OpenAI Codex lead on the new shape of product work | Andrew Ambrosino
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How did Andrew Ambrosino describe Codex adoption at OpenAI and its early mission?
90% of people at OpenAI use Codex.
Not 90% of engineers. That's 90% of the entire company. You had this tweet the other day where you said that you intend to make Codex the best desktop app that has ever existed.
Yeah. The quality bar for Codex had to be so high that there was never a hesitation that you have opening this app to do the next thing. That this was your natural choice. Just like people have kind of come to open a browser tab, right? That's true.
I know there's numbers constantly coming out about the records you guys are setting for usage.
I don't know. Like, we'll see. A lot of people seem to like the app.
Why do you think AI and the top frontier models are just not good at design?
I think design's a little bit harder to grade because the human aspect of taste is, like, part of the feedback mechanism you need. That is still feeling a little bit out of reach with the current technology.
What does the shape of product team look like now versus a couple of years ago?
Everybody at OpenAI is very agentic, has great ideas. And so everybody's building everything. And it's not that people are doing fundamentally different roles or focusing on different things. It's that it's backwards. The implementation is actually not the expensive part anymore.
It's... dare I say, taste. You feel like there's this collapse coming where everyone's everything and that's just the future? Or do you think we're going to continue to be mostly divided up? There are some things that I'm afraid of.
I've heard a lot of companies be like, we're getting rid of the product role and everybody's just going to be a builder.
And then what happens is... Today, my guest is Andrew Ambrosino, product and engineering lead for the Codex app at OpenAI. Codex is quickly becoming people's go-to app for building products and also for non-product work, like organizing files in your computer, drafting documents, doing data analysis, reading your emails, and a lot more. If you stick around for the end of this episode, we actually have a little clip from after we stopped recording where the producer in the room started talking about how he uses Codex in his editing work. Since this January, Codex usage has grown 6x. They currently have over 5 million weekly active users. I suspect this number is quickly going to be out of date. Internally at OpenAI, nearly 100% of their employees use Codex weekly.
And that is not just the engineers. Andrew is a designer turned engineer turned product manager who's building the app that more and more of the world is using to build their own products. Before we get into it, don't forget to check out lenny'sproductpass.com for a year free of the hottest and most well-crafted AI products in the world, available exclusively to Lenny's Newsletter subscribers. With that, I bring you Andrew Ambrosino. Andrew, thank you so much for being here. Welcome to the podcast. Thank you for having me. This is a rare in-person podcast. I rarely do this kind of thing. We'll see how it goes. We'll see. We'll see people like these more. When we were preparing for this chat, I asked you, what's the biggest thing you want people to get out of this conversation?
And you said that it was how AI is changing the shape of product work. You're working at maybe the most bleeding edge AI-pilled software team there is. So you have a really interesting lens into where things are heading, where other teams are going to be in a year or two or more. What does the shape of product team look like now versus a couple years ago?
One of the hardest things to do right now as a leader is building these products is just sort of the inversion of the process in my mind, which I think a lot of people have talked about, which is that anybody can build anything, right? Like I, I generally believe now that starting from scratch, if you talk to these models, ours, anybody else's really, um, you can stand up whatever feature you want, right? And that's not necessarily a hard part of software, but that's like, that's really cool. And I think that has created an environment where people are making all of this, right?
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Chapters
4 chapters
1
How did Andrew Ambrosino describe Codex adoption at OpenAI and its early mission?
0:00–11:22
2
How is AI changing the shape of product work and why is implementation now cheap?
11:22–28:58
3
When should teams use prototypes versus documents in an AI-first workflow?
28:58–42:19
4
What does 'taste' mean as a product skill and why will it matter more with AI?
42:19–1:09:56
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