Claude Opus 4.6 vs GPT-5.3 Codex: Live Build, Clear Winner

Today is a massive day because Anthropic just dropped Opus 4.6 and OpenAI answered with GPT 5.3 codex, but what is the better model and how do you get started and what are some tips and tricks to get the most out of them? Well, this episode is all about that. This is for the technical person who's trying to get the most out of these models who don't just want hot takes, who want tactical sauce for getting the most out of these models. This episode of the pod is with my dear friend Morgan Linton Morgan is one of the best engineers I know. He was an executive at Sonos. He's invested in a lot of AI companies and he's building an AI company of his own. He's one of my first calls when I'm like, hey, which model is better? So we put the models head to head and there's a winner at the end. We rebuild Polymarket, a multi-billion dollar app, but we use these models. So which is the better one, you'll find out by watching this episode, but you'll also learn to become a better AI developer because you'll have these tips and tricks in your back pocket. I'm with one of my favorite people, Morgan Linton. You might not know him, but he is just, you know, just an incredible developer, founder, entrepreneur, investor. He does it all, but today what I needed him to help me understand is Opus 4.6 just came out. GPT 5.3 Codex just came out. Morgan, help me understand by the end of this episode, what are people going to get out of this? Yeah. Well, Greg, thanks for having me. Super exciting day. It's moving fast today. Opus 4.6 came out and then Sam Altman put together a quick tweet. I want to say maybe 18 minutes later, announcing GPT 5.3 Codex. And me, I think everybody else has been jumping on it, playing around, figuring out the differences. You know, all the little neat new settings that there are in each of these. By the end of this, you're going to know first how to make sure that you are running Opus 4.6 and all of the little details you can change in the settings I JSON file to use some of the cool features in Opus 4.6, especially agent teams, which is probably the feature I'm the most excited about. You'll also understand why you might use one versus the other because they both tackled different engineering methodologies. And then hopefully you'll see some cool stuff as we build some demos together that I've put together. I haven't tried myself, so I'll be trying just live with you. So we'll see how that goes. Cool. I think one of them is we're going to try to recreate Polymarket. Yes. And see which model performs best. They're going to have both. They're going to do a head to head to try to each build their own version of Polymarket. So by the end of this episode, you will have a pretty good understanding of how to use the models, when to use the models, how to get started. Morgan, let's get into it. Cool. Right on. All right. So I took some notes and essentially, you know, with five three codex, I'll be showing that in the desktop app on Mac because they're super excited about that. I'm excited about it. I think if OpenAI was wanting a demo to be done the right way, they would want me to do it in their app. Whereas with Opus 4.6, I would say the Anthropic team would want me to do it in the CLI. And so there's a few different configuration settings that you do want to make sure that you get right when you're using Opus 4.6, we're trying to use Opus 4.6 today, tomorrow, whenever it is that you're jumping into use it. I've seen a lot of people online today on Twitter saying it's weird. I'm having a problem like I'm supposed to be agent teams, but I don't see them or how do I know what version I'm running? So I thought, let's start by just giving everybody a level playing field to know, okay, I want to be able to use Claude code with Opus 4.6. How do I make sure I'm doing that and doing that correctly? So here's kind of the initial to-dos that everyone should have on their list. Just do an NPM update, see if that does the trick. If that doesn't and you're running an older version, then run Claude update, but you should see, like as of right now, it's 2.1.32. If you see one dot something, you're running an old version. And then what you want to do is go into your settings.json and I'll just show this here. So if you just do like CD, uh, Tilda slash. So I bet that there's people who are running the old model. They don't realize it. I've probably had bad idea. Yeah. Yeah. So I mean, make sure you go in here, CD, Tilda slash dot Claude. Here's your settings dot json. If you view this, here's essentially what you should see. Um, now it's okay. It can be model. If you want to like really be specific about it, you can put in Claude dash opus dash four dash six that'll lock it in. But because four six is the newest model, you can also just put in model and just opus and that'll work. The key thing that you want to do is that in my opinion, the coolest feature that they added with four six is agent teams. I'm super excited to demo that with you. Um, you have to make sure to turn that on because it is an experimental feature. And that's probably the biggest confusion I'm seeing people have today with opus four six is that they are running opus four six. They keep hearing about agent teams and they're giving it prompts like build a team of agents to do this and this. And it's not quite doing it. And that's because you do have to enable this. So you do have to add in end to this Claude code experimental agent teams and then set it equal to one. Okay. Nothing too crazy. Once you do that, that will make all that possible. Uh, so with that in mind, um, you're pretty ready to go there. Then you can just run Claude in the terminal and you're good for people that are using the API. The one thing I did want to point out is there's a pretty cool new addition, which is called adaptive thinking also just to be clear because I'm seeing confusion on this too. This is in the API. This is not in Claude code itself. Uh, but adaptive thinking just to show it here. You're able to essentially pick the level of effort that you would like the model to use. This is only going to work in four six. By the way, if you want to use like an effort level of max. And so here's kind of the different levels. So with max, Claude always thinks with no constraints on thinking depth. It's opus four six only. So requests using max on other models are going to return an error. So if you're calling the API and you set the effort level to max and you get an error, then you're probably not using opus four six. But here's the example where you can see if I'm calling the API, I set the model to Claude opus four six. And then here's where I can set the effort. And this is another thing. If you're using existing API code, you may have the model of opus four five. And now you adjust the effort to max. It gives you an error. All you need to do is just bump the version in your good. But this is kind of a neat thing they've added to the API with four six. That's worth worth mentioning. And then kind of the last, the last thing I would say is just if you want to use split panes for agents. So if you want agents to show up in different panes and you're using something like warp, just make sure to install T-mux. You can do this with Bernstahl T-mux. And then if you do that, it's going to default to auto, which usually means in process, which means in that same terminal window you have, the agents are going to be working all together. If you want it to split pain, then you just need to update that setting and the settings.json to split pains. I'm not going to go into super details on that, but those are just like, I think, good housekeeping to start with for anyone using opus. But don't worry about it. Really, all that anybody needs to do, especially if you don't even want to use teams, agent teams, is just make sure you're updated using the newest version and that the model is opus and it'll be using opus 4.6. Cool. So that's that. Before I get into kind of the differences between opus 4.6 and codex, I thought I would actually read this because this was posted on hacker news four hours ago. And I was reading and I was thinking, that's like the best way to explain it. So I'm just going to, I'm just going to read this little section here because I think they do such a good job with it. This person saying what's interesting to me is that GPT-5 through an opus 4.6 are diverging philosophically and really in the same way that actual engineers and orgs have diverged philosophically. And I think this really nails it. With codex 5.3, the framing is an interactive collaborator. You steer it mid-execution, stay in the loop, course correct as it works. With opus 4.6, the emphasis is the opposite. A more autonomous, agentic, thoughtful system that plans deeply runs longer and asks less of the human. That feels like reflection of a real split and how people think LM based coding should work. Some want tight human and loop control. Others want to delegate whole chunks of work and review the results. And I honestly, I think that says it beautifully. I think that that nails the differences. And also, hopefully, you know, everybody wants to pick a winner where it's like, oh, no, no, opus 4.6 is better codex. It's different. It depends on what your methodology is. And I think what we're seeing now, not just with vibe coding, but also it's like overall like AI powered engineering, is how do you want to work with agentic coding? Do you want to have a totally autonomous experience where you're sending agents out to do work? Or do you want to work with an LLM like another teammate and pair program with the LLM? And that's where you're now seeing a divergence where I think you're going to see a lot of teams using both because codex really is your collaborator. And what they've added with 5.3 is like really good, like mid execution steering. Whereas with with opus 4.6, it's probably the best of the best now being able to say, I want to spin up three or four agents. I want them to go do stuff. Hey, don't bug me. I want to trust they're going to do good stuff. And it's able to deliver. So are you saying that there in some ways, it's just a preference, like depending on how you know, there's no right or wrong basically, you know, not wrong to be an opus person or, you know, it just like might feel, yeah, it's just a preference. Yeah, well, you might be both, right? That's true. It might turn out that you're both. That's why, like, not to disappoint people here, but if we're not going to end this with me saying, and so the winner is, it's like, well, it depends on what you want to do. Everyone has a different methodology for it. So I'll dive in and try to try to make this part fast because I know the fun part is probably us going in and playing around with both of these and having them do a head to head and try to build a competitor to Polymarket and however much time we have. But I'll just start kind of going into these at a high level just so for any of them wants to know, like, what are the core differences? Why is this so interesting? It's going to what that is. So with opus 46, much bigger context window. So you have a million token context window here. Very strong coherence over entire documents and repos designed for, you know, like load the whole universe and reason over it. Five, three, they talk about large context, but it's not a headline feature. And I actually went back and forth of it to get it to actually give me a number. And the numbers around 200,000 tokens, which is not that impressive. That's small than I was thinking it would be. But that's okay. It's optimized, you know, for progressive execution rather than to recall. So that's why that's not as important. And, you know, optimized for deciding like what to keep in working memory. So high level, what that means is, Claude is better when the task is understand everything first and then decide. GPT Thrive, five, three codecs is probably better when the task is decide fast, act, iterate, more of that, you know, paraprograming, you know, mid-task change behavior. For coding benchmarks, you know, opus 46 is really good at code-based comprehension, refactors with like architectural sensitivity, explaining why a system behaves a certain way. And then, you know, a little less tendency of this like yellow right code, right? Which is I think something everybody wants. So, you know, that's good for everybody, but especially for vibe coders that are getting started and they may not be able to identify hallucinations. Opus 46 is definitely going to perform better there. But then for teams, you know, building in large code bases like like me and my team are doing, that's also really important. So kind of a win for everyone there. Five, five, three codecs did win on SWD Bench Pro, terminal bench overall. It's like scored better on coding benchmarks. So probably better end-to-end app generation. And, you know, Claude's kind of like senior reviewer staff engineer. GPT Thrive, probably like your founding engineer, right? Agentech behavior, opus 46. This is the key one, right? It's like the multi-agent orchestration. That's probably like the bleeding edge feature in 46. And then with five, three codecs, really like task driven autonomy, build, test, modify without being asked, but then this task steering, you can watch it, you can go in, it's like your buddy's coding and you can say, wait, wait, man, wait, why are you doing this? Then you can stop it and it'll go, okay. And then you can restart, you can really fix things in line. Much harder to do that with opus, with opus, you'll kind of be stopping it and then starting somewhat fresh. But it has a pretty big context window. So it knows what it did. But you know, Claude's really asking like, should we do this? GPT Thrive, three is like, how fast can I ship this, right? It's really, I mean, it's so cool because it almost feels like they're different people. I mean, they have different styles. Yes, totally. Yeah, it's a good look at it. It's like a different personality type, right? And then yeah, failure modes, Claude 46, it might overanalyze. It's got a much bigger context window. I can hesitate when requirements are in big US. And then it can stop short of full execution. Five, three codex could be overconfident, can lock in a flawed assumption early, but you can steer back in the right direction if that happens. So that's kind of a high level overview on the on the two. Cool. That's helpful. Yeah. So should we should we just dive in? I haven't tested any of this. So this is not I have like zero canned demos because I thought it'd be more fun just to try something together and see what happens. So should we should we try it? Yeah. Okay, so let's see, I'm going to I'm going to start with Opus. And I've got these prompts preloaded. So I'm giving different prompts. Just like I think you you said it really well. It's like you're talking to different people. And so, you know, when I'm talking to Opus, I can tell Opus, build me a team. And here's what I want each member of the team to do. When I'm talking to codex, I can't really tell it to build me a team, but I can tell it to think about stuff. So the prompt that I'm going to give to Opus is build a competitor polymarket create an agent team to explore this from different angles. One teammate on technical architecture, one on understanding polymarket and the ins and outs of prediction markets, one on UX, and one that just works on building really good tests to make sure everything works. For codex, I'm going to give it a little different prompt, but very similar. So I'll still build a competitor polymarket, but now think deeply about technical architecture, understanding polymarket and the ins and outs of prediction markets, good clean UX, make sure it builds really good tests, make sure everything works. And to be fair, I'm going to try to pace these in around the same time. You're a fair guy, Morgan. I'm trying to I'm trying to keep it fair here, right? It's the only way to do it. Like I said, no winners or losers. It's just about just about letting everybody have a fair shot to play the game. Yeah. All right, so let's see, I'm going to make different directory streets. I'll do, let's just call this Opus 45, polymarket, competitor. All right, so let's fireclot in here. By the way, if you want to check when you're running, just so I really make sure that you're in a good place, but the model, if you type slash model, I can see here, right? Clot Opus 46. All right. So I'm good there. I'm going to take this prompt, copy it, make sure this is all copied incorrectly. Okay, I got that. I'm not going to hit entry up. I'm making this totally fair. I don't want anyone at anthropic or open AI to get upset with me. So I want to be in good terms with both of them. Totally smart guy. Let's see. Oh, wait, actually, I do want to create a new folder for this, but we are keeping it real. We're being objective. Neither myself or Morgan are affiliated with either. Well, actually, I don't know you. I'm not. I'm not open AI. Nope. Nope. I love them both equally about that. Yeah. Okay. And I'm going to try to start as close to on the same time as I can. Enter, go. All right. They're going off the races. So what do you think's going to happen? That's a great question. Well, I know right now because I told Opus 45 to build using different teammates, it's going to do that. So you can see here, it says, I'll build a polymarking pedal by launching parallel research agents first, then synthesizing their finding to a comprehensive implementation planning code base. This is brand brand new, right? Like if I did this with Opus yesterday, wouldn't be possible. That's kind of the difference here is that the way that that codecs is working is the way things have kind of always worked, right? So if you see, this is like the individual visual person, right? It's not saying, okay, I'm going to launch all these different agents and compare what they say. It's like, okay, I'm going to inspect the workspace. This is your, you know, really detail oriented, really senior like founding engineer, like that example gave, right? Whereas over here, you can see it's already launched these agents. And now it wants to do web searches. And I'm going to let it do that. So multiple agents are asking to do web searches. So now, now launching all four research agents in parallel. So this is off. And I've got, you know, my technical architecture agent. I've got this other agent that these are both doing web searches right now. So one is looking at like prediction market order book matching engine architecture. So this one's learning about engine architecture for prediction markets. This one's looking at polymarket, how it works, a binary prediction market mechanics. And then I've got the UX design is doing some design research. And then we've got some test research. Okay, now it's going to go to polymarket. And let's really hope the polymarket doesn't block it. So that'll make things harder for it. Meanwhile, over here, this has discovered codecs. We've got the repos empty. So it's going to scaffold it from scratch. And it is starting to I'm now wiring the core market math and trading engine. So it's interesting, right? So you've got codecs is out here building. And it is like building the engine with opus four six. It still has agents out there like doing research work. Yeah, you really start to see just like how different they really are as they make progress. Yeah. And like I said, I haven't tested it before. So we don't know how long it'll take you to this. Yeah. And I think like, I guess one question I have is like, is one is one model better for being more of a beginner, non-tech body coder or, you know, doesn't really matter. Yeah, it's a good question. I mean, I think the fair answer would be probably codecs because codecs uh, edged out opus four six a little bit on some of those coding benchmarks. And it's kind of known for writing better production code, probably codecs in that way. At the same time, one of the downsides and like I said, I could only do this in a totally balanced way because they're so different. You know, at the same time for a a vibe coder knowing when to interject and stop codecs and say, oh, wait, you're doing this this way. Can you instead look at doing it this way, they're probably not going to know how to do that, right? And so that's where maybe opus four six is better where you could say, okay, spin up four or five agents and let them work with each other, right? Yeah. Okay. Uh, codecs is done. All right. Um, so codecs built a competitor to polymarket in three minutes and 47 seconds. And to be clear, polymarket's a multi billion dollar company. Yeah. I don't think this will work quite as well. But, uh, but we'll see. Let's see. So, um, let's just check out if it worked first. I'll let this keep running here. Um, so you know, it'll tell you at the end here. It actually did the testing so you can see it built a test suite. So it has an LMSR math unit test suite, an engine behavior unit test suite and an API integration test suite. And it passed with 10 out of 10 tests as far as what it built. It has this core LMSR market maker engine. So coherent pricing slippage bound loss behavior, domain trending engine, it built a rest API router, which is kind of interesting because I didn't tell that it would have to build, uh, obviously any of this in any way figured out the architecture on its own, uh, clean responsive front end. All right. Well, let's see. Let's see if it is actually. So, um, let's go here. I'll let this keep running. This has got these four agents just running away here. And I've been here. I'm going to do on PM test. All right. Test 10 past 10. That looks good to me. And PM start. All right. It's running. Oh, let's see. Okay. Here we go. Uh, so this looks like it has the ability. So let's, Greg, let's make you, we'll make you the first trader. All right. Say ad. Okay. You got a thousand bucks. Okay. There we go. Not bad. All right. What, uh, what market do you want to create? Um, well, Bitcoin, I think as we speak is crashed to what, 63,000 or something. Something like that. Yeah. So I do like the, I mean, we'll bdc be about, you know, be above 110k by. Yeah. Okay. By destiny one. That's pretty good. Yeah. Okay. So let's, yeah. Almost double. Yeah. Have you pretty good? It depends when you body, you know, if you bought it at 125k, then yeah. You're not so happy, but let's see. So then I don't know. I don't even know what resolution criteria and source would be. I mean, I think I know what it's getting at, but I guess you could say like, uh, why don't we say use coin market cap as the source and resolve by looking at the price on the last day of December. Just before midnight, I guess, I guess like, uh, the price of btc. Yeah. All right. Okay. It looks like it's okay. So we've got it now. So we'll use coin market cap. Okay. So then you can do a yes, 50%. So what do you think? Yes, yes or no? I mean, this isn't financial advice. This is just purely personal purposes. But I think, I think so. I think that. All right. That's a yes for Greg. Bye. Let's see. How many shares you want to buy? You've got a thousand bucks. I want to put it all. I'll put it all on this. I don't know how much it is per share. Let's see if it's a thousand if that's right. Okay. Yeah. Okay. Trade executed. Okay. So I mean, it seems like it built something, you know, as a prototype, relatively, uh, functional here. I guess that it actually has decremented. So okay. A thousand shares was not that end up being, uh, you know, about $24 that you spent. So you've got more money if you wanted to create another market. But it worked. It's not returning an air. It shows the volume here. Um, interesting. All right. So let's go back. Let's see. So far, so good with that, I'd say. Yeah. Let's see what's going on here. So we've got. Okay. So first off, look at how many tokens people have been talking about how token hungry, uh, Opus is. And it's very token hungry. Each one of these agents has used over 25,000 tokens. Um, so let's see though. So they finished, right? The, the, the technical research around architecture is done. Prediction market research is done. The UX design research is done. The testing strategy is done. Uh, now it's going to go and build. So it's writing the package, Jason. Did you see the ad that anthropic launched about ads? Yeah. I watched them all. They're hilarious. Oh, yeah. Although actually, I guess Sam was not very happy about them today. I saw a tweet from Sam that was less than happy. So, uh, I also, I found them hilarious, but I also understand his side as well. So it's really, it seems like anthropic is sort of anti ads for now. And, yeah. The chat GPT is going to be introducing ads. Yes. And, you know, when I'm, when I'm watching this and I'm seeing you're going through 25,000 tokens, 25,000 tokens, 25,000 tokens. Yeah. Yeah. Of course, anthropic doesn't. Yeah. Yeah. Yeah. I mean, this is literally, I mean, if you add that all up, you're talking about over 100,000 tokens in doing this. So I think that's one of the very good things, uh, for like investors in anthropic, right, is with agents and agents now being, I think probably the new killer feature in opus. Yeah. You're going to take whatever token usage and multiply by the number of agents. Exactly. It's actually really smart. And I wonder if that was like the thinking, like they're like, how can we get people to tokens? Oh, we'll just like spin up agents and we'll design it like that. Or, or did they think like, okay, how can we design a system that is best for the use case? And then they're like, then we'll monetize it like this. I don't know. Yeah. Yeah. Probably a combination of the two. I can tell you I've never used so many tokens in one day. That's today. So it's working. 100,000 tokens is like roughly how much in the US dollars. I don't know because I have, I have a, um, clawed max plan. So yeah. So I'm not paying, we're not seeing it in any limits right now, right? So I'm not paying more than $200. I can tell you that. Yeah. My guess is it's, you know, we're talking like in the $200 max plan, do you remember how many, how many tokens you get approximately? That's a good question. Let me try to fire up. Let me fire up claw and ask it. Let's see here. How many tokens do I get estimate? Let's see. Okay. So here you go. Estimate estimates. So 45 million tokens per month of Sonnet. But let's see. What is your estimate for Opus or six? It's like they don't really want you to know. No, they're trying to make it a little harder. Okay. But yeah, they're not going to tell me actually, they're just going to say there's no public data. It's very new. Opus is roughly five X more expensive. So then if it's 45 million, that's five X to 10 millions, probably the answer about, right? Yeah. Yeah. So then if we're doing, you know, quick math, let's just say we spent a hundred thousand tokens, you know, a hundred thousand divided by five million is, you know, we're going to spend more than that because look at this, we're now over 17,000 tokens on top of that in this next build. Okay. So but still, let's say, you know, even if we use a million tokens, building a competitive plan marker right now, we're only using a tenth of what it, but it can do. That's not terrible. No, I mean, it's $20, which is like the price of a cocktail in Miami. Yeah. Yeah. Exactly. Yeah. So let's say, but now, as I say, I'm watching the tokens creep out. All right. So it's building the API routes now. I have a feeling this is going to be a better end result. I was actually just going to say that this feels, and maybe it's just because there were four agents that were doing all the work beforehand. And now it's doing the work. If it feels like we're going to see something very different when we when we load what it builds. Yeah. I don't think we gave it any like design, like visual design, any, you know, so no, do you recommend her folks to just like sort of get the MVP out, out, play around with it on local host, you know, click some buttons and then sort of update with the visual design from there. It's a good question. I do like 50, 50. Sometimes if I have something in mind, especially if I want something like on brand with something like suppose I'm building something that is going to be in the like open claw multiple ecosystem, I would probably say, hey, I want to design a site that, you know, looks somewhat similar to or is inspired by, you know, open, open claw dot AI and notebook dot com. Right. Take a look at those sites and get inspiration. These models are great at doing stuff like that. Cool. I'm really excited to see what this is doing though. I think we're, we're now like well over 200,000 tokens. They feel like I could tell. But we're not a 10 million. We're not heading any limits. You know, we don't have to take out a second mortgage is on our yet. Yeah, it's still going. I guess, you know, we can tell like here's a interesting thing in a comparison like this is still going. Why don't we say like the design, because I look kind of bland to me, right? Yes, it did. Can you spruce it up and make it look nicer? Because like we may as well have codex working away too, right? Yeah. So you didn't really give it any like specific, it should look like square dot com. Now we'll see, we'll basically see if if codex, if you know, if five three has a little bit of taste. Yeah. Yeah. So that's what saying now, it's saying, okay, I'll upgrade the visual system without changing functionality. Stronger typography, richer color direction, better card hierarchy, and purposeful motion. I don't know what that means, but we'll find out. All right. Okay. So now it's now it's editing. Um, index of HTML. It looks like he's going to add motion hover polish. Okay. Totally that. This current task, we're over 30,000 tokens, building the front end UI. Okay, it's done. Yeah. Codex is fast, by the way. Right. I mean, that's pretty darn fast. Yeah. Um, so we should be able to just go here. It should have already automatically reload a bit. Okay. All right. I mean, I mean, not that, not that different. Yeah. I think, um, could I try something? Yeah. Go for it. I'm going to say, I'll, I would say, okay, thank you. But this was a minor design refresh. I'm looking, I'm looking for a major one. There you go. Yeah. And then I'm going to say, pretend you are Jack Dorsey and how would he design this website to be clean, elegant and full and full of interesting interactions. Yeah. Great. Yeah. Yeah. Jack Dorsey for people that don't know, co-founder of formerly known as Twitter and square block now. He's just got, he's got, he's a design guy. I don't know. He's first one guy came to mine or first person came to mine. Yeah. Yeah. That's a good one. That's a good problem. Let's see. So I'll do a full visual rearchitect, not an incremental tweak. New layout, language, stronger typography, monochrome, first palette, interesting and interaction driven cars. That's a, uh, okay. You know what's interesting is it didn't, I would have kind of hoped and maybe we, you know, we're not quite at AGI yet. I would have kind of hoped that it would say, let me go find some art. Like if you told me that Greg, like, in Oregon, can you read it? I would be like, yeah, let me go look at some articles about Jack Dorsey's design aesthetic. Exactly. I'm surprised he's not doing that. Instead, it's going like, I am assuming it knows who Jack Dorsey is, although I don't know if it actually does. It just seems like it, it's, it's really just taking like this part of your question and going, oh, okay, major refresh. I'll do that. Well, can, can't you ask it? Can't you say, do you know who Jack Dorsey is? Let's see. I can actually, I'm supposed to be able to, in the middle, cut it off. Let's see. Yeah. Do you know who Jack Dorsey is? Let's see. Okay. So here we go. This is the midstream test. It's thinking about it. 43,000 tokens over here. Okay. Yes. Okay. Here we go. Yes. Jack Dorsey is the co-founder of Twitter, Farmer Lockings Square. Okay. With a design style that's typically minimal restrain and interaction focused. Beautiful. Okay. All right. So Touche, it showed us. Now, here's the weird thing. It looks like it's, it's a complete, or do we have to say it? It's a complete, like right when I was saying that, but like, are you done or did you stop because I asked a question? Yeah. This is really interesting. I will say, like, that, oh, I paused when you asked the question, the major redesign, mostly. Well, if you want to resume, so that's weird. So you ask a question. It just stops, but like, so like, yes, of course, continue. Okay. So that's actually some weird UX. Like it obviously should just continue after. Right. Yeah. I would assume that it's such a weird thing as it said, yeah, if you want to resume now. I will say, I do like that you can, in midstream, like kind of edit things. Yeah. That's how my brain works. Totally. Totally. Yeah. Yeah. True. This is using a ton of tokens. Yeah. It is amazing to see the detail. I mean, this, this should be a work of art, whatever design this comes off with. All right. This is done. So now let's see. We can go back to this. Okay. I mean, I'm not blown away, but it's okay. Okay. Opinions become price in milliseconds. Trade conviction, not noise. Signal market is done for fast. These are iteration with transparent pricing. Okay. I mean, I would push it more, I think. Yeah. Yeah. I guess. Yeah. Like, I would say, I would say, that's not the Jack Dorsey. I know. I don't know, Jack Dorsey. Yeah. I was looking for a caps lock major upgrade. That might mean way more copy, way more images, way more storytelling. Yeah, exactly. Etc. Yeah. I'll just say seriously, take your time. Go nuts. Yeah. What are credits? Famous words. I know. All right. It's like, oh, perfect. Okay. That's like a signal with them. The opening headquarters is like, we finally got someone totally the way. All right. So Opus has finished. Yeah. I have no idea how many credits I've used, but probably actually let me ask it. How many tokens in total did you use to put all of this together, including the four agents? And then we can open to using token stamps. That's funny. Okay. Doesn't know. Let's see. Okay. Here we go. Okay. It's estimating. It actually doesn't know, which is weird, because it should know. Although, I wonder if I can actually do slash cost. Oh, here we go. Yeah. Okay. Oh, it doesn't look like now. No need to monitor costs. Okay. No, they really don't want you to know. Okay. It's guessing 150 to 250,000 tokens total. Yeah. That's all right. Okay. Sure. Okay. So here's what it's done. So first off, one really interesting thing here is, you know, Codex created 10 tests, right? Opus created 96 tests. So definitely a lot, a lot more detail on the testing side. And it's called it forecast, whereas Codex called it signal market. So different names. A polymarked competitor is built and verified. Here's what each team member delivered. So the architecture technical lead decided modular model with next year's 14 app router, central limit order book, a database schema, Rustle API. Okay. The prediction market domain expert, buying a new market, where yes, knows always a dollar. Okay. Seated markets across crypto politics. Okay. The UX is only dark mode trading platform. Pages. It is a green for, yes, red for no. Okay. Testing QA lead did order book tests. Okay. So here's the test of breaking out order book tests, matching engine. Okay. All right. NPN run dub to start the app. So let's go in here. And oh, interesting. Okay. I don't want to say anything actually. I already give it to you. What's your initial take? I mean, my hello, Jack Dorsey. You know what I'm saying? I mean, this is what I expected it to look like when we pushed codex. Yeah, me too. This looks really clean. What happens when you hover over? Oh, yeah. Look at that. Yeah. It's got over states. Yeah. It's actually got it organized. Like sports, you know, will the next few will have over 120 million viewers? Will AI pass the touring test by 2027? Will the movie goes over three? It's got stuff in there. Yeah. Yeah. This doesn't even, doesn't feel like an MVP. Yeah. This is pretty wild, actually. And it created some stuff, you know, that we never talked to about, right? Like a leaderboard, which it's already populated with some initial stuff, portfolio section. Yeah. Interesting. So let's see now. So, damn it. I mean, I'm more impressed with though, it was maybe worth the 150,000 to 300,000 tokens till and better about it. Will SpaceX land on Mars before 2030? Only 8% of things, huh? Look at this actually. Whoa. This is insane, bro. That's clean. That's clean. I wasn't expecting to click in and actually get a well-designed page like this. Huh. So if I were to do that, I have to sign in the trade. I don't know if I'm going to be all sign in because I haven't set anything up. Let me just check. Well, you can sign up since don't have an account. Oh, yeah, sign up. I don't know if it gets it all connected though. Let's see though. All right. I'm snagging. You know what? Actually, I'm going to take the username Greg. I'm still using a name. All right. Let's see. Okay. So yeah, it's probably because I was going to say the database isn't wired up yet. Right. So I'm not surprised that I would actually have to do. I wasn't expecting to do that. So but I get it. I mean, it's clean. This is pretty neat. Yep. Yeah. All right. Let's see. So then can this. All right. We've given, I don't know about you, but this is the last chance I'm going to give codex and design side. It's out of, it's out of opportunities here. So, oh, here it's funny. In the end, it kind of, it's acting a little bit like data from StarTrack. Yeah. And the question, what are credits? In this context, credits usually means. I wasn't quite it. That's good though. Okay. So let's see. Let's take a look and see. All right. Here we go. The new version of signal market. Boom. Oh, okay. This is getting a little bit interesting. Let's see here. Read the manifesto. Yeah. I mean, I don't hate it. It's definitely better. Yeah. I mean, it's, it's got a lot going on. Yeah. But it's different terminal. It's different than. Yeah. It's different than any sort of prediction market app I've seen from the UX perspective. I just feel like this is just so clean though. This is so good. Yeah. It's so fast. Yeah. Yeah. I mean, I would say, like I said, I'm not going to say which one is, it's not that opus is better than codex or vice versa. But I would say in this test, opus one. Yeah. In this test, opus one. Yeah. That's just the truth. Yeah. Yeah. But we could give another, I mean, you know, you never know. I think that what's interesting about this is, I mean, codex built it like, I don't know how much faster we can look at the timing on this video. But like 20 times faster or something, right? Yeah. Yeah. Well, anything else you want to cover, I don't think we'll have time to do another example. But anything else you want to cover between, you know, that you want to leave people with. Yeah. Let me see if there is anything else in here. I cover the adaptive thinking. Oh, I guess just on the orchestration, I would say, you know, this is the feature I'm probably the most excited about with opus. And clearly, we saw in this example, it working really well. Just make sure to look at the documentation. It's all in the docs now. And it gives some examples as well, because it has this idea of like compare with sub agents of like context and communication and coordination and kind of breaks this down. And then it has like a sample prompt more of the details on the display mode. There's a lot of other stuff that I didn't go into there that's probably to leave people with because I think a lot of people are going to want to dive in and use use agents with opus 4.6. And they've got pretty good details on all little tweaks that you can make with that. Amazing. Well, Morgan, I can't thank you enough for coming on. I hope people love this episode. I love talking to you. You get. Thank you for having me, Greg. It's a total honor. You're, yeah, it's just I love how clearly you communicate and to technical people, but also non-technical people. And you're criminally under followed. So I'm going to include. I have links where you can find Morgan and follow him on X. He talks a lot about vibe coding over there. And Morgan, anything else you want to, you know, places that you want to leave people to go and check you out? Yeah, I mean, I'm the co-founder and CTO of bold metrics. I'll just give a little plug for us. We have a AI technology that's used by parallel brands or retailers. So if you're shopping online and want to find the right size, you see a find my size button. We a lot of times power that and have really powerful machine learning models that update and adapt over time to help people find the right size and give lots of really interesting data to lots of amazing brands and retailers that you probably all know and love. And then me and my team, you know, we're using all of this tooling like I had a meeting with my team this morning about Opus 4.6 and codex. And I've given everybody access to both of these. And I actually have multiple teams of mine that are trying current things we're working on and are actually testing with each to see which performs better. So, you know, the one thing I encourage all engineering teams to do is like, and engineering leaders to do is like, let your teams loose with this stuff, let them try it. You know, some of this stuff is really cutting edge and really performing and gives us the opportunity to do better, more creative work. Yeah, stop listening to us right now. Yeah, exactly. Stop going. Yeah, ex out of the YouTube or Spotify link, but actually give us a like, a comment and subscribe. Let us know if you like this episode. Morgan, thanks again for coming on the show. This was a lot of fun. See you next time. Craig, thank you so much. Total honor.