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SS Steven Sinofsky Steven Sinofsky Ran Microsoft's Windows division for years before leaving the company in 2012, and now serves as a board partner at the venture firm Andreessen Horowitz (a16z).

“There's been no user study ever that shows interacting with the computer using full natural language is efficient. It's literally always the least efficient way. Ask yourself: how many people are really good at asking questions? Immediately, that's less than half the people who can ask a good question in a meeting.”

a16z Podcast · Startups & Venture · September 2026

“There's been no user study ever that shows interacting with the computer using full natural language is efficient. It's literally always the least efficient way. Ask yourself: how many people are really good at asking questions? Immediately, that's less than half the people who can ask a good question in a meeting.” — Steven Sinofsky, a16z Podcast

Context

Sinofsky, who ran Windows at Microsoft, is enthusing about Vercel's Jev — a model that reads text but returns a choice from a set of options rather than generating prose, which makes it cheap to embed in ordinary software. His point is that chat was always the wrong default interface, and that what's coming back is probabilistic programming, which he notes was most of computer science before 1970.

Transcript

a16z Podcast Around 52:13 into the episode
Erik Torenberg

remarkable. Yeah.

Martin Casado

…And so for all of the use cases that are not talking to like a chat bot, but are actually trying to put it in traditional software, this is a great fit. And so this has probably been the fastest adoption of an AI model since ChatGPT. It's just been remarkable because we're all primed for this. I

Steven Sinofsky

just want to pile on this one because I. I can't tell you how much I love seeing this exact form of innovation. And because what it does is it does the thing that's bugged me from the very beginning, which is there's been no user study ever that shows like interacting with the computer using full natural language is efficient. It's like literally always the least efficient way. And it's very simple. And it's just like, ask yourself, how many people are asked, are really, really good at asking questions? And immediately that's like less than half the people can ask a good question in a meeting. And then how often do you look at the answer and get really frustrated before it's finished, but you have to pay all this money to watch the seven paragraphs come out and then apologize that it's only a little. And so that's one, like having a different model. And then the other, of course, is my favorite, which is the output of it is designed for probabilistic programming. And so instead of saying, like, is this a customer service question, then route to customer service, otherwise route to general help desk…

Martin Casado

Halper Flanks one. That was phenomenal, Thomas. But the

Steven Sinofsky

part that

Aaron Levie

I felt was missing was that like, oh, wait, this is not all new. Like all of computer science was this probabilistic stuff. And so it's going to be very interesting to dust off all of that work because it's exactly what's going on. Like it's not an if statement now is if X percent, not if always.…

Speaker names come from our own diarization. The position is estimated from where the line sits in the episode.

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