed with artificial quirks—like strategic pauses and filler words ("um")—designed to mimic natural human conversation. This approach underutilizes what voice technology can actually deliver for agent-based workflows.

When it comes to serious professional applications, a streamlined voice mode makes sense. One built for efficiency rather than small talk. Something that cuts through the mimicry and focuses on precision communication with AI agents would unlock real productivity gains in automated task management and system coordination.