OpenAI DevDay 2026: Dots, Spaces, and ULTRAFAST

1. 0:00 – 0:58

   OpenAI DevDay recap—and pressing the Codex reset button

   1. CVClaire Vo0:00

      Today I spent the day in San Francisco at OpenAI's DevDay, and it was a fun one, not just because Thibault let me smash the Codex reset button for you all. I was there from the keynote throughout the day, and I have good news for you and bad news for you. The good news is OpenAI released a lot of stuff. The bad news is OpenAI released a lot of stuff. There was a lot jam packed into the DevDay keynote, um, everything from OpenAI's answer to GroqBot and Muse to platform components that developers are really going to use. It felt like every two or three minutes the team was announcing something new. I was able to test some of it early. I wanna share for you the highlights from the releases so you know what to pay attention to, depending on what's important to you, and also maybe three or four things that I've spent a little bit more time with and have come to an early opinion on so you can see what I think about all these new releases. [upbeat music]

2. 0:58 – 6:57

   Dots: early impressions and rough edges

   1. CVClaire Vo1:00

      Okay, so the big release of the morning, the big bang thing, first thing up in the keynote is Dots. Dots are an always-on long-running agent that can work across ChatGPT, across Codex, in its own computer, on your computer, on your phone, whether through text or through call, even in your Slack, to get work done for you. And I was able to test Dots pretty early. In fact, so early it's hard for me to give you all a full review because it's very clear that the OpenAI team is building and building and building on this every minute, every hour, making it better. I think what I want to get across to you is, like, where do bots sit in this ecosystem of, like, GroqBot's very popular, Muse is getting some traction, Instinct is still out there, you know, texting people. What are Dots? What do I think of them? And where do I think they're going? So again, Dots are your agents, and I asked the team, do I get one Dot or many Dots? And right now we are issued a single Dot. So, if you're on Pro, Business, Enterprise, a couple of the key plans, you should have your Dot in ChatGPT in the Codex app right now. So this is my Dot. Her name is Bay. She's a pink blob with glasses and googly eyes. And Bay has her own computer. So as you can see here, there's a machine that your Dot can use or you can take over and use it yourself. It's loaded with, of course, a browser, but also a bunch of apps, things that are probably pretty interesting to developers. In addition to their computer, you can give your Dot access to your local computer. So again, sort of this, like, always on, in the cloud, anywhere bot that can work locally or it can work in its own machine. Some interesting things that they're pushing with Dots is the kind of like multi-channel experience of a Dot. So you can, of course, use your Dot in the ChatGPT desktop or mobile app, but you can also call your Dot. So they, they've actually made this not voice mode with your Dot. They're really calling it call your Dot. It rings, it picks up. I'm curious, it's like an interesting, unique interaction, user experience pattern. I'm not sure that I quite get all the interactions between transcribing voice, live voice, and then calling. But you know, you do you, Bay. And then of course, because we're all enterprises, we're all teams, and we're all on Slack, the ability to install your Dot in Slack. Now, one of the things that I find most confusing about Dots is just, like, where does it sit in the ecosystem of all the other ChatGPT surfaces, um, and all the Codex surfaces? So you know, Dot can do work. They position it as a sort of like replica or delegate of you. So it's sort of like your main thread. Um, and so you have like kind of like one master Dot that is responsible for all your work, can be proactive towards you, can remind you of things, can do work on its own, but it can also kick off Codex threads. Um, and I think chat threads are kind of like one and the same. Um, and do work on your behalf. And so, you know, I think they still have to figure out the information architecture. I wanna do a full Dot review, but I wanna do it when it's baked, and I know that it's really going to work. But it is worth paying attention to. [smacks lips] I will say that early takes are the work itself that these Dots do is good. Like, I had it go shopping for me. It found the right shoes. I had it code something for me. It coded it well. Um, it's proactive in exactly the right way, which is I was trying to figure out my kids' weekend schedule and whether their swim classes conflicted with another thing we were trying to do with them. And then this morning it said, "Hey, do you want me to look for November ones? Here's your options." So I, I, I say the bones of your Dot, which is a very weird thing to say, are good. There are a bunch of rough edges around the user experience. I think there's a bunch of rough edges around Dot's position in all the primitives that you have going on with chat and Codex. I think it's very confusing to understand what's a Dot thread, what's a chat thread, what's a Codex thread, but I think the surface area is moving quite fast. And I think people are gonna have to decide what they think about using their Dot. Where do I think I'm gonna use it? I'm probably gonna respond to its productivity. So Dot is gonna be able to pull me in if it is proactive and suggest using my chat or Codex memories useful things it can do for me. I think that's how an OpenAI agent gets my attention, is it pushes interesting things to me, and I start to engage with it a lot more. I will say right now, early take, and again, I'm not doing a full Dot review... I'm still sitting and using my GroqBots for work. I just like defining micro agents for work, just like I would hire someone. I like to hire an agent for a job, so I'm not really a one, one agent to rule them all person. And then I think the user experience of Muse is just a little more consumer friendly, a little bit more approachable. Um, the avatar is super cute. So I'm gonna give it a whirl, but I'm not gonna give you all a full review until I really feel like I understand the differentiating features of this, and I can tell you exactly where I think it fits in your stack. So it's like early innings. It's got all the makings of something that's good. The actual work it does, because it's powered by these OpenAI models, is really good, and it's pretty smart with memory. I'm just not 100% sure, uh, yet. So we're gonna hold off a couple weeks. I'm gonna come back to a review here. All right, so Dots big review. What

3. 6:57 – 10:37

   Spaces: working with humans and agents

   1. CVClaire Vo6:57

      else is big i- I think one that's under-hyped, and I said this on X, is ChatGPT Space. Space is a place in ChatGPT where you can work on documents, artifacts, slides with humans and with agents. And I think this is what companies have been waiting for. We have been waiting for an AI native document, slide, HTML collaboration platform with all the right sharing built in, with all the right data controls built in, with all the, like, agent native kind of aspects of this built in. I mean, honestly, I built this at ChatPRD early on because I knew that people and agents wanted to collaborate on the same document, and so the OpenAI team has built Spaces into that same concept. So if you see what Spaces can do, it can create pages, it can create documents by which you can collaborate with both your human friends and your Dot, your agent friends. Slides, again, another surface area for businesses where a lot of collaboration happens, and I know that, you know, ChatGPT, these other AI tools are really great at creating slides, but not really great at editing and collaborating with slides, and so this is a big win. And then all the, like, good stuff around sharing permissions, et cetera. One of the things I love that my Dot did, one moment of delight that I didn't touch on in the overview before, is it made a space for me called your personal scratchpad. And it just created a space where my Dot and I could just collaborate via Dot on things we have to do. And I don't know if they read my mind. I have a very, um, loosey-goosey approach to my to-do list. I'm never gonna be like an organized table Notion boy. Um, I just want a stream of consciousness, list of bullet points, and comments I can make on things I need to do that I can check off with me and my agents. And I actually built this. Um, it's called Claire's Notebook. Let me pull it up really quickly. Uh, so what's really funny is I actually built this for myself a couple weeks ago. I built this collaborative, um, document where me and all my agents, Codex, Groq, Muse, could all collaborate on our to-do list, 'cause I was working across a bunch of agents. So I did invent this, invent it here, um, this collaborative doc. But a good example of a space, again, is this place where you and your agent can just keep a running list of to-dos, decisions, notes. It also created documents for me. I'm prepping for a talk. Um, I have how I AI recording plans, so what's coming up next. And again, what's nice about this is it's not just a doc. It is, um, you, you have the ability to at mention your doc, at mention ChatGPT, and get updates to the doc. And then you can just imagine this across slides and other artifacts. So this is really like a little bit of shots fired on Google, which again, is just watching this AI opportunity go by. They have all the goodies, and yet OpenAI, Meta have all beat them to the punch. We gotta figure this out. But I do think Spaces are one of those things that enterprises really want, so I'll really be watching to see who actually adopts Spaces. Will you see companies move more and more to these OpenAI hosted documents or not? And how kind of the push and pull between some of these source of truth, um, business collaboration platforms like Slack, Google Drive, Dropbox, et cetera, play with Spaces.

4. 10:37 – 13:06

   Sites, connectors, and sharing internal tools

   1. CVClaire Vo10:37

      The other thing that is related to Spaces that I think is really interesting is the updates announced to Sites. Sites, in case you don't know, is sort of like OpenAI's built-in website app builder that can be deployed. Um, you can sign in through ChatGPT, and then anybody can access your web app. It's sort of like bridging that gap between deploying something locally and something you can share. You know, they pulled Sites into Space, so it has nice sharing and permissions, but the one thing that they added to Sites, which I think is really, really, really smart, is you can now bundle connectors and plugins into your site. So let me just give you an example. L- let's say that you wanna create a dashboard, a custom dashboard pulling data from your Snowflake. You have a Snowflake plugin through your ChatGPT app, and you wanna just use that same data in your shared reporting. Well, you can now use that plugin to power the data in your site. And then what's really interesting about this is if you share it to somebody on your team, they can log in and they can use their connector. So if they have access to the same data, great, they see the report. But if they don't have access to the data, then those controls come in and they can't view the same thing that you can. This is truly the number one problem I hear from enterprises that we work with trying to figure out h- what to do with all these vibe coded internal tools, what to do with all these vibe coded platform ... what to do with all these vibe coded prototypes, what to do with all these vibe coded reports. Everybody's like, "What do I do with this information?" And I think this Sites plus plugins is OpenAI's answer to this. I am really curious. Again, I think there's this competition between, like, Claude artifacts, OpenAI Sites, where is the enterprise source of truth gonna be? And I think you really have to compete on the things that matter to companies, which are, like, easy access to data, governance and controls, permissions, you know, ease of sharing, and then quality of these artifacts. So I think it's really interesting. Um, coming up next week, we actually recorded it at the event. I did a live episode with Cath, the product lead on Sites, where she's gonna show us all the, like, magic in Sites. But this is something that I think you should, if you are an enterprise considering ChatGPT as your platform for collaboration, that I think is quite nice. Now, I've covered two, three big things, which is Dots, Agents, Space, like collaborative workspace, Sites, just like a nice little quality of life thing here.

5. 13:06 – 14:36

   Models and platform: GPT-6.1 Sol

   1. CVClaire Vo13:06

      Let's talk about the things that I actually care about. Model. [snaps fingers] Models and platform. That's what I care about. Your girl is a software engineer at heart. I am excited about models. I am excited about infrastructure, and I'm excited about platform components. So let's talk about what those releases were. [smacks lips] It was actually really funny. One of the first things Sam Altman said is, "You know what we constantly get feedback on? We just want faster models cheaper." And it's like, of course. We all want models faster and cheaper. And they did release GPT-6-1 Sol. This is almost Astra intelligence at Sol speed and really, really cheap cost. Um, so it's $2 per million input tokens, $10 per output token, which is much different than Astra, which is $10 per million input tokens and 50 per output tokens. So it's a lot less, and it's a good one. S- and I, I love the Sol models. I have loved the Sol model since it came out. It's just a workhorse. It's sort of like my middle-of-the-line most engineering tasks, um, model that I work with. I do love Astra the very most, and so because I will pay for the tokens, I'm, like, happy to be in Astra. But if I were being more cos- cost conscious, I would definitely spend time with Sol. Sol is super awesome, and I think is just gonna be a welcome, um, addition. But I'm excited about two other things that I wanna show you.

6. 14:36 – 15:27

   Decisions API: fast decisions with vision

   1. CVClaire Vo14:36

      You all know that it's Jev week this week on How I AI, and you know what? It's also OpenAI Dev Week, and they announced a Decisions API. So they announced their little Jev, Jev competitor. This is basically Luna with constraints, and so it's gonna have Luna intelligence on a predefined set of answers, and it return decisions very fast. [smacks lips] Now, that sounds like a fast follow to Jev, but there's more. I was able to test a little bit of the Decisions API, and it has vision. It has vision. So we get the speed, cost of, like, a Decisions API, a Jev style model, with eyeballs, with computer eyeballs. And I wanna show you an example of where I think this is super, super

7. 15:27 – 16:29

   Finding better podcast thumbnails with AI

   1. CVClaire Vo15:27

      useful. So I have an episode with our friend John Lindquist on Jev that we recorded. It's about a 40-minute episode, and we need to make thumbnails. And every time I make thumbnails, I have to scrub through the video and find when we're not making awkward faces. And I can do this with... Some models are actually quite bad at it, but it takes a lot of time because we basically, like, clip every two, five, 10 seconds. We try to find places where our faces aren't awkward. And so I built this with the Decision API. [smacks lips] It took less than, I don't know, 10 second... It was, like, very, very fast. And it went through 100 frames and found all the ones where we were not looking awkward. Like, look, we look so happy. It's really cute. It's really hard to find photos where two live guests do not look weird, and the Decisions API did that for me. And this has actually been a real pain point for me, something I couldn't solve with Jev, 'cause Jev doesn't have vision.

8. 16:29 – 17:17

   Hot dog or not hot dog?

   1. CVClaire Vo16:29

      Okay, also very important with Jev, I built Hot dog, Not hot dogs. Okay, so if I select this picture of a hot dog, and I... It, it is 100% confidence in less than a second that it is a hot dog. So again, AGI's here. Decisions API, you all know how bullish I am on Jev. I think this is, like, the missing piece in a lot of our AI architecture, and so I'm really excited to see OpenAI announce this. They haven't released it yet, so TBD on when it's fully released. I got a little bit of early access testing, but when it's released, I will definitely do a head-to-head eval, Decisions API versus Jev, and tell you what I think. So those are kind of, like, two models that we're very excited about, uh, Sol

9. 17:17 – 18:50

   Astra ultrafast: speed, pricing, and possibilities

   1. CVClaire Vo17:17

      6-1, Decisions API. But what's the one that I really want? I can't afford it, but I want it. Ultrafast. So ultrafast... You know, there was fast. It is ultrafast. Now, I don't know if you know this. You can run your models in Codex on normal mode, on fast mode, which is two times as fast, or on ultrafast, which is eight times as fast. Now, it costs six times as much. It's expensive, but GPT-6 Astra ultrafast is available in Work Codex in the API, and I got to test this also a little bit early, and this is the one that is making me feel the future. You all think I would put Astra on, like, extra high reasoning and let it rip through my bug backlog, re-architect something, build something new. No. I, I wanted to see what someone could do if they were using ultrafast via API as part of their stack. So what I think is really interesting is if you can get very high intelligent, at almost real-time experience, you can build some AI things that I think you couldn't build before. And like a good podcaster, you can build games. And so I wanna show you two games that I did with Astra ultrafast that I think are just really interesting. I think the latency is still, like, a little bit, um, slow for what would feel like a real-time app, but it's pretty magical, and I hope this just kinda like opens up your mind to what 8X, 10X, 20X, whatever's coming soon at the highest frontier intelligence

10. 18:50 – 19:45

    The Other Pencil: drawing alongside AI

    1. CVClaire Vo18:50

       can do. This is called The Other Pencil. It's an AI human collaborative sketchpad. And so if I go in here and do some waves, um, then Astra's gonna come behind me and draw SVGs that, uh, match what I do. And so let's see if I put, like, a circle here with a smile. Oh, no, it made a little [laughs] it made a little chicken. It's very cute. It's, like, e- almost too fast for me. Let's see if I do a flower here, maybe what it will do next. And I don't know if you remember this from my Astra review, but Astra's really good at drawing SVGs. And again, this is something that I just feel like you couldn't do real time before, that is super cute and very fun. Oh, look, I got a little ladybug. But let's take it a step further. So this was real-time SVG drawing with Astra. I think it's super cool, and something you couldn't do before, but let's take it a little further.

11. 19:45 – 21:24

    Little Starship: a 3D world you can change with a prompt

    1. CVClaire Vo19:45

       So this is Little Starship. This is a 3D app that I built, um, and it has three characters. It's Pip, Momo and Sprout. Now, this was 3D built by Astra pretty fast. I didn't do, um, ultrafast, but it was built pretty, pretty quickly. So Astra can definitely code an app like this. But here's where Al- Astra ultrafast comes into play. So if I type in here, and I wanna use those other rooms, and I say, "Let's build a bathroom for our friends," then what happens is it uses Astra ultrafast to render these new 3D objects super fast, real time here in the app. So it's done a really detailed job here. There's a little rubber ducky. There's bubbles in the bath. Pip has gone over to the bath. So you can actually build this sort of, like, real-time game. My kids were doing this yesterday. They were doing so much stuff. So let's say, "Let's all go on vacation to a tropical island." Um, and it will completely change the scene of this little game. So look, there's a little, a little island it made with a coconut tree and, um, some sand, and all my buddies are coming over to hang out on my tropical island. Now, you can also change the physics of the game. So let's say, "Remove gravity. It's time for a float party," and it will remove gravity. And like, again, it's very, very fast. It's a couple seconds to do all these changes live. These are all rendered through Astra ultrafast, and my kids were playing this for like 20 minutes last night. Now,

12. 21:24 – 22:25

    The $97 AI game—and what it makes possible

    1. CVClaire Vo21:24

       real talk, it cost me, like, $97 or something to run this for 30 [laughs] 30 minutes. So it was not cheap. Um, this is a very expensive game, a little expensive demo for you all, but I just think how cool this is to be able to do these, like, real time code rendered games. Um, it has like, keeps a big long log. These are all the changes that we made to, um, to the planet, all the changes we made to the ship. And again, like, this is a, a cute little example, but, but I do think if you can start thinking about, like, what real-time super intelligence would look like from a user experience perspective, there are some pretty cool things you can build. So from a model perspective, really excited about Sol 6.1 'cause it's fast and cheap. Really excited about Vision and the Decisions API, and really, really, really excited, my wallet is not excited, about ultrafast.

13. 22:25 – 23:03

    Agents API, computer use, plugins, and plan updates

    1. CVClaire Vo22:25

       There were a lot of other things announced. I mean, again, there were just so much, like, Agents platform, computer use in the Agents API, all the Codex primitives enabled for developers. There are updates to how plugins work. Rumor has it that you can even monetize at some point your use of plugins. They've announced some changes to the ChatGPT plans, including a new Pro 500 plan. There was a bunch of developer primitives released so that you can build with the same infrastructure and tools that Codex is built on, including using the Agents API with computer use. There was just

14. 23:03 – 24:19

    What I’d try first

    1. CVClaire Vo23:03

       so much announced today. But if I were to tell you to pay attention to a couple things, it would be give Dots a whirl, tell me what you think, full review coming later. Um, it would be if you're at a company and you're really struggling with collaboration on AI generated tools, either with humans or agents, to take a look at Space and Sites. And then the models, the models are just so good. And as a developer, as somebody who both builds with these models and builds on these models, I am very excited about the Decisions API with Vision, and very, very excited about ultrafast, just because it makes me really imagine what the future of AI products can look like. This has been my very fast OpenAI DevDay recap. Highlights for me, um, episode with Cath from the Sites team coming this week, and, and I can't wait to hear what you've tried, what you're excited about, and what you think I should cover next. Thanks for joining. Thanks so much for watching. If you enjoyed the show, please like and subscribe here on YouTube, or even better, leave us a comment with your thoughts. You can also find this podcast on Apple Podcasts, Spotify or your favorite podcast app. Please consider leaving us a rating and review, which will help others find the show. You can see all our episodes and learn more about the show at howiai pod.com. See you next time

Episode duration: 24:20