Ed Bayes

I kinda came in, always worked on research projects, and then worked on chat, and then kinda worked on this, and I think you mentioned that it's been like priority since 2025. I mean, the original Codex model, which was a coding model, came out in 2021, so it's always been this, always been there. And I think it was just very clear, early on, kind of anyone that's worked on it, how powerful this stuff is, right? Like if you used the early Codex, even pre-GPT-5 or any of the Claude Code models, you could kind of see where it's going. So I think it's more of first trying some of these new models or seeing some of these new capabilities, you're just like, "Gosh, this is gonna change everything." So it's less about some kind of corporate event and more, for example, with the merge, we kind of announced the merge internally and what we were gonna do and bring these things together. And I just remember coming out of it speaking to a few people just thinking, yeah, it's just crazy that we've gone from this tiny group of a few people in the corner, most of the company obviously paying a lot of attention from the research side but from the product, chat, consumer product, very much focused on different ends, and here we had this kind of coding product which is kind of enterprise-y. So from a product and design perspective, it was very much just kind of like, oh, this team in the corner doing their own thing to kind of coming out these meetings of, okay, this is now the future of ChatGPT, basically. And that was just quite astounding. I've just certainly never been part of a team that has had such a trajectory of users and the kind of the power of the product.

Do you have a specific memory of that specific meeting of like how that happened? Like now this is ChatGPT.

Yeah. I mean, I don't know if there were like specific—I—the one I'm thinking of is just an all hands basically, where Tibo or someone's basically kinda saying, now we're gonna bring the power of Codex to chat and this is the rough shape that it's gonna take and I had some early designs I kind of set up as—and presented. So it was just a team all hands basically coming away, and it was very much like, congrats to the team. We've done so well that now it's gonna bring it to the kind of billion user space.

One of the things I'm trying to understand is like, this doesn't—this just doesn't happen. You don't like start a small team inside of a big company and then end up disrupting the main 800 million or billion user product. People have tried for many years.

The way that OpenAI is structured is it's a large company but it's still structured with very small teams building products, and when you're on one of those teams, it feels like you're part of a scrappy startup. You have these pods, you have a PM, a designer and small team of engineers, a research lead, maybe a few researchers. And, these projects really start very small, like five to 15 people working on very ambitious but quite discrete projects, and that's kind of how a lot of the company has worked. It's this kind of like a constellation of these groups. People talk about coding agents being this new thing. I mean ChatGPT is an agent, right? It just has a different harness so it's not two completely separate products. So it's realizing the original promise so it's more of an evolution.

When did you join the Codex team?

After we launched Codex Cloud. I was asked "Okay, can you build this like CLI thing, and then we're gonna do this IDE extension?" And I was like, "Yeah, cool. Pretty chill." [chuckles] And then we launched the IDE extension with GPT-5. We started to have this steep curve, and you look back now and it's like tiny, but at the time we were like, "Wow, so many users!" Then we decided to do the desktop app and built that out with a very small team and then we launched that earlier this year and then it's now grown into the merge with ChatGPT.

What are some of the like design challenges—I think the Merge is a really interesting one that I'd like to get your take on in a second, and I've talked to Andrew so much about tabs and just whatever. But before we get there, what are some of the design challenges for the desktop app that are like maybe unintuitive, like that you ran into?

The original desktop app was very opinionated and the thesis that I discussed with Alexander a lot was this is a command center for your agents. So as a result we optimized for being able to run multiple agents at once. This might sound like a small design detail, but at the time other similar products had two lines in the left sidebar. They had a bunch of icons. It was very noisy. I very intentionally flattened it into a single line, very clean, very similar to chat in that sense, so that you can basically work on double the number of tasks at the time. And also orienting it around projects, which is I think another pattern that others have now moved towards. Previously if you're in an IDE, you have to open a new window to work in a different workspace. Here you can work on front end, back end next to each other. So you can kick off 10 tasks and work in parallel. The challenge was, we're building a developer tool and developers want all the bells and whistles, so it's this healthy tension of trying to simplify things and delete things and make it very, very simple. And then just really obsessing over a few core flows for developers, thinking through the entire software development lifecycle from coming up with an idea to creating a PR, to code review, to merging it, and building a bunch of things like worktrees around that.

Tell me about the merge.

Yeah. What about it? [chuckles]

I mean, it just seems like the gnarliest thing ever from a design— I mean, from a lot of perspectives, but in particular from a design perspective.

There are a few really interesting design problems here and ideally you'd abstract all of these away from users, particularly non-developers. So first you have ChatGPT. You have all of these cloud-based tasks in a ChatGPT harness, and then you have Codex, which is this coding agent that works on your computer and it works with local files. So first you have this kind of incongruity between local and cloud. Then you have these different types of tasks which do different things. One of them has access to a computer, either on your computer or in the cloud, and another doesn't have that. So we're working with a lot of these constraints. There's a clear path to reducing the constraints or making it a little simpler to users. But until then, you have this like messy middle. You also have an innovator's dilemma type challenge where you have this existing product that people have a very clear expectation for, and then we have this new, powerful kind of way of using it, and you have to teach users how to use it. So they're the kind of constraints and you have to work around them. But you can expect over the next few months some of those become simpler.

That's interesting. Do you have any— Do you have a specific memory of like a specific design challenge that you were working on where you're, you figured something out that you think is unintuitive or underappreciated?

I guess it's more of a like high level principle that I generally believe in, which is with ChatGPT we have this universal interface for asking questions and with Codex we have a universal interface for getting work done. Until now we have these bifurcated products where you have a developer tool called Codex, and then you have this general product called ChatGPT. But if you're a PhD scientist studying rocket science, you don't use a different ChatGPT to a grandmother in Michigan who's learning how to knit, right? And I think we'll get there with Codex in ChatGPT too. Maybe that's slightly unintuitive in that we've got to this space and developers are very much like, "this is for developers." But I do think it benefits everyone if you simplify. And we saw that with some of the examples that I gave of like simplifying the left sidebar and moving things around projects. If you simplify products, that generally benefits all users, even power users.

What do you think of Tibo and what makes Tibo effective at what he does?

He's very good at getting things done. He straddles research and product, and that's really rare. His deep understanding of the research org and the research program, and bringing that in line with product. At a frontier lab, the best thing you can do if you're building product is thinking about where we're going to be in six months and building for that world. And that's basically the bet we made with the Codex app as it only really made sense once you had this generation of models that came out in December. So not only is he just very effective at getting things done but also lives in that world where you kind of look forward a bit and design for that. He's just a great guy as well. I think people really like working with him, and that helps as well when you're a leader and you're trying to bring people along.

Anything else that we haven't talked about you think we should before we end?

I don't think so. I'm curious your reflections on the journey over the past year.

I mean, I think that it's, like I said, it's like super rare to fall behind and then come back by disrupting yourself. It's just like super rare. And right now, I think of you guys as being the one to beat again. And it feels like Anthropic made a big bet on a gigantic model that is, in my view, more powerful than 5.6 but is very hard to use. And you guys have an incredibly well post-trained model that is in the best harness and that is actually better than the super ultra intelligence that can't talk to you. Which is—that's an unintuitive thing. And not only that, but the super ultra intelligence, it seems like is making the rest of their models worse because they're using it to make those models, and those models now have the same personality. So—I wouldn't have guessed that. Yeah. I also think that—you guys had 4.5, which was the big model that didn't really work that well, and I don't think Anthropic had that. I think they just got into that, some of those difficulties.

Hmm. Interesting. Yeah. See, yeah, maybe one other reflection I think, and this is actually something that Lindsay once said to me, which is I think one thing that she always is very impressed by with the Codex team was it was very AGI-pilled. And a lot of that came from leadership of Tibo. And I think the very unique thing as well is the team was just like very uniformly very strong, very founder-led, very AGI-pilled. It's quite rare to have a small team who are so aligned and similarly pointing in the same direction and philosophically aligned as well.