OpenAI Codex lead on the new shape of product work | Andrew Ambrosino

Andrew Ambrosino leads development of the Codex desktop app at OpenAI. Nearly 100% of OpenAI employees—not just engineers—now use Codex weekly. A lifelong builder with a background spanning engineering, design, product management, and founding companies, he is now responsible for turning the Codex desktop experience into what he calls “the best desktop app that has ever existed, full stop.” *In our in-depth conversation, we discuss:* 1. Why AI has completely flipped the product development process 2. What “taste” really means as a professional skill, and why it is emerging as the most valuable capability in an AI-first workplace 3. Why Andrew believes the Codex app would have failed if they launched it last November (vs. in February) 4. The “zone defense” model for how product managers at OpenAI operate when everyone can build anything 5. How roles are collapsed on Andrew’s team, and why eliminating the concept of roles entirely is a big mistake 6. How Andrew uses Codex to run his own workflows 7. The vision for a home base that coordinates work across ChatGPT, Codex, and the tools people already use. *Brought to you by:* WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more: https://workos.com/lenny Mercury—Radically different banking, now with Command: https://mercury.com/ *Episode transcript:* https://www.lennysnewsletter.com/p/openai-codex-lead-on-the-new-shape *Archive of all Lenny's Podcast transcripts:* https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0 *Where to find Andrew Ambrosino:* • X: https://x.com/ajambrosino • LinkedIn: https://www.linkedin.com/in/ajambrosino • Website: https://ambrosino.io *Where to find Lenny:* • Newsletter: https://www.lennysnewsletter.com • X: https://twitter.com/lennysan • LinkedIn: https://www.linkedin.com/in/lennyrachitsky/ *In this episode, we cover:* (00:00) Introduction to Andrew Ambrosino (02:30) How AI is changing the shape of product work (06:32) When to use documents vs. prototypes (10:25) What “taste” actually means (12:06) Why AI is still bad at design (16:18) Is the design process really dead? (21:35) What the design process looks like on the Codex team (23:41) Are product functions disappearing? (27:22) Team structure (30:12) IC vs. management (31:37) Planning roadmaps (35:16) Building features that don’t work yet (38:13) The ambition problem: when you’re too AGI-pilled (39:17) The latest frontier: loops and autonomous development (52:05) How Andrew uses Codex to automate his entire job (46:52) The power of computer use and browser automation (49:10) Will we run all our SaaS apps inside Codex? (52:05) The future vision for Codex (57:20) The videographer who built a Premiere Pro extension with Codex (59:30) Failure corner (1:01:50) Lightning round (1:07:03) BTS: How our producer uses Codex for editing *Referenced:* • Codex: chatgpt.com/codex • The Primal Mark: How the Beginning Shapes the End in the Development of Creative Ideas: https://www.gsb.stanford.edu/faculty-research/publications/primal-mark-how-beginning-shapes-end-development-creative-ideas • Linear: https://linear.app • “Taste” is not just taste in aesthetics: https://x.com/thenanyu/status/2067327619897446721 • Linear’s secret to building beloved B2B products | Nan Yu (Head of Product): https://www.lennysnewsletter.com/p/linears-secret-to-building-beloved-b2b-products-nan-yu • Paul Graham’s website: https://paulgraham.com • The design process is dead. Here’s what’s replacing it. | Jenny Wen (head of design at Claude): https://www.lennysnewsletter.com/p/the-design-process-is-dead • The case study factory: https://essays.uxdesign.cc/case-study-factory • Why humans are AI’s biggest bottleneck (and what’s coming in 2026) | Alexander Embiricos (OpenAI Codex Product Lead): https://www.lennysnewsletter.com/p/why-humans-are-ais-biggest-bottleneck • OpenClaw: https://openclaw.ai • OpenClaw: The complete guide to building, training, and living with your personal AI agent: https://www.lennysnewsletter.com/p/openclaw-the-complete-guide-to-building • From skeptic to true believer: How OpenClaw changed my life | Claire Vo: https://www.lennysnewsletter.com/p/how-openclaw-changed-my-life-claire-vo • The Codex feature that works while you sleep: https://www.lennysnewsletter.com/p/the-codex-feature-that-works-while • The AI paradox: More automation, more humans, more work | Dan Shipper: https://www.lennysnewsletter.com/p/the-ai-paradox-dan-shipper • Atlas: https://chatgpt.com/atlas • Anthropic: https://www.anthropic.com *Recommended books:* • The Gruffalo: https://www.amazon.com/Gruffalo-Julia-Donaldson/dp/0803730470 • The Big Orange Splot: https://www.amazon.com/Big-Orange-Splot-Manus-Pinkwater/dp/0590445103 _Production and marketing by https://penname.co/._ _For inquiries about sponsoring the podcast, email [email protected]._ Lenny may be an investor in the companies discussed.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  90% of people at OpenAI use Codex. Not 90% of engineers, that's 90% of the entire company.

• 0:06Lenny Rachitsky?

  You had this tweet the other day where you said that you intend to make Codex the best desktop app that has ever existed.

• 0:12Speaker 00

  Yeah, the quality bar for Codex had to be so high that there was never like 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?

• 0:24Lenny Rachitsky?

  That's true, I know. There's numbers constantly coming out about the records you guys are setting for usage.

• 0:28Speaker 00

  I don't know, like we'll see. A lot of people seem to like the app.

• 0:31Lenny Rachitsky?

  Why do you think AI and the top frontier models are just not good at design?

• 0:36Speaker 00

  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.

• 0:45Lenny Rachitsky?

  What does the shape of product team look like now versus a couple of years ago?

• 0:49Speaker 00

  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.

• 1:04Lenny Rachitsky?

  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?

• 1:11Speaker 00

  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...

• 1:22Lenny Rachitsky?

  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.

• 2:06Lenny Rachitsky?

  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 lennysproductpass.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.

• 2:33Lenny Rachitsky?

  Andrew, thank you so much for being here and welcome to the podcast.

• 2:37Speaker 00

  Thank you for having me.

• 2:38Lenny Rachitsky?

  This is a rare in-person podcast. I rarely do this kind of thing. We'll see how it goes.

• 2:42Speaker 00

  We'll see.

• 2:42Lenny Rachitsky?

  We'll see if 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 of years ago?

• 3:09Speaker 00

  One of the hardest things to do right now as a leader, 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 generally believe now that, starting from scratch, if you talk to these models, ours, anybody else's really,

• 3:35Speaker 00

  you can stand up whatever feature you want, right? And that's not necessarily the 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? You give people unlimited tokens. Everybody at OpenAI, OpenAI is very agentic, has great ideas, and so everybody is building everything. Whereas I think, you know, you look back at product process that we've all run for a long time and it's been a little bit. Opposite, right? It's been kind of research ideation. Maybe there was some prototyping, but it was, you know, even when we got past waterfall, it was still kind of flavored of like, the implementation is expensive.

• 4:20Speaker 00

  And so what you want to do is you want to de-risk all implementation upfront through documents, through research, through prototypes, because prototypes and designs are cheaper, was kind of the assumption there. And that's changed. That's like totally changed. And right now, I'm sure there are 90 different explorations for, there's this feature that we desperately need to do that I'm sure there are 90 different uncoordinated teams like implementing and trying, right?

• 4:50Speaker 00

  So I guess the short answer is like, it's backwards. And it's not that people are doing fundamentally different roles or focusing on different things, or that even skillsets have vanished or that roles have just disappeared. It's that it's backwards, right? The implementation is actually not the expensive part anymore. It's DRS a taste. But it's the curation process. It's like of those 90 attempts, like what's good about these? What should we fold into other aspects of this, right? How should we frame this? Should it be part of this other feature, right? How many segments should be in the toggle? You know, all of those things.

• 5:23Lenny Rachitsky?

  This episode is brought to you by our season's presenting sponsor, WorkOS. What do OpenAI, Anthropic, Cursor, Vercel, Repli, Sierra, Clay, and hundreds of other winning companies all have in common? They are all powered by WorkOS. If you're building a product for the enterprise, you've felt the pain of integrating single sign-on, SCIM, RBAC, audit logs, and other features required by large companies. WorkOS turns those deal blockers into drop-in APIs with a modern developer platform built specifically for B2B SaaS. Literally every startup that I'm an investor in that starts to expand up market ends up working with WorkOS. And that's because they are the best. Whether you are a seed-stage startup trying to land your first enterprise customer or a unicorn expanding globally,

• 6:08Lenny Rachitsky?

  WorkOS is the fastest path to becoming enterprise-ready and unblocking growth. It's essentially Stripe for enterprise features. Visit workos.com to get started or just hit up their Slack where they have actual engineers waiting to answer your questions. WorkOS allows you to build faster with delightful APIs, comprehensive docs, and a smooth developer experience. Go to workos.com to make your app enterprise-ready today. Taste such a buzzword. I want to come back to that. This idea of 90 prototypes, so interesting. So just to make sure I understand that. So there's an idea out there floating around OpenAI. What people used to do is write docs.

• 6:46Speaker 00

  Yeah.

• 6:46Lenny Rachitsky?

  Here's what we're going to build. Here's the feature. Here's the strategies, PRD. Today, what you're describing, which makes all the sense, is people just create a prototype. And what you're saying is people across the company have kind of similar ideas. And now, instead of a doc, they create their little prototype. And that leads to kind of 90 different things people can look at and maybe pick here's the direction we want to go down.

• 7:05Speaker 00

  Yeah.

• 7:05Lenny Rachitsky?

  Idea.

• 7:05Speaker 00

  There's a lot of this.

• 7:08Speaker 00

  And it's not just happening here. Like, you've seen many product leaders say PRDs are dead. Prototypes are in. And I actually don't believe this at all. I think that one of the interesting things that is happening right now is that because implementation has gotten so cheap across every medium, it's very tempting to jump straight to a prototype. Especially if you're not an engineer, right? Especially if you've never been able to write code or never been interested or never had the time. It's really tempting to say like, PRDs are dead. Let me just show you what I mean, right? What I've also noticed, though, is that for engineers, it's really tempting to write a lot of documents. A lot of documents that are not worth reading.

• 7:54Speaker 00

  And this is no shade on people writing documents. It's that if implementation is abundant, then it's really important to pick the right format for the point you're trying to make. If that point is product clarity around a vague area, then it might actually be a document. If what you're trying to do is get something in people's hands to try out and to stress test an interaction pattern, it's a prototype. But I think like, this is kind of the funny thing now, which is that like, it's really important to pick the medium.

• 8:28Lenny Rachitsky?

  There's this term that a podcast guest shared that I think about when you say this, which is, it's called the primal mark. When a designer or a painter or an artist just creates the first mark on a painting or a piece of art.

• 8:42Lenny Rachitsky?

  That mark is what you start to respond to. And so everything kind of trickles down from that first mark you make. And what I'm hearing you saying is sometimes the prototype is the wrong first thing to do, because then you're just responding to this prototype versus a different idea versus a bigger idea. So I love hearing this. So like, everyone's just like, okay, forget it. No more writing, no more docs, no more period ease. You're saying they're actually still useful for specific use cases.

• 9:03Speaker 00

  Yeah, I think too, there's this part of the previous world was that the medium implied it had baked in a lot of, a lot of signal around where in the process something was. Right? So if you're seeing something that feels like the app in production, that means that it's late in the process, that assumptions have been de-risked, that, you know, design has looked at this, that this is a good business goal. Right? And now those things are sort of divorced. Right? And the reason it was that way is because it was hard to get resources to build the thing until it was properly de-risked. And now that's like just out the window. Right? And so I think it's really important to start saying, look, we can have prototypes.

• 9:46Speaker 00

  We have documents. Is it, are we clear around what this is doing? Right? Because to your point, you do not want to over-anchor on this thing that was meant to be an exploration, but now it looks so production-ready that like, oh, visually it's ready for prod, but it's not actually the right model of, of where the research is going, or what users are asking for, or what's right for the business. Right? Not to overdo the taste thing, but it's like, it's once again, it's like, the taste to know, like what to work on, how to present that information, like how to achieve the goals, what medium to use is emerging as like the most important thing to do. And that's, that's, that's in every field.

• 10:26Lenny Rachitsky?

  What is taste when you talk about good taste? Is it, is it what you described deciding, here's the thing we're going to invest in? Is it also, once you have a thing, is this right? Is this the thing to ship? Talk about when you think about what is good taste? Good judgment? What is, what is that concretely? Because people hear this word, they're like, oh, I have good taste. I know it. What does it look like in practice?

• 10:46Speaker 00

  Yeah. Um, it's funny, there was a tweet, I'm too online. There was a tweet, I think it was yesterday, from the head of product at Linear. I might be getting that wrong, sorry to anybody. Who said, people overemphasize the aesthetic part of what taste means. And they used, um, Paul Graham's great, but they used him as an example, saying Paul Graham clearly has great taste. And wears cargo shorts, right? Like, you know, we gotta, we gotta like tease out what taste means a little bit. And, and there's a lot of nuance here. I think it's all of the above to, to what you mentioned. It's, it's the like, there is an aesthetic part to it. But there's also a, a systems thinking part of it, like, how does this fit in the system? There is a, where are we going and how, like, what?

• 11:31Speaker 00

  What theme is this part of? There's how to present this. A lot of it is wider context. And, you know, obviously there are parts of taste that are like, hey, this interaction animation doesn't fit. In the semantic meaning it's supposed to, right? Like, it's too snappy for what it's actually trying to convey. And that's incredibly important, and I focus probably too much on that. But there's, there's like the. The like, what should, what should this be? Like, if we can build anything, like, what's, what's the, what's the goal here? And how do we, how do we get there? That I think is like, actually the real taste question here.

• 12:06Lenny Rachitsky?

  When I, when I hear things like this, I always wonder, where will human brains continue to be valuable as AI becomes stronger? And better and doing, and doing more of, of the work? And it feels like taste is, is a part of it. Something I think about along these lines is just, AI is still very bad at actual design. Like, the output of AI is not great.

• 12:24Speaker 00

  Yeah.

• 12:24Lenny Rachitsky?

  Rarely is it like, this is it, they nailed it.

• 12:26Speaker 00

  Yep.

• 12:27Lenny Rachitsky?

  And it's always like, oh, this is Claude design, this is Codex design. Why do you think AI and the top frontier models are just not good at design today?

• 12:36Speaker 00

  Yeah.

• 12:36Lenny Rachitsky?

  And do you think they'll get there? Do you think we'll get to a place of like, holy moly, we're done?

• 12:40Speaker 00

  Yeah, I tend to think that there are some practical reasons why it's lagged and also some.

• 12:48Speaker 00

  Harder problems to crack. I'm not in our research work, like, I'm sure I'll get yelled at for saying this. I think design's a little bit harder to grade than than than software. And that, you know, creating a loop where you can train the model and like, what's good design and what's bad design is just a little bit more tedious and onerous than, you know, does the code compile? Does it, you know, do do what it's supposed to, right? It because the human aspect of taste is is like part of the feedback mechanism you need. I also think that the labs historically invest in making their models good at things that accelerates AI research. And that in the era, the early era of coding models is very clear that the model being able to write correct code

• 13:32Speaker 00

  would accelerate research, right? In a way that you can't really make the same case for design. Not that getting good at design isn't important, it's that it's not directly in that that flywheel, right?

• 13:46Speaker 00

  Those are practical reasons and I, you know, those will go away, like, these models will get pretty good at design. There are some kind of murkier things that is is going to be really tough. Like, I have kind of a short list of them. One is, there is an aspect of of culture to what is considered good design. In that, you remember, it was probably what, last year, where like, every new website that came out was just a copy of Linear's website, right? Like Linear's website, great design, great taste. Like, if a model did that, I'd be like, wow, this is incredible leaps here, right? If I have a model that outputs Linear's website every time, that's not the challenge here, right?

• 14:29Speaker 00

  There's an amount of like, novelty that is more important in design than it actually is in software engineering. Like, software engineering, you almost you must want it to overindex unknown patterns, right? Whereas design, it's like, no, there's an element of randomness here and and novelty, right? There's also the, you know, to me, like, I I spent a lot of time writing code or, you know, supervising code on the early Codex out. And even as the models get good at design, there's sort of a an abstraction layer that is an interplay between the software design and the code that's being written. Like, this thing over here in this corner should share X, Y, and Z in the codebase with this thing down here, right?

• 15:14Speaker 00

  And that's a little bit different than saying the model needs to be a better designer, especially on the like, you know, that's not visual, that is visual design, but it is significantly deeper. It's about the abstractions in that like, oh, if tomorrow our company did a rebrand, the shallow version of this is that we have to, you know, update 263 components one by one. The deep version is like the semantics between these two things that look different. Like they're both in list, they have the like this style that convey this interaction pattern to the user. And I think like that is still feeling a little bit out of reach with the current technology. Right? That abstraction layer. So I think, you know, as, as we've gone through this process, right?

• 15:58Speaker 00

  Of, you know, we started the Codex app in November and we weren't using it full time. Now we use it for everything. That's been a journey, but now it's like the things that we actually do while using it are different things. So what was the question?

• 16:16Lenny Rachitsky?

  And that was, that was an amazing answer. Speaking of design and being creative, the Codex app, when it came out, it's like such a new thing.

• 16:23Speaker 00

  Yeah.

• 16:24Lenny Rachitsky?

  That nobody has had seen before. It's like not a terminal thing. It's not an ID thing. It's like this chat thing that codes and you could see code.

• 16:31Speaker 00

  Yeah.

• 16:32Lenny Rachitsky?

  To your point, it feels like it'd be hard for AI to be like, here's a whole new paradigm for how to code. And that feels like where human brains continue to be valuable for now is like creativity almost. And coming up with something new versus like a patterns of things that have been done before.

• 16:47Speaker 00

  Yeah, I mean, I totally agree. Let's give it up for the human brain.

• 16:50Lenny Rachitsky?

  For now. As we were getting ready for this, you said that you were listening to the episode of Jenny, who is just head of design for Claude Code and cowork and such. And she had this whole kind of thesis that the design process is dead. There's no time for design. Things are moving too fast. Just build now and design is kind of steering things as things move along. You're implying you have kind of a different perspective on the design process.

• 17:13Speaker 00

  We probably agree on, on a lot of this, Jenny and I. I wasn't a fan of the design, like the design process proper. I agree with, with her take that it is, it is dead. And I genuinely was not a fan of this process before AI. Like I, I think.

• 17:28Lenny Rachitsky?

  You described the process real quick, just from people think about the design.

• 17:31Speaker 00

  Yeah, yeah. So I mean, I. When I ran a startup a number of years ago, we would do design hiring. And there was this sort of snarky article that came out about like the case study factory. And it was like mid syrup era stuff, right? And it was that designers are being taught about this process and valuing that above all else, above all outcomes even, right? And if something went through this process, that two things were true. One, it would be good and the process would guarantee quality and guarantee impact. And also that if something, the thing was good, if it went through that process, even if you don't like it and nobody uses it.

• 18:12Speaker 00

  And it's like, the process of user research and the divergence and the convergence, it's the right framework. It was always a little academic, but I think, I think this is really exposing some areas where it falls down, especially because of the speed of implementation. And like, once again, like that process is sort of predicated on the assumption that implementation is expensive and that you can really only afford to build once. And so you need to fully, like exhaustively go through the problem space and the solution space before implementing, right? And then like what kind of we saw with like, you know, Figma and Origami and all of these

• 18:56Speaker 00

  tools, that you can fast forward some of the insights by pulling interactive prototypes earlier into the process, right? That you can simulate production and like, you know, there ended up being sort of a meme about executives just being like, well, can we just do a prototype and then like expect it to, you know, work? But, but this thing was real, right? That this became part of the, the design process proper, right? We pulled prototyping into that. The problem now is that you can pull all of implementation into that.

• 19:28Speaker 00

  And there's a mismatch between, I think, a lot of assumptions. Again, like you see this fully polished prototype that looks like it's ready to go out the door. And enough people at a company see that and they're like, can we, can we release this now? But the appropriate, like, we're actually in the early design process stage and nobody's just saying that. Right? Like, this is, this is where we are with like a bunch of like multiplayer exploration. Right? You know, 90 people will have this idea. It'll look really polished, but it's like, no, this is actually, that, that's the design process now. Right? Tying the design process to mediums, media. Like, that's the scary part. It's that designers have more tools now to do this process with.

• 20:12Speaker 00

  Right? You can put stuff into the current product and you can A B test it. Or just, you know, use that as a prototype. Many companies right now have this idea of like a baby version of the product. Like baby cursor, you've seen this on Twitter, like we have baby codex, right? A dramatically simplified code base that approximates all of the interactions of the production app. And therefore is a lot quicker to vibe code over. Right? Cause you can be like, well, what if the sidebar worked like this? Or what if a pain came in and had like a group chat here? What if X, Y, Z, right? That's like a huge tool that's part of the design process. So to say the design process is dead, I feel like it's both true and false.

• 20:49Speaker 00

  Right? It's that if you are, if you are tied to the tools in the, like the, the exact, like data specifics of the process. Then yeah, it's dead. Like you're not gonna have a good time. But to throw the process out completely or throw like the overlay of the process, the like, hey, we're at this point in the process. Like that is still more important than ever.

• 21:11Lenny Rachitsky?

  It's, it's really interesting because you have a background in every function. If people look at your LinkedIn, it's like engineer, designer, product manager, founder. Now you oversee the desktop app and I think design is not under your perp. Is that right? Is there like a separate design team or are they under your?

• 21:25Speaker 00

  Depends on the week.

• 21:26Lenny Rachitsky?

  Okay.

• 21:27Speaker 00

  We worked very closely together, like we believe in while sitting together, being embedded. I, reporting line, I don't.

• 21:35Lenny Rachitsky?

  The shape, the shift weekly. What does the design process look like on, on the codex?

• 21:38Speaker 00

  Yeah, there's been a lot written about role collapse, existential role collapse. There are no roles anymore. We haven't seen that. We've, we have seen more role collapse in the codex org. Then I think other parts of the company and other parts of the economy. I think part of this is that. This was a technical product for engineers. And so our designers speak engineer, right? Our product managers speak technical language and write code. Alexander has a master's degree in computer science, which is I do not have a master's degree in computer science. Like, so we've seen a lot of role collapse. And, and I think that, you know, one of, one of the ways that we describe how the groups work together

• 22:23Speaker 00

  is that there's significantly more overlap in the roles than there used to be. And everybody's sort of defined less by the fence and the boundaries of where design stops and engineering starts, but more the average of where they're working. Right? So like, you know, if you average up all of the things that somebody on our design team does, there's plenty of code writing things. There's plenty of things that are product work. But on average, like, there are dots over here, right? If you draw, if you draw it out on a diagram. And this sort of speaks to the process too. Especially because the entirety of the Codex app has been informed by the dog fooding loop. There is a desire among all of us to try to do as much as possible in the app,

• 23:07Speaker 00

  even when it's not the best tool, so that it can become the best tool. And so a lot of design, we all work on by using the app and say, okay, what's broken about this? This is a whole thing we do, which is that we, we often don't improve our process so that we can make the product better to do it, which is a deeply uncomfortable place to be in. But, you know, week to week, it's changing.

• 23:30Lenny Rachitsky?

  I love this point so much that, like, what are you? It's your role is the average of what you spend your time on. If most of your work is PM work, then okay, you're a PM for now.

• 23:40Speaker 00

  Yeah.

• 23:40Lenny Rachitsky?

  If it's engineering, you're an engineer for now. I feel like, was OpenAI the first company to call people member of technical staff?

• 23:46Speaker 00

  No, I believe that this. This might have started with Xerox. First company I interned at, this company called Up There, did the same thing.

• 23:54Lenny Rachitsky?

  It's been around.

• 23:54Speaker 00

  But it's much more common now, but you know, it is kind of a tradition in research-focused companies.

• 24:01Lenny Rachitsky?

  Okay, got it. So it emerged from research, but I feel like it's such a, I don't know, sign of where things might be headed, this idea of, we're just going to call everyone member of technical staff, your function isn't set. You're not like in this bucket of the PM org, of the NGO org, of the design org. Do you feel like that's where we all head long-term? Do you feel like functions will continue to exist? Like, there's still the PM skill set and the NGO skill set and the design skill set?

• 24:26Speaker 00

  Yeah.

• 24:27Lenny Rachitsky?

  And people are, I'm a designer. Where do you think this is like, like people call it builder? Do 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 in the margins?

• 24:39Speaker 00

  There are some things that I'm afraid of. And I think that, you know, some companies

• 24:46Speaker 00

  like to be very extreme about getting on to the bandwagon of whatever people say is going to happen.

• 24:55Speaker 00

  And I think part of the danger in eliminating the concept of roles is that it can dangerously eliminate the idea that things are specialties with knowable best practices, right? I've heard a lot of companies be like, we're getting rid of the product role, which I think is, by the way, a terrible idea. And everybody's just going to be like a builder. And then what happens is they don't, like, this whole discipline of product that's been built up and has like real best practices, real things that have been tried and failed and like real processes, like that just gets abandoned because people are like, oh, I wrote some code, right? Like, that's not a great place to be in.

• 25:37Speaker 00

  I think that the boundary of like so-and-so, like this isn't your lane. I welcome that part going away, but.

• 25:47Speaker 00

  There's a balance here where it's like not everyone can work on everything. For one, both in terms of breadth and depth, right? Like this is why managers are not going to go away. Not everybody can work on everything. And also, like, every discipline has a skill component to it. Which I think a lot of engineers are guilty of not recognizing that like, well, engineering is a skill to it. It's writing code and like other roles are just people vibing. It's like, no, that's not how it works, right?

• 26:18Speaker 00

  Like, yes, you can use Excel, but you cannot work on the finance team, right? That is like that kind of stuff, right?

• 26:24Lenny Rachitsky?

  Yeah, I think there's also just like, do you want to be doing this work?

• 26:27Speaker 00

  Yeah.

• 26:27Lenny Rachitsky?

  Do I want to be?

• 26:27Speaker 00

  I think more of it's that actually now is like, it's easier to switch roles. It's easier to learn the best practices. It's easier to not tie your effectiveness in a role with the ability to use the exact tool. Right? It's more of like, can you get yourself into this mindset? Learn which things work and which don't, and then like focus on it, right? Like, I spent so long feeling like I should not be a software engineer because I didn't care about like, assembly language or memorizing TypeScript syntax. You know, and it's like, there have always been parts of these roles

• 27:09Speaker 00

  that are that sort of gatekeeping that are like, well, no, this like being good at this role is being good at this tool. And I think that's what's kind of starting to erode. I just don't, I think people take this, they hyperbolize all of this.

• 27:21Lenny Rachitsky?

  What does your team look like on the Codex team? How many engineers, designers, PMs? Well, it's kind of like the makeup of the team right now.

• 27:28Speaker 00

  Every time people ask me like, how many people are on the Codex team? Do you remember my answer to this? I'm like, it's somewhere between 10 and a few thousand. I mean, it's like a fake answer, but it's, it's real in that we do see this as the culmination of what everybody works on here. Like everything that goes into model research, everything that goes into how, you know, models are good at Kuua and browser use. Everything about how, you know, monopersonality, all of the product work around, you know, front end infrastructure, all of the user, like all of it is this product. At the same time, we are not accepting PRs daily from thousands and thousands of people on whatever they want. So we've got a team, double digits of engineers, probably half that on the design

• 28:11Speaker 00

  side, a few product people, although product here is kind of more of his own defense play. And I think one thing that is very common among everybody on the codex side or on the desktop side is agency and taste, right? A lot of former founders or people who were at larger companies doing founder-shaped things, a lot of people with them in taste. At OpenAI, we let teams get very large. So we haven't said, hey, there's no management, but like, the teams are quite large, right? It's mostly ICs. And I think that's good.

• 28:47Lenny Rachitsky?

  You use this term zone defense for product work?

• 28:50Speaker 00

  Yeah.

• 28:50Lenny Rachitsky?

  And that's really interesting. It kind of maps to the design kind of shift also, just like you're there to kind of manage and coordinate. Talk a little bit more about what that looks like. What does zone defense look like for a product person?

• 29:00Speaker 00

  Yeah, and I have had a lot of conversations with Alexander about this analogy, which is that like, if two product people are working too closely, that's often not a good signal. And that like, you kind of want, like, as a product org, you sort of want to do this like force directed activity, where you're like, where are the gaps? Especially in this new world where curation and like, you know, steering and alignment is a lot of things where you're like, there's a ton of chaos happening on people throwing ideas all over the place, right? The whole like top-down, you know, year-long planning thing not going to work. And so now it's like, we need the tastemakers to guide things from inception to what the product should be. And that means you basically want company

• 29:45Speaker 00

  coverage. And so you spread out and you say, all right, who's like, who's best at what? Let's create some space between us so that we got full coverage, right? And that's kind of how it goes. And then you fill in the gaps and you're like, look, like, we want to hire engineers to a product minded. Like, we don't, we don't want it to be that, you know, we've got a bunch of people writing a bunch of code that needs like, full team reviewing it for like, product coherence, right? Like, we want everyone to have these skills. But I think like, what people go deep on has to change, right?

• 30:14Lenny Rachitsky?

  This is definitely a thread I've been noticing. Over and over with talking to folks like you is the the most valuable person right now. One of the most valuable, someone that could take an idea from idea to done with the taste to know this is great.

• 30:28Speaker 00

  Yeah.

• 30:28Lenny Rachitsky?

  Just like shepherding throughout this obsession with making it awesome. Like this kind of high agency, high taste person, exactly as you described. Is that is that kind of the way you think about here's who we're hiring here's who's going to do really well in this new world?

• 30:40Speaker 00

  Yeah, I think that that's that's the core piece right now. And it it also speaks to how I sort of see IC versus management, which is that it's not that management is going away. It's not that everyone's an IC, but like everyone's kind of both now, right? If you're an IC, you're not typing code out character by character, right? Like you are managing something, you're managing agents, you're managing, you know, like you're managing work that is happening, right? That comes together to do a certain thing. If you're a manager of teams, you're doing the same thing, just at a different, like different granularity, right?

• 31:20Speaker 00

  I generally look for like, obviously command over the discipline, but then the taste to say like, hey, you're gonna have unlimited tokens and I don't like, we can't just be doing slot. Like you need to be able to determine what signal, what's noise, like in a world of just infinite content.

• 31:38Lenny Rachitsky?

  Mentioned planning. At the pace things are moving, it's become very hard to plan roadmaps.

• 31:44Speaker 00

  Yeah.

• 31:44Lenny Rachitsky?

  I imagine especially in your world.

• 31:47Speaker 00

  People are very frustrated with me all the time on this.

• 31:49Lenny Rachitsky?

  Yes. Because things are just constantly shipping, things are changing, right? How do you plan on on your team? What's kind of like, how far ahead are you thinking? And what does a plan look like? Is it like spreadsheet? Is it MD file? What's kind of the output of a plan?

• 32:00Speaker 00

  Yeah, I don't think we do anything revolutionary on that. We're not clever about planning. I think like, the basic gist is the shorter term something is, the more detail it needs. And then it's not that we don't plan for nine months out. It's that that just has to stay very hazy. Because any amount of precision that you add to a nine month plan right now is false precision. And like, you're just gonna waste time. But you can say stuff, right? But like, nothing that we planned. I think research is different. So I'm not speaking for research here, but like on the applied side, when we do products like. Anything that you could have planned in November may have been true for December, but like, isn't what happened, right? So it's hard, like, it is really hard to do planning.

• 32:44Speaker 00

  We generally need to know, like, what do we think models are able to do on what timeline? And my last company, I kind of saw this shift where we were starting to use the models to drive features. And the product process fell down. It basically had to be like, let's list out all of the things that we think we are interested in doing for the next year or two. Let's prototype all of them, decide which things are ready now, and then just let the others sit and bake. And then every time there's like a new leap in models, let's try that thing again with it swapped out. Because like, the whole premise of whether features were good or not

• 33:26Speaker 00

  were based on whether they were smart enough, not the shape of them. So this is a great story about the Codex App. I, like, I am very confident that the Codex App that we released in February, if that had been ready in November, it would have absolutely failed in the market. And that the only difference was the models between November and February, right? And I, I think, like, there's a lot to that, that this product with the exact same shape, I think, would have, like, its, its outcomes were totally different depending on just a few months of timing.

• 34:04Lenny Rachitsky?

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• 34:46Lenny Rachitsky?

  I've been using command to transfer money around to figure out what categories I've been spending the most money in, analyze my cash flows. And just today, I used it to find out how much I've made from a specific sponsor over the past year. I just ask, how much have I made from X over the past year? 10 seconds later, I have an answer. It is so freaking cool. Visit mercury.com to learn more and apply online in minutes. Mercury is a fintech company, not an FDIC insured bank. Banking services provided through Choice Financial Group and Column NA, members FDIC. This is definitely a thread on this podcast is build things that are not yet working that will work when the model gets better. And there's this kind of other threat of ambition, be more ambitious with the things you take on.

• 35:31Lenny Rachitsky?

  So is this just like a way you approach things? It's just like, let's just build a bunch of things that may not work yet. We'll just have them around and wait for a model to catch up. Is that kind of the approach?

• 35:39Speaker 00

  Yeah, I think we have a lot of that. I think sometimes the challenge is like, you have to be very clear again about what stage of the design process that's in. People still have this muscle memory of like, oh, I wrote the code for this thing, therefore we should put it out there. It's like, no, no, that means you have an artifact now that we can test against for into future models, right? This happens with the in-app browser in the app that we have, right? Like, we had a kind of a working version. I mean, go back to Atlas, we had agent working inside of Atlas and, you know, that was pretty cool. We had operator before that in chat GPT, right? That didn't work out. Very cool idea, like, there's some thread that you can draw between operator, Alice, Codex, ChatGPT.

• 36:21Speaker 00

  That's like fundamentally the same feature, but the re-releasing of it with different intelligence totally changes the outcome here. And so I push people not to be stubborn about like, no, this isn't working, so it's a bad feature. It's like, no, it might not be ready yet. There's also this aspect of, especially in research, there's always a desire to be the most ambitious and to say, okay, but at the limit, the model can just do this and it just doesn't work on the product side. Like if you, if you go back to the original Codex release, basically what it was is it said it was Codex Web and it wasn't good for interacting with. It was like you give the model a task and it's going to go off,

• 37:04Speaker 00

  do the task, come back to you with it finished. Like, doesn't sound that radical. The problem is like it didn't do the task that well. Like it wrote code. It was, it was, it was good, but it was like that form factor was too early. And then the Claude code comes out, totally local, like not hooked up to the cloud. Doesn't pretend to be as, it's not as AGI pelt, right? It's like gonna ask you questions, it's gonna sit there. You can't just delegate your life to it. That worked way better, right? Cause that's the point that the models were out there, right? So we were like, we were too AGI pelt for the moment. And I think like, I, I think about that lesson a lot on this stuff. It used to be that, you know, failing market told you all these things about the shape of the product, about the communication of the product. And now it's like, no, you might need to release this thing

• 37:49Speaker 00

  six different times before it works. And that might like, the shape might not change at all.

• 37:55Lenny Rachitsky?

  There's like, it's so interesting to hear about all the variables you have to think about building product now. There's the timeline for the models and the research and how smart it gets. There's like people's ability to even understand this is how you could build software in the cloud and this is the future. Like get people prepared for this new future and then just what you can build as a team. And I love that Codex example because it comes back to this idea of ambition. And I want to hear if there's anything there for you of just this thread of just be more ambitious because these models can do so much more than you even imagine. And sometimes it's too ambitious for the market and they're not ready for it. But you think about that at all, just like pushing your team to be more ambitious because it's so much easier to just do things that maybe felt crazy hard in the fast.

• 38:34Speaker 00

  Yeah, this is a core challenge. Once, once there's a product that exists or a feature that exists, it's really easy for people to find paper cuts and

• 38:43Lenny Rachitsky?

  Micro-optimized.

• 38:44Speaker 00

  And they should. And people on Twitter like to remind us of this and I thank them for that. Like people should be focused on the features that exist and making them more reliable and better. But this, you know, this is why we also have a culture of bottoms up exploration here. Because sometimes, in the same way the Codex app came and disrupted ChatGPT in some way, right? This thing will get disrupted by a feature effort and that's, that's part of the design. Is that like, you can't always as one team be good at both the disruptive piece and the like maintaining a product and its quality piece. Some point in, you'd design a process that allows for both.

• 39:18Lenny Rachitsky?

  Kind of zooming out a little bit, if you think about the progression that we've been on of AI impacting how we build product. It's like insane how far we've come from, as you said, we used to write all our code by hand, like artisanally created human code, to AI writing a hundred percent of our code, to, you actually put it this way, that now like coding is steering the AI. And like, when you think about what percentage of my code is written by AI, it's almost like, how many times did I have to steer it in the right direction as the AI version of coding? And now that there's like agents and loops and all these things, what's kind of the latest frontier from what you've seen of how people are building?

• 39:59Lenny Rachitsky?

  Is it loops? Is there something else of just like the most AI-pilled, AI-forward teams? Here's how they operate now that people may not be aware.

• 40:07Speaker 00

  Yeah, I mean, loops are so last week, man. I mean, we talked about this. You know, one of the big questions is always, well, how much of the product is AI-written? And it's always hard to answer that question because if you're using the goalposts from last year, it's like, well, a hundred percent of our product right now is AI-written code. So the question is more like, well, okay, fine. Is the code written supervised versus unsupervised, right? And that's like a totally different thing. I welcome the moving of goalposts because that means we're making product progress. There have been a lot of explorations here around like autonomous, autonomously developed software.

• 40:46Speaker 00

  A lot of like harness engineering stuff, a lot of different explorations. I'm like, okay, well, what if you came in overnight and did garbage collection of the codebase to clean it up, right? One thing that I think all models suffer with right now is just, they usually increase complexity. If research is listening at any company, please make the models better at deleting code.

• 41:07Speaker 00

  But, you know, that becomes a problem right now when you try to put development completely on autopilot. And it's both on the, the human side and the codebase side. So like feature requests, right? You know, how do you teach a model which features to build, which ones to ignore, which ones to kind of like group together and reframe a little bit? How do you teach a model how to build the right abstractions, right? Like all of this is getting better. I don't think we're at a place yet where we're like. We're just gonna set up a loop that's like improve the app, you know, and listens to Twitter and listens to Slack and listens to email. I was like, we're not there yet, but we are, we are, we're trying to make it happen.

• 41:49Lenny Rachitsky?

  Do you think we'll get there? Do you think we'll get to a place where it's just like grow, like win?

• 41:54Speaker 00

  Slash goal, make money, like make me a billion dollars.

• 41:57Lenny Rachitsky?

  Win, win the market.

• 41:58Speaker 00

  I don't know, man. Like I, I am not in the business of saying never or always or whatever.

• 42:05Lenny Rachitsky?

  Yeah. How are you using AI in your work as product leader, engineer leader? There are some ways that you use it that maybe people may not be aware they can use AI for.

• 42:15Speaker 00

  Yeah, I, I think I have the best job in, in the world right now. Um, but one of the things that makes it very fun is that when we were developing the original Codex app, the goal for me personally was to make it the thing that I wrote the code with, right? I was like, I need to make this so good at development that I can build the Codex app with this. And the Codex app at that time was a development tool, right? And we did that like super quick dog fooding loop. Cause you've got your personal dog fooding loop where you're like, oh, like I can't do this thing. I should fix that so that I can do the thing. Now I can do the thing. Now I can do more things, right?

• 42:53Speaker 00

  You know, we released that. And then the next challenge was, hey, people are starting to do some different shaped things with this, right? And now I, you know, need to grow this. And so I need to hire a few people and help. So then like my role changed at the same time that the role of the app needed to change. So I'm like, okay, I need to do more product discovery here. I need to figure out the right loops for seeing what everybody's working on and steering things that are off track. And so all of a sudden, that's what I started using the Codex app for, right? I did still write code. It's like I've, I've tried to align my own usage of it with the problem that we're trying to solve. Right? And now I'm like, I need to build a spreadsheet that models this out. I need to kind of do it, you know, internal deep research on all of the efforts

• 43:36Speaker 00

  that have gone into this area of research for the next version of this. There was a release or a series of releases in May-ish that introduced the In-app browser. Computer use and artifact creation to the Codex app. That was, I think, our Codexes for almost everyone release. And everybody knows the term vibe coding. I think that was like our first vibe coordinated release. We're like, I had a, you know, Notion doc somewhere with everything that needed to happen. And I was like automating, like going out to gather updates from pull requests from Slack channels and like updating the status tracker. And like now this is pretty commonplace.

• 44:17Speaker 00

  But at the time, I felt like I was at the bleeding edge of like, how to manage a product release? In short, like the way that I use the Codex app is basically like, what? What has my job grown into? And how do I make this thing able to do everything I need to do? I will get up in the morning. I will see the daily brief that I have from like, everything from the 3,000 Slack channels that I'm in, like which things need my attention? I can kind of message back and be like, all right, give me five questions and I'll answer them. And I can do that.

• 44:49Lenny Rachitsky?

  How do you set that up? What's like the workflow to for somebody to set that up? Yeah, that sounds amazing.

• 44:53Speaker 00

  Again, I think we're still in the like discovery phase on a lot of this. And so right now it's like, I'm making automation that says, or scheduled task that says like, go through my Slack channels. These are the things that I care about and think are most important. You know, so I'm still kind of defining that. Like, these are things to watch out for, different categories. Like here's some context and, you know, I'll, you know, that'll get set up as a automated task. And then first few times it runs, it might need some steering. And luckily with this app, you know, I don't have to find out how to edit the instructions. I can just be like, hey, next time this runs, like, can you please worry about this instead? Or can you de-emphasize this work stream? Or hey, this thing happened and it didn't come up in a brief. Like, can you make sure that stuff in the shape?

• 45:38Speaker 00

  So I can kind of coach it along the way. It'll update the way that it notifies me, stuff like that.

• 45:44Lenny Rachitsky?

  Amazing.

• 45:44Speaker 00

  I think in the future that like, this is, this has been a core problem with the chatbot shape, right? Is that I know how to set this up. I have time to set this up because for me, it's product discovery to set it up. But if you're not working at OpenAI, not to belabor this, like, you don't want to have to figure out all this stuff. We need to like figure out that that shape of things.

• 46:06Lenny Rachitsky?

  Yeah, what I'm hearing is I don't think people realize that your app can act a lot like Open Claw.

• 46:12Speaker 00

  Yeah.

• 46:12Lenny Rachitsky?

  You was was people were so excited about like you just talk to it, set up this thing, check on this thing for me every day and then tell me what's going on like.

• 46:19Speaker 00

  Yeah.

• 46:20Lenny Rachitsky?

  Like it's starting to become a part of all these, all the products, uh, which is amazing. So the way if somebody would set this up is they just talk within the app and say, I want to set up an automation to do this. Look at my Slack and these are the things I met, I want to do.

• 46:31Speaker 00

  Yeah. Great. Yeah. And the app will say, you know.

• 46:34Lenny Rachitsky?

  Yeah.

• 46:35Speaker 00

  It'll set it up for you. If it doesn't have a Slack connector, it'll say, can I add the Slack connector? Yes or no? You can hit yes to that.

• 46:42Lenny Rachitsky?

  Yeah.

• 46:42Speaker 00

  Like the least that we can do is make it so that if you don't know how to do something in the app, they could just ask it.

• 46:49Lenny Rachitsky?

  Yeah.

• 46:49Speaker 00

  Right?

• 46:50Lenny Rachitsky?

  Yeah.

• 46:50Speaker 00

  I don't think that's enough, but I think that's the least we can do.

• 46:52Lenny Rachitsky?

  Yeah. A good example is I built this little app that filters spammy email for ManBox. So every email that comes in, and I built this in Codex, uh, every email that comes in, it looks at it and decides this is unsolicited, unsolicited kind of cold email-y stuff that I don't want to look at and labels it and puts it somewhere else. And to set that up, one of the steps was you have to go into like the Google Cloud Console and set up all these hub, sub, hub, API things and triggers. I don't know if you've ever used that interface. It's like so annoying and silly. So I was like, wait, what if I ask you to do it? And I was like, okay, cool. Do this for me. And it just, you described computer use. I've never actually seen this happen on my computer before.

• 47:29Speaker 00

  Yeah.

• 47:29Lenny Rachitsky?

  It just takes over my computer and starts going there.

• 47:32Speaker 00

  It's like, I don't care if you don't have a connector, man. I'll just start clicking.

• 47:35Lenny Rachitsky?

  Yeah. And it figures it out. It's crazy just to like watch it doing this thing.

• 47:39Speaker 00

  Designing the decision boundary between connectors, when to use the in-app browser versus your Chrome extension that's connected versus computer use.

• 47:48Lenny Rachitsky?

  Yeah.

• 47:48Speaker 00

  Was interesting and all done through just like feeling it out.

• 47:51Lenny Rachitsky?

  I saw a great Twitter thread the other day where they describe all these three and what you use it for.

• 47:56Speaker 00

  Yeah.

• 47:56Lenny Rachitsky?

  So this person described it really well.

• 47:58Speaker 00

  These personal workflows are really interesting because some of them.

• 48:04Speaker 00

  Really click like some of you know, people are trying all sorts of stuff. Everybody's making these personal systems. You ask everybody here what they do and everything's could be different. And then like certain themes arise and we're like, you know what? That should be a first, a first class experience on the app. Like, we should take this thing that everybody seems to be setting up and just make that work. And I think memory is sort of in the shape where we've had a lot of people and a lot of people at other companies too are like, well, I set up an obsidian base or a notion area and I tell it how to basically build my mind palace and how to put. It's like, eh, I don't know if everyone like, you shouldn't have to do that. Like, there should be a memory feature that does that for you, right? That's pretty generic. So that's, you know, that's one, but then there are other things like they're your process of your job.

• 48:49Speaker 00

  And there's something that like, yeah, you should set that up. But I think this is, we're constantly waiting through like, what's working for individual people? Like, what should, what should enter the product versus stay like, no, that's just how you do your job, right? What should become a primitive? What shouldn't?

• 49:05Lenny Rachitsky?

  Yeah.

• 49:06Speaker 00

  Yeah.

• 49:06Lenny Rachitsky?

  This is the, the taste in judgment you spoke of earlier, deciding these things. I want to talk about this browser use piece a little bit because I think people don't realize how powerful this is and what it could be used for. Reminds me, I don't know if you watched, uh, when Dan Shipper was on the podcast, he had this, uh, from every, he had this prediction that we're going to start using Codex to run our SaaS apps inside of.

• 49:28Speaker 00

  Yeah.

• 49:28Lenny Rachitsky?

  So instead of going in Chrome.

• 49:29Speaker 00

  I know he slacks me about this every day, asking for stuff.

• 49:33Lenny Rachitsky?

  Do you feel like this is where things go where we're just working within the Codex app using Notion and Linear and Salesforce inside with your agent kind of helping you along? Or do you think that's a kind of a different direction?

• 49:46Speaker 00

  It's been, yeah, it's been really interesting because obviously we've had a few attempts at browser shaped activity, right? And an operator and chat to the agent mode and Atlas. And now we have the in-app browser inside a desktop app. We also have the, the ability to install a Chrome extension where the app connects to Chrome, like. We've had a lot of shapes of this, and I think we've, we've learned a lot of different things. There's, there's a lot of play. There's a lot of really boring things at play, like, you know, we originally launched the app. It's an Electron app. The things that you can do within app browsers in there, it's, it's like kinda janky. So we have the, the in-app browser was for development. It was for testing your front end on development.

• 50:28Speaker 00

  And we were like, it's not really for anything else, guys. Like, it's, it's developer tool, right? And then we, we switched over to our Owl, Owl stack, which had powered the Atlas browser. And so now, you know, it multi-tab, and we've got enterprise security so that you can actually log into all your websites if you're, you know, so we've been iterating on this. I think the tough thing has always been, what should the shape of this browser be? Like, is this something that is only for the agent, right? That like, you've got Chrome, you open Chrome, you, you know, do your thing in Chrome. If you ask the desktop app, it opens up this browser that it can control really quickly. Doesn't have the latency of Play, right, whatever. But that, you know, or are we trying to say, this app is for everything? And like, we want you to use this as a browser. And those have a lot of trade-offs.

• 51:12Speaker 00

  It's not super, you know, well-traveled path, right? Like, most browsers are browsers at the top level. They've got browser tabs. This creates a lot of really boring, tedious problems, like keyboard shortcuts, right? Are we trying to do key mapping to VS Code or to Chrome? Or to our own thing, or to Linear, or like, you know, we wanna have some sort of muscle memory that carries over, but got all these things that have shape, like, sub-shapes of different products out on the market. What do we do?

• 51:42Lenny Rachitsky?

  And this just highlights how extra challenging this app is, where you have to allow it to work for somebody that's never built anything from like the more basic user to like power, like Peter, you know, open claw, trying to code with it.

• 51:57Speaker 00

  I, I'm not convinced I'm gonna get Peter to use the app. I think he might be the last.

• 52:02Lenny Rachitsky?

  Is it terminal?

• 52:03Speaker 00

  It's our real holdout.

• 52:03Lenny Rachitsky?

  Okay.

• 52:04Speaker 00

  But I'm gonna, I'm gonna keep trying.

• 52:06Lenny Rachitsky?

  Okay, let me, uh, let me zoom out for a moment and talk about kind of the big picture. If we're, you're taking all this. What's the, what's kind of the vision for, for Codex? Where does this go? What's it gonna look like, you know, I don't know, a year or two, 10 years?

• 52:18Speaker 00

  We had Codex as a CLI, right? And then we decided to build this app. And, you know, we were, we were a little uncertain about the app and, um, but had a lot of conviction in what it could be as to start a developer tool, right? That, you know, and it wasn't gonna be an IDE. It was gonna be this right sized surface where it was like sort of a chatbot, but it was more than that. And you could see the code, but we weren't gonna let you edit the code. There's a really interesting thing that happened at OpenAI in January and February. And it was before we actually released the Codex app, which is that we'd started to dog food the Codex app.

• 52:58Speaker 00

  And what we were finding, like, we were converging on some pretty clear internal PMF on engineering, right? And research workflows. They were thrilled. They were loving it. We were like, all right, we just gotta get the quality bar up before we release it to the world. We're convinced that this will be a thing. But then at the company, we spun up a few other workflows to say, hey, like, this Codex effort is on to something with these coding agents. And we have people from marketing, from comms, from finance, from legal, from basically every discipline who are using this Codex app, even though it is actively hostile to these people, right? It is like trying to show them code. It's trying to ask for approval to run RG on the, you know, it's like,

• 53:41Speaker 00

  it's doing all of these things that are actively not the right product surface for them. So why don't we take our other surfaces and add Codex to them? Like, let's add it to the ChatGPT desktop app. Let's add it to the Atlas browser, right? And let's essentially take the lessons of Codex and make it more general for a general knowledge work tool, right? And those efforts went for a little bit and the the most annoying problem happened, which is nobody would leave the Codex app for the apps that were allegedly for these other personas. And I think the lesson in all of this was just that like the whole developer tool versus general knowledge work tool, like there's a lot of nuance here that isn't

• 54:24Speaker 00

  just one or the other. And I think we really, we believe really strongly in this and that there are certainly, in the same way that we talk about the average of your role is like what your role is now, this is true on the product side, too. People who are doing Excel work don't want to see get repository information. We know that. But we also know that we can tell a lot from what they're doing about what kind of work they do. And we can start simple, grow the product complex as we feel is needed, right? Doesn't mean we don't have modes, right? You might want some modes for organizing your stuff and to sort of be like legible about the the ways that you enter the experience, right? But we really believe strongly that what we've built here is the right shape to take,

• 55:07Speaker 00

  take on like really deep vertically focused things, right? We work deeply with our finance team, with our team working on science, team working on legal, right? And and we say like, if we can build the right extensibility primitives and the right general model, then you can do anything with this, right? And then our challenge is, well, how do you, you know, how do you generalize it? But this is kind of going back to like the best desktop app that we can build, like what does that look like? And so, you know, was Codex the developer tool? Chat GPT, like, where's this going? This is how we think about it.

• 55:48Lenny Rachitsky?

  It is so interesting, the point you made that the Codex app was so, like, you did such a good job getting people to be aware it existed and so good to use and fun to use that everyone's starting to use that versus the Chat GPT app. So clearly the direction is combine them so that you're not creating this confusion, which I know is, you know, things people have been talking about, this idea of come bring them together.

• 56:06Speaker 00

  Somebody called it a super app and. Wish the head said that because now I have to hear about the super app all day, every day. We'll get past it.

• 56:13Lenny Rachitsky?

  Great. Okay, but is that is that kind of the not let's not call it a super app, but the idea is like one place people go to do all the things. Is that the general idea? Or TBD?

• 56:23Speaker 00

  Yeah, I think what we see here is that it's a great home base. It's a great place to keep track of all of the things that you have to do across different surfaces. And some of those things, you do all of it in the app. Some of those things, the app opens other apps to to do, right? The app can connect to Excel so that, you know, yes, it has a spreadsheet editor inside the app. Is that good enough for people doing financial modeling at OpenAI for raising billions of dollars? Like, probably not. And so the app talks directly to the add-in in Microsoft Excel on your desktop. When it's done, you can close Excel, right?

• 57:03Speaker 00

  And so it's not just about, hey, we're drawing a rectangle on the screen and everything needs to happen in that rectangle. It's this thing should be a home for you where you start work, you end work, you automate work and it uses whatever you need to do, right? There's a there's a great story about we had some videos that we shot in this room for the original launch of the Codex app. And our in-house DX videographer Brent then was tasked with editing all these videos, right? And he edited all the videos with Codex, which was one of the early like, whoa, what are people doing with this thing? Right? And the process for why he decided to start using Codex was really interesting.

• 57:46Speaker 00

  He started just because he was curious if Codex could edit videos. And so Codex is not a video editor per se, right? It doesn't have any of that UI in it. But it was able to understand that he used Premiere Pro. It could do some edits by editing the files that were backing what was on screen in Premiere Pro, but it couldn't do everything. So naturally, what Codex then did was built itself an extension that could be installed into Premiere Pro that it could then talk to and say, hey, Premiere Pro extension, can you please change this marker inside of the Premiere Pro app? That was pretty nuts when we saw that happening.

• 58:28Speaker 00

  It's a great model, right? There are these like specialty tools that specialize in things. And so we're trying to do two things at once with Codex and with now with ChatGPT. One is, how can we seamlessly interact with these tools that you're already using? And say like, we don't, we don't need to build a better video editor for you, right? But like Codex and ChatGPT can use that video editor, right? It can interact again, can hand stuff off to it, right? So how can we do that? And that's often through connectors or computer use or even extensions in this case, right? And then there is, you know, Dan Shepherd's thing, which is, hey, I have these web apps that you can click around and use, but I want to be able to open these in Codex and have Codex do extra stuff with it, right?

• 59:12Speaker 00

  And so there's a kind of like two models that are almost inverse of each other that we're doing a lot with both at the same time.

• 59:18Lenny Rachitsky?

  This premiere story is interesting to me because it's another example of just be more ambitious with these AI jobs. Like you may not, you may not know, maybe they could do this thing. It's almost just like, go try, go try, see if it figures it out. I'm gonna take us to a recurring corner on the podcast that I call fail corner. And so the question for you is, people see people like you just like killing it, just growing, everything's winning, Codex is doing so great, this crazy career, everything's up and to the right. People may not see the times that things didn't work out and things that you launched that were failures. And so these stories are really important for people to hear, that it's not all just win all the time. What's a story of a time you failed in your career that taught you something really important?

• 1:00:03Speaker 00

  It's funny to hear that description played back at me. And like, this is perhaps the first time I've, I've not felt like I was failing. I mean, I was a startup founder for a long time. I ended up selling the company for parts, essentially, right? And it was just, it was years, it was a slog, it was heavily regulated spaces, the whole thing felt like a constant failure.

• 1:00:28Speaker 00

  I went to this other startup and we were trying to do some AI tools and this also like pretty lockdown regulated industry. And that felt like just time after time of trying things and it not working. So to me, it's been like, oh, I've failed actually quite a lot. And, you know, sometimes it's just a point in time where things line up, like skillset, passion, point in the market line up. We, with this, you know, With this project to bring what we've learned with the Codex app and marry it with ChatGPT, there have been, I don't know how many micro failures on this where we're like, this is the shape it should look like, and then throw that in Slack and there's like a 2,000 message thread about how stupid we are.

• 1:01:12Speaker 00

  And it's like, this is the thing I love about opening eyes, people will just tell us that, right? There's, there's no, uh, there's no holding back on like when we fail with product things internally. It's why the external product has been pretty great is because it goes through these cycles of like

• 1:01:26Lenny Rachitsky?

  2,000, this sucks.

• 1:01:28Speaker 00

  I failed for like, I don't know, somewhere between 10 and 15 years before getting to this point. So I'm still surprised every day that things are going well. And I know it, I like, but.

• 1:01:38Lenny Rachitsky?

  I think this is really important for people to hear that you can have a lot of things not work out and then things start to work out super well. And let's just keep going and keep learning, I imagine is a lesson. Well, with that, we're, uh, we reached our very exciting lightning round. I've got five questions for you.

• 1:01:53Speaker 00

  Great.

• 1:01:54Lenny Rachitsky?

  Here we go. What are two or three books that you find yourself recommending most to other people?

• 1:01:59Speaker 00

  See, man, I'm a parent now. I'm a parent of young kids, so I, I'm like, I don't know, there's one called The Gruffalo. These are my kids.

• 1:02:07Lenny Rachitsky?

  Oh, my God, our kid just got obsessed with The Gruffalo.

• 1:02:10Speaker 00

  Yes.

• 1:02:11Lenny Rachitsky?

  We have like a bedtime chart.

• 1:02:12Speaker 00

  Yeah.

• 1:02:13Lenny Rachitsky?

  And now it's like pajamas, brushed teeth, books, gruffalo, uh, on blankie.

• 1:02:18Speaker 00

  Yeah.

• 1:02:18Lenny Rachitsky?

  Yeah, it's so good.

• 1:02:19Speaker 00

  So other books I'm reading right now are like that style. I'm like, actually, The Gruffalo is not a terrible one. I feel like there's some lessons.

• 1:02:26Lenny Rachitsky?

  So sweet, yeah. Although every kid's book is about death, like someone's eating someone, someone's killing. There's always like bad, like murder.

• 1:02:34Speaker 00

  Yeah.

• 1:02:34Lenny Rachitsky?

  And destruction.

• 1:02:35Speaker 00

  Kids like violence, they don't want it to feel like violence to them, like the words that they're just like.

• 1:02:40Lenny Rachitsky?

  It creates like an arc and excitement.

• 1:02:42Speaker 00

  Yeah.

• 1:02:42Lenny Rachitsky?

  Yeah, okay, great choice, Gruffalo.

• 1:02:44Speaker 00

  I currently have a book backlog. I, I need like, I need to read all of them.

• 1:02:49Lenny Rachitsky?

  Any other children's books then that your kid likes?

• 1:02:51Speaker 00

  Okay, so yes, actually, um, I am well versed on children's books. My favorite children's book ever is a very old one and it's called The Big Orange Spot or some, something along those lines. Look it up. It's great. Go get it. If you hate HOAs, go get it. It's about this guy, Mr. Plumbeen, who lives on a street where all the houses are the same. It's a very neat street. And then one day, a bird drops a large can of orange, orange paint on his house. And he says, F, F it. Like, I'm going all in. So he goes to the store, he gets paint, hammocks, alligators, and he's like, totally redoes his house. And the neighbors, like, they're up in arms, right? Like, you know, HOA, property value, whatever,

• 1:03:33Speaker 00

  whatever. It's not about HOAs, but I'm a very anti-HOA person. It's just really cool. And then like, one by one, the neighbors go talk to him, have what they refer to as lemonade, but like, it's a very convincing lemonade, because one by one, they all start redoing their house. Like, one guy does, like, a boat, right? I think, I think that's a good book. I think people need to read this when they're, especially, you know, nibbies.

• 1:03:54Lenny Rachitsky?

  When I hear from this is agency.

• 1:03:56Speaker 00

  Agents, exactly. You can just do things.

• 1:03:58Lenny Rachitsky?

  Just do things. Amazing. Okay, we'll keep going. Favorite recent movie or TV show you really enjoyed, if you have any time?

• 1:04:05Speaker 00

  So The Magic School Bus is back on Netflix. It's, it's a newly animated, it's got Kate McKinnon, because Miss Frizzle is now Professor Frizzle, and she's, you know, around, but she's not the main Frizzle now. Kate McKinnon plays the main Miss Frizzle. It's, yeah, I always liked The Magic School Bus. It's back.

• 1:04:21Lenny Rachitsky?

  I've never seen it first.

• 1:04:23Speaker 00

  Personally, like, I don't have time for movies. So what I do is watch hour-long Netflix things, back to back. You know that thing that people do?

• 1:04:33Lenny Rachitsky?

  Like, binge watch?

• 1:04:33Speaker 00

  Oh, I couldn't sit, I couldn't sit down and watch a whole movie, and then like, watch hour-long episodes and keep, yeah, I do. Some, there's something addicting about that.

• 1:04:41Lenny Rachitsky?

  Favorite product you've recently discovered that you really love?

• 1:04:44Speaker 00

  Well, that's a terrible answer. I feel like I'm discovering our product every day.

• 1:04:49Lenny Rachitsky?

  Beautiful. That's so.

• 1:04:50Speaker 00

  I think linear, linear does a great job. Like, linear, until, until this, linear was like, my favorite. At least software product.

• 1:04:59Lenny Rachitsky?

  Is that what you guys use to plan in?

• 1:05:01Speaker 00

  Well, in theory.

• 1:05:03Lenny Rachitsky?

  Do you have a favorite life motto that you find yourself coming back to in work or in life?

• 1:05:07Speaker 00

  I want to ask everyone who works with me this because I, I, I feel like I'm not a motto person. And then people tell me stuff I say all the time.

• 1:05:16Lenny Rachitsky?

  Yeah, like when we were chatting ahead of this, there's so many little nuggets that stood out to me that I've integrated into this chat. So I totally hear that. Okay, last question. You've been a PM, you've been a designer, you've been an engineer. Which is the toughest role of the three, which is like the hardest?

• 1:05:32Speaker 00

  Trying to start a war?

• 1:05:34Lenny Rachitsky?

  Yes.

• 1:05:35Speaker 00

  I don't know. I think they're all very different. And the things that make it tough for one person make it easy for others. There's a lot, there's so much, so many takes on this. And like this triad, what's going to happen with this triad? Like designers are done or like should designers code? Are PMs cooked? Like are engineers, do we not need engineers anymore because PMs are going to write all the code? Or a designer is going to PM now? And like, everybody's cooked and everybody's so back. And I don't know, like, there's some convergence. There's some fluidity that is being introduced that I think is refreshing and great.

• 1:06:16Speaker 00

  Especially for people with agency that want to be able to just like do the thing that needs to get done. And at the same time, like we talked about, there are some things that shouldn't go away. But I think people should find the stuff that's worth working on and go figure out what to do on those things.

• 1:06:32Lenny Rachitsky?

  That is a beautiful way to end it. Andrew, thank you so much for being here.

• 1:06:35Speaker 00

  Thank you.

• 1:06:36Lenny Rachitsky?

  Bye, everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennyspodcast.com. See you in the next episode.

• 1:07:01Speaker 02

  I love that thing about Brent in the premiere.

• 1:07:04Speaker 00

  Yeah.

• 1:07:04Speaker 02

  That's cool. I've actually used CodeX as well.

• 1:07:08Speaker 00

  There we go.

• 1:07:09Speaker 02

  Simple stuff like, oh, could you just cut this into the three breaks? You know, like if there's a pause in conversation, like the second, and Codex understands it.

• 1:07:19Speaker 00

  Basically, every job we feel like starts with a story like this, which is the product's not designed for it, but it's sort of a blank chatbot that can write code. So it can do everything, but like, what are the useful things for it to do?

• 1:07:34Speaker 02

  Right. I mean, people just have to have curiosity about the project. They have to, you know, have an intentional outcome and use Codex as the platform for that, just to see what happens, you know, because there's no risk at all.

• 1:07:48Speaker 00

  Right. Just a few tokens.

• 1:07:49Speaker 02

  A few tokens. But of course, if you're working for OpenAI, there's less risks on that regard.

• 1:07:55Speaker 00

  Yeah. You asked one of them, like, what, or a lot of them, actually, like, what skills are important? And it's like, then, then you've also had conversations about like the cracked new grad versus the, like, I don't know, if you're married to the exact process you have right now, like that, I don't know what advice to ever give, but if there's one piece, it's like, do not get married to your exact process. Get married to like the outcomes that you were uniquely able to deliver, and then do things like change your process to try things.

• 1:08:28Lenny Rachitsky?

  You just keep.

• 1:08:29Speaker 00

  Like, I'm the best at understanding Figma auto layout, like, what are you doing?

• 1:08:33Lenny Rachitsky?

  Right, because AI is going to be better at that also. You just keep spouting interesting things.

• 1:08:38Speaker 00

  Keep it in.

• 1:08:39Speaker 03

  It's crazy, the level of self-awareness that's required to be successful with AI.

• 1:08:45Speaker 00

  It is.

• 1:08:45Speaker 03

  Yeah.

• 1:08:46Speaker 00

  It's also why I'm nervous to ever say like, this is how something's going to be. Because I think about, like, my parents are open-minded people. They are into their careers, but just like, the stuff that works here is just not going to, it's not going to work with everybody. There's no nice way of saying that, you know? But like, the people who are here are self-selecting for. Like, oh, I'm somebody who just figures out the next thing to do. And that's just not, like, most of the population will not be an early adopter of things.

• 1:09:13Lenny Rachitsky?

  And there's also just like, it's kind of like a bummer to have to relearn things all the time.

• 1:09:17Speaker 00

  Yeah.

• 1:09:18Lenny Rachitsky?

  You know, it's like, god damn it, just to learn a new thing again.

• 1:09:21Speaker 00

  Yeah, like, I hate repetition. This is like a me thing, like, I don't, this is why I'm like, not ever the best media person either, because I just like, I hate repeating myself.

• 1:09:31Lenny Rachitsky?

  Perfect.

• 1:09:32Speaker 00

  Sucks to be a founder when you hate repeating yourself, because you'd like have to.

• 1:09:35Lenny Rachitsky?

  Repeater in chief.

• 1:09:36Speaker 00

  And so like, to me, I'm like, if I can come in and do my job in a different way every day, love it, but like, that's not.

• 1:09:44Lenny Rachitsky?

  You found product market fit for your job?

• 1:09:45Speaker 00

  Yes, yeah, no, that's how it is. I like can't negotiate because I'm like, well, I don't want other jobs.

• 1:09:54Lenny Rachitsky?

  Amazing, man. Well, thank you.