# ChatGPT Work runs the Codex harness in a managed cloud Markdown copy of https://realalpha.app/s/chatgpt-work-runs-the-codex-harness-in-a-managed-cloud/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy. - Speaker: [Tibo Sottiaux](https://realalpha.app/builders/tibo-sottiaux/) · Tibo Sottiaux is an engineer who created Codex and head of Core Products & Platform at OpenAI. · Led OpenAI's launches of Codex, ChatGPT Work and the new Dots personal agent platform. - Host: [Gergely Orosz](https://realalpha.app/people/gergely-orosz/) · Host, The Pragmatic Engineer · Spent four years at Uber heading mobile, web and backend teams; shipped part of its payments system. - Show: The Pragmatic Engineer - Episode: [Building Codex with Tibo Sottiaux](https://realalpha.app/v/sLSTM9znQNs/), Sep 9, 2026 - Moment: 1:02:15 to 1:07:04 of the episode (5 min), playing on https://realalpha.app/s/chatgpt-work-runs-the-codex-harness-in-a-managed-cloud/; the episode from there: https://realalpha.app/v/sLSTM9znQNs/?t=3735 ## Quote > “ChatGPT work is essentially like running the **full codex harness in a cloud**, together with like a cloud computer.” > — [Tibo Sottiaux](https://realalpha.app/builders/tibo-sottiaux/) at [1:04:41](https://realalpha.app/v/sLSTM9znQNs/?t=3881) · The Pragmatic Engineer ## Takeaways 1. ChatGPT Work runs the Codex harness on a cloud machine. 2. The teams reconciled separate stacks, plugins, and libraries. 3. Codex captured project debates and decisions. ## About this segment The merge joined a local coding agent with ChatGPT's managed cloud stack, then unified plugins and libraries for broader access. Codex also recorded the teams' debates as they worked. From “Building Codex with Tibo Sottiaux”, Sep 9, 2026. [Watch the full episode](https://realalpha.app/v/sLSTM9znQNs/) ## Transcript Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there. [1:02:21](https://realalpha.app/v/sLSTM9znQNs/?t=3741) know you will actually do it speaking of hard problems and the fact that you're not out of them one of the interesting things that you've shipped from the outside it i would say it it was you know as an engineer was moderately interesting uh is the what you call the merge which is codecs appeared inside of chat gpc and the reason i say that as engineers it kind of moderately interesting because we've been using codecs like yeah it's there you can now open it in the chat gpc app great like i I just went there and I just immediately went to Codex because I don't really use ChatGPT in the app per se. [1:02:53](https://realalpha.app/v/sLSTM9znQNs/?t=3773) But I talked with folks at OpenAI and people in your team and they were telling me there was a lot of preparation going on, a lot of engineering challenges. Can you give a sense of how big this project was, what you needed to do, and why was it difficult to pull off and how did Codex and other tools help you get it done in ways that would have been hard before? Because since you've launched the merge, the numbers that you keep sharing of how many people use codecs, it's like it's going up way faster than before. [1:03:24](https://realalpha.app/v/sLSTM9znQNs/?t=3804) So I assume there's a big scale problem you've solved here. A lot of things were challenging with the merge is, first of all, completely different stacks. ChatGPT is like fully managed cloud-based. like you know you run everything on our uh on our systems we store things like traditional traditional way of like building things um built for scale built for for efficiency codex fully local and so the merge is just really like how do you get the same uh the same benefits and the same capabilities from this local coding agent and then build a product around it and build it in a way where it can benefit like a much much broader pool of people, which is just also why, you know, all of us joined OpenAI is like to benefit like this very, very broad population across the world. And so it was like a very exciting journey of [1:04:23](https://realalpha.app/v/sLSTM9znQNs/?t=3863) like figuring out like, how do we build a cloud version of this that in essence is capable of like very, very much the same things, but is also built in a way where, you know, we can serve it through like tens and hundreds of millions of users in a way that is still efficient so that we can include it all the way into the plus plan. ChatGPT work is essentially like running the full codex harness in a cloud, together with like a cloud computer. [1:04:54](https://realalpha.app/v/sLSTM9znQNs/?t=3894) It's a very powerful machine actually. Like people have sort of picked up on it and showed like, you know, what you can do. Like, you know, if you are creative. The prompt is that, you know, you can get you can get ChatGPT to train another model in there. You know, there's some pretty wild things. You know, you can get it to install Blender and, you know, do like 3D modeling. It's like very permissive. It has like internet access. [1:05:19](https://realalpha.app/v/sLSTM9znQNs/?t=3919) It's like a powerful machine. And then Codex just works on it. And this is like what we ship through ChatGPT works. So a lot of system challenges, the team did it very quickly. Obviously, like Codex helped you know, to make it more efficient, look at and build a lot of the infrastructure. And then, you know, help resolve a lot of the little differences as well that, you know, had been occurring between Codex and Chattapiti, like merging plugins, architecture, you know, merging library and like sort of like really, really working towards like unified system, which is really the goal is like you shouldn't feel like, you know, you can do something in Codex that you can't do in Chattapiti or vice versa. Like what we're trying to build is like one unified product that gives you access to the same intelligence, but in the way that you want [1:06:05](https://realalpha.app/v/sLSTM9znQNs/?t=3965) to use it. And so it was very fun as well, because Codex throughout the whole journey also acted as a journalist to sort of like document all the steps and the debates and the discussions that the teams were having. And it was very animated debate, you know, of how we should do it and how we should name the thing and, you know, when to introduce it in what way and like what to merge to what there were like many different permutations considered and so there's like a very fun journalistic element to it where we like we have a full recounting um that codex did over time uh and uh yeah it's just it's kind of become known as well as like the toggle arc of uh open ai where you know we introduced like the work toggle um which there was also a lot of debate around of like you know whether this was like the right thing and then you know it's just like we [1:06:51](https://realalpha.app/v/sLSTM9znQNs/?t=4011) I kind of grew to just really like it. But over time, we're going to merge things further. So it's like we're really headed into the direction of like full unification.