Decagon has defined early stage enterprise success. Perry Ha and his team are the unsung heroes behind that motion.
Perry is a former founder who has built their forward deployed motion. He's created their Agent Product Manager program, and those APMs are responsible for the tremendous success they are having with customers like Chime, Duolingo, Eventbrite, and Samsara.
I loved sitting down with him to talk through the initial build, optimal team structure, how to hire for this role, and what he wishes he knew when he started out.
Please enjoy this candid conversation with my good friend Perry Ha!
@DecagonAI
Speech-to-speech models sound amazing in theory…until they’re deployed at enterprise scale.
It’s easy to see why people are excited. By skipping the separate speech-to-text and text-to-speech models, S2S models deliver exciting demos that capture tone, emotion, and nuance in with minimal latency.
S2S models may be an incredible technical achievement, but they’re still difficult to control in production and harder to guarantee that workflows are executed precisely.
Many of the S2S voice demos optimize for speed and naturalness, not for correctness or safety. In real-world deployments, those tradeoffs erode trust fast.
For our voice agents, we’ve kept the structured pipeline but re-engineered it for speed. We made a ton of model and infrastructure optimizations to deliver faster, more natural-sounding speech. The result is a 65% improvement in speed while maintaining the auditability and precision enterprises depend on.
Speech-to-speech will get there eventually. But today, precision and reliability are what make voice AI work at enterprise scale.
What does it really take to make AI work in the enterprise?
Our Co-founder and CEO @thejessezhang took the @OpenAI DevDay main stage with @kimberlywtan and @vxanand to discuss.
Full recording below. ↓