Whats really going on with AI, Expert weighs in

AI researcher Dimitri joins the show to talk about the real impact of AI on software engineering. We discuss token costs, AI coding tools, the future of developers, and whether engineers are heading toward a world of reviewing AI-generated code instead of writing it. It’s a grounded conversation about the hype, the risks, and where AI might actually be taking the industry.

• 0:00Speaker 00

  Welcome everybody to The Stand Up. We have an extremely special episode of The Stand Up. If you have been living under a rock, you did not realize that Casey has started his own podcast, a competing podcast.

• 0:11Speaker 01

  Competing.

• 0:12Speaker 00

  I know, Casey, how could you do this to us?

• 0:13Speaker 01

  The Sit Down.

• 0:15Speaker 00

  How could you?

• 0:20Speaker 00

  Uh, anyways, I'm sorry. He and Dmitry are talking about and having a real conversation about what is the actual effects of AI and all that. And you're probably asking, well, why would they do that? Well, Dmitry turns out to be a legend when it comes to AI. He knows a lot about it. He's been working in it for a very, very long time. And just like Casey, is significantly more competent than TJ and I combined. And so therefore, their conversations are actually useful and good to listen to. And we thought we'd bring them on and ask some of our own very own questions. Kind of a podcast melding.

• 0:51Speaker 01

  There's a lot less Cars references and jokes in their podcast. So if that's what you're looking for, just make sure you're still coming back here. But if you're, you know, just wanted to make that clear, where are sort of competitive edges? Is the Cars references?

• 1:07Speaker 00

  Specifically, the Cars references, and that is it.

• 1:10Speaker 01

  Exactly.

• 1:11Speaker 00

  Oh, they also do like technical skill and excellence and all these other things and have deep, reasonable conversations.

• 1:16Speaker 01

  Well, we weren't listening what they did better. I was listening what we did better. Cars references.

• 1:19Speaker 02

  Focus on the positive.

• 1:21Speaker 01

  Yes, right. I'm more of a glass half-full kind of guy, or like glass 1/10 full kind of situation here.

• 1:27Speaker 00

  Glass has water kind of guy. That's the person I am.

• 1:31Speaker 02

  All right. In all seriousness, though, this was, the podcast was actually Dmitry's idea. It wasn't even my idea. It should have been my idea because I agree that I should ditch you guys and go with some like, some higher quality co-hosts here. I mean, that's obviously clear, but, but it wasn't. Uh, cause Dmitry, you know, you were actually the one who was kind of like, I want to talk about AI because I'm just, basically you weren't happy. You were like, I, I don't like the, I don't like what's being said. It feels like it's misleading.

• 1:59Speaker 00

  Did you go on Twitter by accident? Is that what happened? You went on Twitter, saw all the hype? But wait a second, we need a podcast immediately.

• 2:07Speaker 03

  Yeah, so let me add a little bit to what Casey said there. So actually, I did not set out to have a podcast. I set out. So I get. So I've been working this a long time, like 20 plus years. I have lots of friends who are not programmers or any kind of lawyers, accountants, doctors, whatever, and they're frequently asking me, you know, first of all, can I use this in my job and other things like, how does this go to affect? Like, I have kids in college. Should I stop sending them to college? Right? All of those kinds of questions. So at some point, I thought I should just try to put this stuff together somehow. And first I started writing stuff, but that felt awkward. Then I thought, maybe I'll record something,

• 2:47Speaker 03

  but I'm not really a recording personality. And then Casey and I have been talking about AI on and off for four years. And my suggestion was, what if we record like one session? And I had a list of things that we could talk about. And Casey said, Well, there's so many things here that we could just turn this into a podcast. So that's how we ended up ended up here. But let me add one more thing to that, which is, so I know that there are a lot of people out there who are, you know, I see Casey, I click personalities. I am that kind of personality as well. So part of, part of what I want to do here is to facilitate

• 3:26Speaker 03

  having more Casey out there on stuff where I can be the wingman, right? That Casey understands. So one of the things that I appreciate about appreciate about him quite a bit is that he wants to know what he's talking about before he says something, which, you know, puts him in the top 20% of podcasters at least.

• 3:46Speaker 01

  At least.

• 3:47Speaker 03

  At least.

• 3:47Speaker 00

  At least top 50% of this podcast.

• 3:54Speaker 03

  Wait a second.

• 3:57Speaker 00

  Hey, is that HTTP? Get that out of here. That's not how we order coffee. We order coffee via SSH terminal.shop. Yeah, you want a real experience? You want real coffee? You want awesome subscriptions so you never have to remember again? Oh, you want exclusive blends with exclusive coffee and exclusive content? Then check out Kron. You don't know what SSH is? Well, maybe the coffee is not for you.

• 4:31Speaker 03

  What I hope comes out of this in total is that we get kind of Casey culture-aligned commentary on AI. And I mean, Casey can, I don't want to put words in his mouth, but we see software in a very similar way, right? I'm similarly skeptical about the quality of anything coming out of big tech these days, about questionable ethical business practices and so on. So on general software, not AI software, Casey and I see eye to eye on most things. And so what I'm hoping is that I can be the wingman and give a platform for more Casey culture commentary, specifically on this crazy AI thing that's taking over

• 5:13Speaker 03

  everyone's life, including my own, right? Like, as I, you know, in our inaugural episode, I mentioned that my life used to be much more quiet, and nobody believed AI would work, and we were just quietly doing fun stuff. And in a way, things were better. I mean, it's good that that things are working now, or sort of working. And the sort of working actually is a big part of what I care about, trying to make it better than sort of work. So I don't know, I've gone on long enough, maybe Casey, you should put a bow on it.

• 5:42Speaker 02

  I think you're, I think you're being way too generous to me. I'm the wingman on our podcast, because I don't really, like, I just don't work with AI stuff. So to me, it was just like a good opportunity to like, have somebody on who like, I trusted to give solid perspective on AI. Because like, it's really hard to, you know, the only real way I thought otherwise that I would be able to give any commentary is I'd have to go spend a ton of time with it, right? And I just didn't really want to do that. So it's been great, and I've really enjoyed it. Obviously, Deetra and I have recorded a couple things that, you know, we haven't posted yet. So, but yeah, it's been really great having you on. So, and I should kick it back to Prime and Teach. So like, We don't want to just talk about our podcast here. So like you guys had some AI questions you wanted to talk about.

• 6:26Speaker 02

  Uh, or I don't know. Take, take it wherever you guys want to take it. We are here, we are here at your disposal.

• 6:32Speaker 01

  I did want to say, part of it is to have both of you talk about the podcast because I said, Casey, you should come on and then talk about the podcast with Dimitri so that people can hear about it. I really enjoyed episode one. So we at least wanted to make sure everybody knows that this thing is happening. So don't feel bad about talking about it. That's why, part of the reason that we're doing this today. So that's, that's number one. I really liked it. Um, Prime, I don't know, anything you want to start with? Otherwise I've got a few questions.

• 7:00Speaker 00

  I do want to start with some things, which is Dimitri, can you please, uh, we didn't give you really like an actual qualifying intro other than you're legendary. Uh, could you please define?

• 7:08Speaker 03

  I should downplay that a little bit. Okay.

• 7:10Speaker 02

  They say this about me all the time too, Dimitri.

• 7:12Speaker 00

  Legendary game developer Casey Muratori. So there you go.

• 7:16Speaker 02

  Legendary for what?

• 7:17Speaker 00

  If I talk like Trump as just a morning, everybody's legendary, everybody's the best.

• 7:21Speaker 02

  You've been hearing some very good things about me, Prime. It's like some beautiful things.

• 7:25Speaker 00

  Best game developer.

• 7:26Speaker 02

  Beautiful code.

• 7:27Speaker 01

  Everybody agrees.

• 7:28Speaker 02

  Beautiful American.

• 7:29Speaker 00

  You are the best.

• 7:30Speaker 01

  Every American.

• 7:30Speaker 02

  Amazing code. Totally corrupt, but, but beautiful code.

• 7:34Speaker 00

  Beautiful code.

• 7:35Speaker 02

  Alright, sorry. Keep going.

• 7:37Speaker 03

  Yeah, I was just gonna say, I appreciate the kind words. Like I, I consider myself relatively competent, but I mean, there are like big names in the industry who are, uh, either friends or friends of friends. And it's, uh, useful for me to keep, uh, keep myself calibrated relative. Uh, you know, uh, relative to people with, uh, much more, at least public, uh, uh, public renown. So yeah, I, I don't know. I guess, uh, in terms of introduction, we, uh, I've been doing, um, broadly AI related, uh, research for 20 plus years. I shipped, uh, shipped to many people. My very first custom design AI in 2025 at, uh, at Google. It was one of their first, uh, spam.

• 8:18Speaker 02

  2025?

• 8:19Speaker 03

  Uh, sorry, 20, 2005.

• 8:21Speaker 02

  Yeah, I was gonna say like, that's like 20 years off.

• 8:22Speaker 00

  That's like banana, nano banana. If you're shipping that one. Okay, okay.

• 8:26Speaker 02

  Yeah.

• 8:29Speaker 03

  So anyway, I've been doing this for a long time and seen lots of the ups and downs in the business. And also I studied the history of the business as well. So I know about, you know, the ups and downs for like the preceding 50 years. Like going back to, you know, going back to even the 60s. And so one of the things that really interests me is how this is going to affect other people. Like people that I work with, for example, who are now, I mean, in the first episode, we just talked about the impact on junior engineers. And separately, probably should talk about the impact on senior engineers, right? Because there's, they face a different problem, which is if you're like, let's say you're whatever. Forty five years old now, you've been doing this a long time. You have a good, stable career, making good money.

• 9:15Speaker 03

  And now you're wondering what happens if they like crack the nut and in five years I'm useless. Right? And I know, I know people who are wondering this myself.

• 9:28Speaker 03

  And that's in a specially bad time to be useless, right? If you're like late mid-career, what do I do if I'm 50 years old? And I don't know, like, what do I do next? Right? And there, there is not anything like the, the problems that the junior engineers face where it's, I mean, again, a big problem for the junior engineers, but they have their whole lives ahead of them and they can't, they have time to try to do something else. But if you're 50 years old and don't have, you know, 15 years of building up a new career ahead of you, what do you do? So that's, that's something that I see people worrying about a lot as well.

• 10:04Speaker 03

  Yeah, I don't, I guess maybe I, I, let me not talk, talk too much about myself.

• 10:08Speaker 01

  You can't talk too much. We're used to hanging out with Casey. All right. It's fine.

• 10:13Speaker 01

  We like it when people talk. That's why we bring smart guests on.

• 10:17Speaker 03

  Yeah. So I guess another thing I will add, and this, this connects back to kind of having a Casey style perspective on the industry is that I've seen a lot of how the sausage gets made, both in terms of the technical side, but also, also the business side. And this is something that we, we talk about in later episodes about how, how much can you take certain claims at face value? And how to evaluate which claims can be taken at face value and so on. So what I'm, in the same way that

• 10:52Speaker 03

  Like you can't take whatever Microsoft's claims at face value about improvements in Windows performance.

• 10:57Speaker 01

  Right.

• 10:58Speaker 03

  You can't.

• 10:59Speaker 01

  Well, this is gonna be the best Windows yet. This is gonna be perfect and flawless.

• 11:03Speaker 03

  I was promised.

• 11:04Speaker 01

  Will be safe.

• 11:05Speaker 02

  It was gonna be the last Windows ever as well.

• 11:07Speaker 03

  I was promised the last Windows.

• 11:09Speaker 01

  Well, I did. I they are still working on making it the last Windows ever.

• 11:14Speaker 02

  That's a good point.

• 11:17Speaker 00

  It's the year of Linux desktop is what TJ is trying to say.

• 11:19Speaker 01

  They they put that into the AI and it gave them a plan back of how to make it the last Windows ever and they're executing on that flawlessly.

• 11:28Speaker 02

  Yeah, it is. They're like, we got this thing called Windows 11 and it will ensure that Windows 10 is the very last version of Windows.

• 11:38Speaker 01

  All right.

• 11:38Speaker 02

  And if that doesn't work, we have Windows 12.

• 11:43Speaker 01

  I um, so I I've just got a few topics that I thought would be fun. We can just see where uh like they lead us and what happens. I think there's similarly to on on the episode at least that I've listened to. Um, you start on a topic and there's like 95 different branches that we can go off of. So I I'm not if we don't get to all of them, it's whatever. I I think it uh it'll be fun. But um, one of the things I'm interested in and like it's just hard to get anybody's like unbiased. Well, everyone's got to bias whatever. Just like a more rational take on like this current state of token cost and what that's looking like going forward. I don't know if you have any thoughts, Dimitri, about like, is it gonna

• 12:26Speaker 01

  be that Sam Altman was right and we're gonna get 10x cheaper every year or whatever? I don't know. That's what Twitch chat always tells us.

• 12:33Speaker 00

  That's what Sam Sam has it on the record. He's said it twice now. He said it. He said it twice and made projections into the future, saying it's 100x cheaper. GP2 5.2 high will be uh 100x cheaper in uh two years.

• 12:45Speaker 01

  Okay.

• 12:47Speaker 03

  Uh, so a lot of that is infrastructure development and algorithm development that is trade secrets that like I can't evaluate. Uh, and even like even an OpenAI insider, it would be illegal for them to to evaluate in public, right?

• 13:02Speaker 03

  I. I don't know what they're cooking up there. I mean, they have an extremely talented team. A hundred X cheaper seems hard to believe, but I guess wait and see. So I mean, one of the thing, one of the problems with these, with evaluating claims in this business is that the timing matters as much as the content of the claim. So like, like Musk is a good example, just to take Sam out of this for a moment. Where Musk was saying, you know, we'll have, I mean, we'll have, you know, reusable rockets in, I think he first made the claim in 2005 or something like that. And it took many years before that actually worked.

• 13:43Speaker 03

  Later, you know, when was the first promise of Tesla full self-driving? That was like 2016 that he was saying.

• 13:49Speaker 01

  And then every six months after that.

• 13:53Speaker 03

  So, so I would, I found it useful to try to separate out the content of the claim from the timing of the claim. So I would not be surprised. I would not be surprised if eventually we can get a hundred X cheaper token cost. Whether or not they can do it now, I, that's beyond my knowledge because that's, that's partly that's infrastructure, partly that's like custom hardware, partly that's can you get cheaper electricity? There are so many things that go into the, into the business that it's hard, hard for me to claim one way or another. What I can tell you is that it has been, as I'm sure you've seen, it has been a land rush mentality, right?

• 14:36Speaker 03

  So everyone's building as quickly as they can, whatever they can. Put it out, does it work? Does it barely work? Okay, move on to the next thing. And some of that is, some of that is maybe recklessness, but some of that is just market forces, right? Because the.

• 14:55Speaker 03

  Right now, there are multiple really big players and probably there won't be as many big players in 10 years. And so, given how much money they've all put into this already, they really don't want to be the ones caught out, right? And so, the arms race is rational from a business perspective, whether or not it's producing completely rational engineering artifacts. So, all of that is to say, I'm sure that there is very substantial opportunity for improving efficiency in the current stock. And I don't know if they... So, my biggest question would be, is the internal stock stable enough that you can optimize it now, right?

• 15:40Speaker 03

  Because like, say you spend a year optimizing it to get the token costs down, and then there's whatever the next architectural innovation is, does that invalidate your optimization or not? So, I don't know, right? And so, you will hear me say, I don't know perhaps more than most people talking about AI, just because it's... There's a lot that's unknown even to people who are deep inside these companies about what's going to happen in like 2 or 3 years, right?

• 16:09Speaker 02

  I would add one thing to that, that, you know, it's not adding something as in information, adding something as in sort of like a thing to think about. And that is that it's worth noting that if the costs were really going to get that low that fast, I think I would have expected Google's costs to be very low already. And I know it's a weird thing to say, but if you assume that there's any hardware component... Like, if you think that all 100x is going to come from software, then that seems, okay, maybe that could happen. But if we're counting on a substantial portion of that 100x coming from infrastructure builds,

• 16:52Speaker 02

  it feels to me like Google has kind of been building AI-centric like stuff for quite some time and has gotten their thing that like, their TPUs are very much just like, we built machines whose only purpose is to do this job. As opposed to like, say for example, Nvidia, who's not doing that. Like, Nvidia cards are kind of like still in a weird like hybrid state where only the most... Only the very latest Nvidia's could be said to be focusing on AI really, and even those are still a little bit hybrid feeling to me. So I could imagine if someone said, well, you know, if all we had was Nvidia to look at, maybe you could believe that like, you know, there's a very long lead time on hardware.

• 17:36Speaker 02

  So, you know, we don't know what they, you know, when they shifted probably four or five years ago to going like, oh, my God, AI is going to be the biggest thing. We need to completely redesign everything to just focus on that. That stuff will only be, you know, we'll only be seeing the end of that pipeline, you know, now or something like that. Right? So I could see that, but I feel like Google's kind of, I mean, am I wrong about this, Peter? I feel like Google's been doing this for a long time. If there was a huge, if there was huge gains to be had by doing just AI hardware, I would have thought they'd have them already. Is that, am I way off base there?

• 18:08Speaker 03

  I'm not sure they don't, right?

• 18:09Speaker 02

  Okay, okay.

• 18:10Speaker 03

  The first time I heard about TPU, I think the first time I heard that they were starting to work on it was like 2014 or something. So that's just when I heard about it, right? I'm not a Google insider, so I'm sure, like, knowing how Google works, I'm sure that they were talking about that like three years before I heard about it in public, right? But when I heard, when I first heard about TPU development was somewhere around 2014.

• 18:36Speaker 02

  Yeah.

• 18:37Speaker 03

  So I guess I have not been studying the, whatever internal economics reports Google puts out. It's possible that they are already substantially cheaper than.

• 18:49Speaker 02

  I would think.

• 18:50Speaker 03

  On, on operating costs substantially cheaper than OpenAI. I don't know. And but I mean, this is something that's a common folk belief in the industry, which is Google is sort of the quiet monster in the business because like they, if you compare them for a moment to say OpenAI, they have had, they have been infrastructure leaders forever. They have been AI leaders forever. Unlike OpenAI, they have, they have, I'm trying not to say the word surveillance, but I'm just going to say surveillance. On the entire internet, right? So they have just a constant flow of potentially trainable information and, you know, XAI has.

• 19:33Speaker 03

  Has that flow that that is their own proprietary flow of data.

• 19:39Speaker 03

  So many people have have this feeling of Google was kind of slowed on the on the product side. I emphasize on the product side with like chat, chat L L M products. But there is many people have this feeling of possibly Google is just going to quietly leverage all those advantages that nobody else has. And like X A I is the only one that's sort of sort of close in and having that capability. It's interesting to note that as far as I've seen in public X A I, they're merging with Starlink, they're talking about, sorry, with.

• 20:17Speaker 02

  SpaceX, yeah.

• 20:18Speaker 03

  SpaceX. And they're talking now about orbital data centers. And something that I thought was interesting there was that the designs that they've talked about are G P U based, not T P U based. And I don't know if that's because they don't think they can build it up as well as Google did, or they don't think they can license it. So I don't, I don't know, right? But the thing I will point out is that the designs I've seen, I mean, I guess I haven't looked, looked in like three months, but the designs I've seen were estimates based on, you know, Nvidia style G P U's and not T P U's. So they must know something because this is, this is the kind of thing that they do, right?

• 20:57Speaker 03

  The big, the biggest competence advantage that I would put in the kind of Musk category of companies is the relentless execution on, on building and optimizing and streamlining physical stuff. That's something that they've been doing really well for a very long time. So if, anyway, that caught my eye, that the designs I saw were based on G P U's and not T P U's. And I do know that they're working on their own, their own A I chips. I don't, I don't know that much about how far they are there. But it's interesting that, that when they were talking about the orbital data centers designs, they were talking about conventional G P U's as we understand them.

• 21:40Speaker 01

  I gotta say orbital data center is like the coolest sounding thing to build.

• 21:45Speaker 02

  Yes.

• 21:45Speaker 01

  Like it seems really not practical. I get like I get there saying, oh, we're gonna have robots do it and it'll be outer space and it's really cool. But I got, I mean, you, I just feel like everyone's gotta admit orbital data center is probably the coolest thing to say you could work at in software development, so.

• 22:03Speaker 02

  Yeah, I think like, yeah, based on what I've seen for orbital data centers, it sounds like it's, it is either much cooler or much less cool than what you're thinking about, depending, depending on your perspective, right? So, excuse me. If you're imagining like a giant building in space, like,

• 22:27Speaker 01

  Yeah.

• 22:27Speaker 02

  Like it, it sounds like the kind of more leading designs that are like more plausible. They're more like Starlink. They're more like satellite clusters where you just have lots of little things that talk to each other over light links, basically, for high-speed communication.

• 22:47Speaker 03

  Well, and giant, giant radiators, right?

• 22:50Speaker 02

  And huge, yep.

• 22:51Speaker 03

  It's, it's almost all radiator and then there's a little like nub in the center that contains, that contains the GPUs, right?

• 22:58Speaker 02

  Yeah.

• 22:59Speaker 01

  That doesn't sound as cool as what I had in my head of a big skyscraper in outer space where we've got racks of GPUs and you can walk around in it and it's like really cool. But that's okay because when you tell your parents that you work at an orbital data center, they won't know, so it's fine.

• 23:16Speaker 00

  That's what they imagine is that.

• 23:18Speaker 01

  Yeah, I say it's exactly like Star Wars, mom and dad. Trust me. Trust me.

• 23:24Speaker 02

  Unfortunately, like heat is just very,

• 23:28Speaker 02

  I guess the, as the kids say, say problematic in space. Like you don't have anywhere to put it. Like it's very hard to get rid of heat in space, so this is a problem. As Demetri was saying, you, you end up having to have a lot of surface area per chip, like per, per heat generating Nvidia, like GB200 or whatever. I mean, there won't be a GB200 by the time they get these things launched, but the, you know.

• 23:54Speaker 01

  That's the thing I didn't, I didn't get, I don't, what is the advantage then? Cause in, in like, I get that it feels like if you talk to like a regular person about putting it in outer space, they're like, well, it's cold in outer space. So that's going to be really good for GPUs. But it's the opposite, I think, right? I mean, I, so I don't get.

• 24:13Speaker 00

  It's not that it's not cold in outer space. Cold is the lack of available, you know, like not having energy. There's just, there's no density. So you have nothing you can.

• 24:22Speaker 01

  Yeah. I meant like more like they said, cooling would be super easy. I feel like that's like the normy thing. If you say put something out, it's like, it'll be cold. Sick. It's like a huge refrigerator, bro. But that's not how heat works. I like, so I get that part. So then what is the advantage? Why this is, we also don't have to go way down this route, but I have been wondering this myself. So what, like, why do they want to put it in outer space?

• 24:44Speaker 00

  Incredible investment TJ. Like the amount of investments that are coming in will be.

• 24:48Speaker 01

  The TAM, the TAM for outer space is big. Think about how many data centers we can put in outer space.

• 24:53Speaker 03

  Well, it's, so it's free power and difficult, but free cooling, right? So if you, if you can make the physics work, and I don't, I don't, they have really, really good like thermal people at, and you can imagine they have very good thermal people at, uh, at SpaceX. So, uh, I, I assume that they have done simulations that, that suggested them that this can be made viable. Um, but yeah, so it's free power and also like more free power than you would get for the same panel on earth. Because there's no atmosphere eating up your atmosphere or weather for that matter.

• 25:25Speaker 01

  Yeah. No clouds.

• 25:26Speaker 03

  Right. So free power and, uh, tricky, but free cooling.

• 25:33Speaker 01

  Gotcha. So it's like when you build a really complicated thing, but then it's passive in a video game. I understand. This is, this mechanic makes sense to me.

• 25:40Speaker 03

  And maybe one thing I would add, uh, this, so this is entirely business strategy speculation. Um, so whatever, like take, like pour a big.

• 25:49Speaker 01

  It's financial advice. Got it.

• 25:50Speaker 03

  It's exactly right.

• 25:51Speaker 00

  You're investing right now.

• 25:53Speaker 03

  If it works, if it works and you are.

• 25:58Speaker 03

  Musk's AI team and you just get to launch your AI into space and everyone everyone else is like fighting local governments and can I build a hydro plant here? Oh, how much do I have to pay you to right?

• 26:12Speaker 01

  Yeah.

• 26:12Speaker 03

  And you'll just be like, we're going to space, right? Like you losers can hang out here. We're going to space. And by the way, if you want to go to space, you have to come through me, right?

• 26:19Speaker 01

  Yeah, yeah.

• 26:19Speaker 00

  Yeah, he pretty much owns the the passage to space. So it's

• 26:23Speaker 01

  Yeah.

• 26:23Speaker 00

  It's a pretty synergistic business.

• 26:24Speaker 01

  They can't ask Katy Perry? She's been out of space.

• 26:27Speaker 02

  Well, and also like it's pretty trivial for like when you look at the projections for these sorts of things. It's all about launch cost, like whether or not it makes sense to put a data center in space, a quote unquote data center in space. It's like, here is the launch cost, like at this launch cost, we think we could do it because and that's based on like the failure rate of the thing, how you know, long it's expected to be able to be up there, you know, all those sorts of of things. And so at the end of the day, if you know, if you look at somewhere like SpaceX and they're like, well, for us, we could get our launch cost down to fifty dollars a kilogram or whatever, you know, the magic number is.

• 27:07Speaker 02

  We just charge everyone else seventy-five dollars a kilogram and then it's it's not worth it for them to put it in space or theirs will always be worse than ours, right? It's a very good position to be in and a strangely profitable bet for SpaceX. If it turns out that these are actually useful in the future, so.

• 27:24Speaker 00

  So I think we should probably attempt to get a little bit more on on a more practical approach to AI. I do think orbital data centers does sound amazing.

• 27:32Speaker 02

  You don't want the title of this video to be orbital data centers or like AI in space, Brian? That's good. How many clicks is that going to generate? Come on, man?

• 27:40Speaker 03

  AI in space.

• 27:41Speaker 00

  AI in space.

• 27:42Speaker 03

  That's my that's my rock opera I'm writing. That's crazy. How did you know?

• 27:47Speaker 02

  Because I am also writing a rock opera called AI in Space, as it turns out.

• 27:51Speaker 01

  Oh, sick we could collab.

• 27:53Speaker 02

  Yep.

• 27:54Speaker 00

  That's not gonna happen. Uh, he's just he's just gonna take it all from you. Okay, so I guess we should.

• 28:01Speaker 00

  We should probably talk. I think the number, I get a lot of concerns from people and one of the most frequent questions I've been getting lately is, is my future just reviewing code?

• 28:14Speaker 03

  Yeah, so quite possible. Um, let me, let me try to be measured in what I like, how likely I think that is. Um, so one, one thing that I've been,

• 28:26Speaker 03

  I, I have discovered in my own work and that I've been saying publicly for a while now is,

• 28:31Speaker 03

  so I try to work on like repeatable and reproducible AI results. So the bucket term I use for that is, has been reliable AI, but it turns out that there's a company called reliable AI.

• 28:44Speaker 03

  So anyway, the thing that I, I, I think you can do right now, like completely hands off and not have to review anything. Right. So this is what I mean by reliable, right? That like, if I ask you, teach to whatever, go implement,

• 28:57Speaker 03

  like download this thing from this HTTP endpoint and like save it into the database and give me a dashboard that, whatever calculates the averages of some things, right? I can just tell you that and expect the result and it will work and I don't have to talk to you about it again. Right. So that's what I mean in this completely hands off style. Right now, I think the limit of that is somewhere around a couple of thousand lines of like relatively standard junior level code. And I want to emphasize, because some people, some people have justifiably pushed back on this a bit. I'm not saying you can't do more by having oversight and doing multiple tries and having algorithm test suites. I'm not saying you can't do more. Right now, what I'm talking about is what's the limit of what you can do hands off? And you can mostly just trust that it happens.

• 29:37Speaker 03

  I think, I think at a, at a minimum, we are going to go through a review heavy phase because the, the businesses are, as, as I'm sure you know, the businesses are trying to shove this into everyone's workflow, whether they like it or not, right? And I get lots of people, lots of people, even in the AI business, you tell me like, I hate how much they're trying to push us to use these things. Right. I just, I just want to do my job, uh, but like they're monitoring my token usage, right?

• 30:07Speaker 00

  Anecdotally too, not just like literally, like I have friends who are like, we have to use this tool. Part of my KPIs like we use, we have to use Claude code only. That's and.

• 30:20Speaker 01

  My manager has a dashboard with my token count for the month. And it is a thing we talk about and review. Not even like, oh, you can use whatever one you want. We just want to see you guys experiment. They're like, you have to use call code, you have to do this. Yeah, it's crazy.

• 30:34Speaker 00

  Yeah, think about Amazon Kira. That's a lot of people are talking about that right now with the whole Amazon accidentally having several Sev ones.

• 30:41Speaker 01

  Yeah, they're like, you have to use our stuff to take ourselves down. If anyone's gonna bring it down, it's gonna be me. Okay?

• 30:46Speaker 02

  We want to make sure we are, but we want to make sure our site goes down and our AI looks bad at the same time. We don't want like someone else's AI to look bad.

• 30:55Speaker 01

  No, that would be mean. Okay, if it's gonna, if it's gonna go down because of AI, it's our AI. They're putting the I in AI, okay?

• 31:01Speaker 02

  There you go. Very good. Yes.

• 31:05Speaker 03

  So yeah, Prime, on that point, I think it's very likely that we will go through a review-heavy phase. I think, I think that at some point, like, the workers will object to this enough that we're going to have to find something, something more acceptable, right? Because I don't know if you've tried it, but if you're just like reviewing stuff like, you know, Claude dumps another thing on you every, you know, five minutes, you're like, okay, I have to review this and approve and merge, whatever. Or, I mean, you can just Yolo, right? And, but, but we've seen what happens if you just Yolo. So I do think we will, at a minimum, go through a reviewing, mostly reviewing phase.

• 31:47Speaker 03

  And I think people are not going to like it. That's my expectation. I don't know, I don't know how, I don't see what the alternative is right now, because, so the either, the two possibilities I see right now are, like, they're going to be monitoring your token count. And so you need to be consuming and generating tokens. And then that has to go, that has to get linked, which, you know, in some places it actually link the tokens to PRs, right? And so you need to be generating lots of PRs, you need to be consuming lots of tokens. How can you do that other than just generating many, many PRs with AI and reviewing?

• 32:29Speaker 03

  And like hoping that you're not taking down, you know, taking down fraud by, by missing something in your review, right? So I, I don't know how we get out of that other than, uh, at some point, the business side says, okay, like we can cool it, right? We're going to, um, we're going to stop monitoring your token use, which I mean, I, I personally feel like that's not that different from a desktop monitor or like a keyboard monitor or something. It feels very invasive to me like, hey, you know, I, I understand you're asking me. I think it's fair to ask me, hey, can you use this tool? Can you try to do better work? I think that that's fair, right? Like I'm ultimately you're like, you're being paid to do something for the business. I think it's fair for them to ask, hey, we'd, we'd like to be using these tools and we think you can do whatever, like 20% more work if you can, if you use this, I think that's fair.

• 33:14Speaker 03

  I think the micro, micro tracking feels worse than the past and, um,

• 33:23Speaker 00

  It's really easy to game too, right? You just like sequentially look at every single file and it's just going to be like dang, dang, dang. I'm crushing the tokens.

• 33:32Speaker 03

  I know people who are like at big techs who are working on stuff and they have to do what exactly what you're saying. And they're like, I, I like, I do, I, I do this just to keep up appearances for my AI use. And, you know, by the end of like my output changes maybe 10%, right?

• 33:51Speaker 01

  I do like how it's literally just setting money on fire and they're like, this makes me look fast. Cause so that actually before we got distracted on the orbital data centers, which I'll repeat coolest name ever.

• 34:02Speaker 00

  Cool.

• 34:04Speaker 01

  I, uh, was, I was interested in, you know, some of your thoughts about sort of the tokenomics side of things. Because right now it feels like people are burning a bunch of money, trying stuff out and exploring and willing to just be like, oh yeah, you just spent $5,000 this month. Whereas before, like you couldn't get like a $45 like online course approved. And they're like, oh, but yeah, yeah, $5,000 tokens for nothing. Yes, we're totally down for that. Do that every month. Cause I, I was interested to if, you know, Uh, like if we're gonna see a big, you know, or your thoughts on if we're gonna see a big push on like generating less or like more focus on like, we're gonna use more tools to check what's being generated.

• 34:45Speaker 01

  You know, because at some point, you know, Claude, Claude just released their thing about code review. And they're like, yeah, it usually is like 15 or 25 bucks a review. And you're like, well, that adds up kind of fast, especially at the rate people are saying, I'm shipping 10,000 lines of code a day. Or I made a 30, 300,000 line Ruby on Rails application for my blog. That's Gary Tan, by the way, in case you could see that tweet. Okay, um, hey, he's boiling a lake and then he's gonna boil the ocean. All right, that's what he told us. Yep. I, side note, I cannot tell if he's the most genius rage baiter of all time. But we can circle back to that on a different episode. Yeah.

• 35:27Speaker 01

  Yeah, so, cause I'm, I'm interested in, in sort of that angle because I do find like some tasks I can get done like a lot faster with letting agents work on it. Or like agent spin on something like forever. It has a really clear outcome. There's some stuff. I already have a bunch of patterns in my code base. Spin, but I'm like, is, is everyone just gonna be chill forever with me spending $500 of tokens overnight on this? That doesn't seem like what a business would like. I don't think we're gonna get $500 of value back from this feature. So I don't know if you have any thoughts like in that vertical or? Um, yeah.

• 36:01Speaker 03

  So this is speculation?

• 36:03Speaker 01

  Yeah, yeah, of course.

• 36:04Speaker 03

  Speculation. A lot of this is, um, like principal agent problems for the business. It's like the, so there are for sure, uh, like CEOs and like one step down from CEOs who one way or another.

• 36:21Speaker 03

  Their, uh, their personal benefit is tied to claiming that they did a lot with AI.

• 36:27Speaker 01

  Yes, true. Yeah.

• 36:29Speaker 03

  And as you know, like in any big organization, you never just evaluate something for whether it's good or not. It has to be evaluated through some KPI, right? So.

• 36:39Speaker 01

  Yes.

• 36:40Speaker 03

  There are people, I'm sure, like, I haven't seen this personally, but I'm sure that something close to this exists that there is someone with many millions of dollars worth of bonuses tied up to, can I get our token usage to double this year? And can I get our PRs to increase by 20% as attributed to that token increase? Right?

• 37:00Speaker 01

  Right.

• 37:00Speaker 03

  Like extremely bureaucratic thinking about using this new technology, right? So I'm sure that there are many people like that. And so those, to those people, they're not, they're not spending their own money, right? They're spending the company's money.

• 37:13Speaker 01

  Right.

• 37:13Speaker 03

  They're telling, they're telling you to spend the company's money to do something that makes them have to go up that gets them a bonus. Right?

• 37:18Speaker 01

  Yeah.

• 37:19Speaker 03

  So I don't know how long that's going to last, but there's certainly right now a very large premium at multiple levels of the, kind of the business stack, where people are like, you know, why, why isn't your token usage doubled? Right?

• 37:31Speaker 01

  Right, yes.

• 37:33Speaker 03

  To some people, to some people, that sounds like a joke. I have friends who literally, they say, my, my boss came and asked me, why hasn't my token use, usage doubled? Right? But you only used $300 of Claude last, uh, last month.

• 37:43Speaker 00

  Honey, you barely touched your Claude last month. What's going on?

• 37:47Speaker 01

  Is something wrong, sweetheart?

• 37:50Speaker 00

  Okay, so I do actually want to follow up on that because this is the, you know, this was one of the big things that has been going around. Is this Amazon Kiro thing taking down everything? And now they're saying, hey, we're gonna make it so that juniors and mid-level people who use generative AI must have a senior sign off on this.

• 38:04Speaker 01

  Can I do a quick question on that as well, Prime? Which is, was there a policy before seniors didn't have to review juniors' code? Just in general?

• 38:12Speaker 00

  I assume, I assume it's like a lot of companies, which is that a, a junior could have a mid-level person review the code and say, hey, this is not really good. Like, not every change needs to have, you know, the same, because you, you effectively will exhaust and lose your senior population if they have to review every single PR. And so kind of.

• 38:27Speaker 01

  That makes sense.

• 38:28Speaker 00

  So excluding the personnel problem that will likely develop from this with Amazon, is this like the first sign of people realizing that token measurement isn't necessarily the best metric? Because I assume that's what's hurting Amazon is that they really push super hard as token metric is the greatest thing that has ever existed and you must only push on this one thing? And now they're feeling some of the effects of maybe moving too fast? Is there a world that's going to exist where people are going, okay, instead of trying to double metrics, maybe we should double some other thing? Say, I don't know, uptime? Maybe like uptime could be the thing that we're like, you know, that we're valuing? And then that can be, that could be it? Like, is this an actual, like, path forward?

• 39:10Speaker 00

  Or are we, I don't know, from your perspective, are we just gonna see continued push on double your token usage? Double your token usage? Because they both sound super appealing, I guess, from my purely theoretical point of view of like, oh, more features? We could, no, we could get all the features? Or, no, let's be stable?

• 39:27Speaker 03

  Again, I think that, so, as we, as we discussed with Casey, and Casey, you should, you should jump in on, on this part.

• 39:35Speaker 03

  Like, we've seen these cycles of, like, everything has to be, you know, like, 25 years ago, everything had to be online, and then everything had to be, uh, Web 2.0, and then everything had to be, uh, like, social, local, mobile app, and then everything had to be crypto, right? And that, right? So, um, we are in that phase absolutely right now, where separate from any utility that the technology is offering, there's just this social mania of, everything has to be this right now. I don't know when that fever will break. I, I think certainly, events like the Amazon, um, Amazon event will, will help with that. And I, I do think that at some point, people, someone is going to say, okay, look, um, we just can't be burning this kind of money all the time, and also, like, setting our

• 40:20Speaker 03

  infrastructure on fire, and driving our engineers crazy. At some point, at some point, we should actually get a benefit from this instead of hurting ourselves.

• 40:30Speaker 00

  You could only pick two points on that triangle. Drive engineers crazy, burn a lot of money, uptime. You could have picked two of those points.

• 40:36Speaker 03

  Yeah, true.

• 40:39Speaker 03

  But, uh, I think... I think this could last for years, and the reason I say it could last for years, I know people will not like that. Uh, I think the reason this can last for years is it's easy to underestimate. Um, like on, you know, you guys are like people who watch this, uh, you know, watch the stream. How far, how far up the, the like power law curve of, uh, early adopter you are. And

• 41:05Speaker 02

  So true.

• 41:06Speaker 03

  Just be lots of people all the time who still conceptualize AI as like it's a better search engine, right? And I, I mean, it's, uh, it's easy to forget that actually the vast majority of people don't know much about this and aren't really trying to use it. And, um, so all those people somehow will have to be carried through the, uh, the fever swamp. Um, and I don't know, like, I think that could take years.

• 41:33Speaker 02

  I would agree with that, uh, for and add the sort of the chaser, which I think we did talk about on that first episode of the podcast, which was, I don't see it as mattering whether it takes down prod all the time either is the problem because like, uh, at least my experience for the past 20 years has been, it doesn't matter how bad the practice is. If it's just something that is in the zeitgeist, then people do it and you can show them clearly, like you can literally demonstrate, look, if you had done it this way, this is how much better it would be. They don't care because the best practices is that you do it this other way. The best practice is you use Python, then we're using Python or whatever it is. And you're like, look, if you'd just written it this way, it's a hundred times faster. And you're like, we don't care.

• 42:17Speaker 02

  That's how this industry has operated. And so it would be very weird to think that in the special case of AI, that anyone would care one way or another, whether it even was better, right? So you can almost take your, take your guesses about how, uh, good AI will be in practice about generating code in the first place. You could even put that aside. I think the fact that it has this much momentum is enough to know that this will be here for, uh, a long time. The current way we're doing things, even if it never gets any better than it is right now. Even if it's exactly as good as it is right now, no improvements, literally at all. I, I don't think that would change the outcome. Honestly, I really don't.

• 43:00Speaker 01

  Well, there's like a trillion dollars invested in the two, right? So they're like, well, hopefully. Exactly. Even if, even, and it's, I mean, it's not a really even sunk cost fallacy. It's just like literally sunk cost truthacy, which is like, we really, we really need this to work, guys, or we're really underwater, right? It's not like.

• 43:18Speaker 02

  Yeah. So it will become the workflow. I think that's like inevitable. And like, I wish that, I wish that we could say like, well, if the AIs don't improve substantially, then people would like rethink the, I don't, I don't think that's true. Like, I think whether or not they're able to push the quality up, I mean, hopefully they are, because, you know, everyone is putting a lot of money into pushing the quality of the AI. So hopefully they do get better, but even if they don't, I don't think it's going to matter personally.

• 43:49Speaker 00

  So I actually have a bit of a follow up to that one, Casey, and I'm, no offense to me, I'm actually very curious on Casey's thought on this one. In 2024, GDC started doing this survey asking about the perceptions of AI inside of the game development space. And in 2024, 18% of the developers held a negative view on Gen AI. In 2025, 30% of the developers at GDC had a negative view on AI. In 2026, it's now at 52% have a negative view, and only 7% have a positive view. Is there, is, is this like a special, unique thing to games? Because games does contain a bit more art than the average programming, shall we say? Is this like a special games thing?

• 44:31Speaker 00

  Or is this actually a momentum change that people are feeling due to, hey, you must use this, this is the greatest thing ever, you have to use it to therefore, and then you start using, and you're like, okay, well, it's great here, it's bad, you know? And you, you feel this giant disconnect from Twitter. Because I have my own opinions that are largely formed because of how much I hate what Twitter has to say.

• 44:48Speaker 02

  I mean, obviously, I can't speak for people who are taking that survey. I mean, they know what they were thinking when they checked the boxes or, or pushed whatever they pushed. But I, you know, I think, as I've said before, I think it's very difficult to separate out people's opinions of Gen AI, the technology, from Gen AI, the people and the companies. And I think when we look at things like negative surveys, I, I will say, I'm right there with them. I, I have nothing but disdain for this sort of.

• 45:23Speaker 02

  Current moment, but that's not based on an objective look at generative AI and where I think it's going. It's based more on the behavior, the legal behavior, the attitude. It's based on, you know, like many things, when, you know, we're humans, we make decisions largely based on what we think the intentions are of the people who are in charge of things. Because at the end of the day, like that's, you know, if we have a really good feeling about someone who's running something, we are less concerned about that thing than if we have a really bad feeling about it, right?

• 46:02Speaker 02

  And so I would suspect that a lot of it comes from there. And that, you know, especially like you said, there's a lot of more, there's more artistry in games. There's a lot more people making art assets, a lot more people making music, making sound effects, making narratives. And, you know, the behavior with respect to that of the AI companies has been utterly deplorable, right? I mean, I've said this many, many times on Twitter, you know, it's a pure disdain for the law, no concern about what they were doing. They just decided, they basically just made a decision, we're just going to do what we're going to do and we'll deal with the lawsuits later. Was clearly what they decided. I mean, I don't, I don't have evidence that they literally decided that in a meeting, but their external behavior makes that clear. If they were, if they had been at all concerned about the, you know, whether they were breaking the law,

• 46:47Speaker 02

  they would have done a lot of things first that they didn't do.

• 46:50Speaker 00

  By the way, Casey, what's it called? The Facebook actually was caught with emails saying, this is illegal, right? Yes, it is. Don't do it on the company computer, idiot.

• 47:01Speaker 02

  You know, multiple of them, like now, if you look in their in-court documents, multiple of these AI companies are on the record as having known they stole things. Not, not about fair use, like just literally pirated.

• 47:13Speaker 01

  They weren't like, this is transformative.

• 47:15Speaker 02

  No, no, there's none of that. There's like, there's like, we, we are literally taking an illicit step to acquire data. And we know there's multiple companies that are now in court records, like they have that evidence, right? So. Yeah, so I think-

• 47:29Speaker 01

  Well, we also know like GitHub could have just filtered out non-permissively licensed stuff to train Copilot, for example. Like, that's the easiest one in... That's one of the ones where it's easiest, like, you own the search thing that you're doing to find the code. You could have clicked your own check... It's not like, "Oh, we just crawled the internet and we got back 10 million things."

• 47:50Speaker 02

  Yeah, yeah. Like, one of the primary things that these LLMs are good at is understanding language. They all now are at the point where they could analyze their own training data set and assign a probability of legality to each document. That could be done today. For all I know, they have done this, right?

• 48:09Speaker 01

  They would all say 100% legal for my company, dude.

• 48:14Speaker 00

  As long as you don't distill it from us, it's legal, okay? But if you trick it from us...

• 48:18Speaker 02

  So I think that's, you know, from an artist's perspective, you can see why this is a big deal. Because it's not just, you know, it's not just looking at something and saying, "I'm afraid that this thing is going to take my job," or "I don't like using this thing because it doesn't feel like art to me when I just..." It feels like management, because I think that's another thing that, you know, we haven't talked about that much. But an artist wants to directly manipulate the thing that they're doing sometimes. You tell them, "Oh, well, you know, now you don't do that. You just ask it to make this thing for you." That doesn't feel like art to a lot of artists. Some artists are fine with that. There's, you know, there's technical artists and there's non-technical artists. And a technical artist might be more used to that,

• 48:59Speaker 02

  because they're used to kind of going through this, like, technology-intermediated process to produce what they're doing. But a non-technical artist, they're in that business because they like the direct tactile work of making art. And so, not only is it bad in that sense, where they don't like it because they're like, "I don't really want to use this and I feel like it's threatening my job." That's obviously bad. But then you add on top of that, "Oh, and by the way, it was your own artwork that they used to take your job from you without paying you anything extra and without asking you first." I mean, how do you not check the negative... Like, it's obvious that that's just bad.

• 49:35Speaker 01

  And they're not even nice about... Also, the CEOs get there and they're... "Hey, guys, guess what? Guess what? We're putting all of white-collar workers out of work. Am I right, boys?"

• 49:48Speaker 00

  Whoa, whoa, whoa, TJ.

• 49:49Speaker 02

  Yeah.

• 49:50Speaker 00

  TJ, you are... To be fair, TJ, that was a bit of a misinterpretation, okay? What actually happens is Dario first makes a really painful face and goes... I'm so sorry, but we're gonna have to have some economic struggle, okay? We're just gonna have to lose some jobs, okay? Some are gonna have to go now.

• 50:07Speaker 02

  And when I say "we," I mean "you," because I'm not interested in struggling at all.

• 50:12Speaker 00

  Okay, I'm gonna buy the cookies, you're a broke boy.

• 50:15Speaker 02

  Yeah, I mean, what I would, I have, I have proposed before, I was like, they always say, like, we're gonna have universal basic income. My thing is like, look, if everyone at AI companies demonstrate that, all of you go on UBI first.

• 50:32Speaker 02

  Like, all of you go on a fixed low salary first, because if that's what you believe the future is, let's see it. Let's see you guys all be happy with that first, and then sell it to the public, right? But they're like, no, actually, we would like all the really high salaries for us, and everyone else can have the UBI. Like, it's just, it keeps getting worse every time, you know, they, they step into these things. So, so, I don't know, my opinion on that is like, it's obvious why someone at GDC would check that box. I think that's probably gonna be true for a lot of workers, not just game developers. It's just that game developers are, you know, more exposed to this technology currently, because they tend to be more technologically savvy than, say, someone working at an accounting firm randomly right now,

• 51:12Speaker 02

  who maybe hasn't really seen this stuff all that much, their firm hasn't started adopting it, whatever, you know? The average worker may not have been encountering AI to the degree that a game developer has. They're, they're further ahead on that curve. That would be my answer, Prime. Dimitri might have a different take on this, but that's, that's what I would say.

• 51:30Speaker 03

  I completely agree. So, the two, two points I would pull out, starting from the most recent one, is,

• 51:37Speaker 03

  the, like, the accounting world has not been dragged through this yet, and they will. The HR world, so I happen to know someone who works on apps for, for HR surveys and stuff like that. Like, we've all seen these very tedious HR surveys right there. But all those were made by, made by someone who had a job, which was, I guess, HR survey designer. That's probably not surviving, at least not in the current form. And they don't, like, that world doesn't even know that this is happening yet, right? So, all those other industries, like, the reason they're not yelling yet is because they just haven't been under the gun yet, right?

• 52:16Speaker 03

  And then the other thing was, I think Casey made this really good point about... If you are, if you're the kind of, if your position in the art production pipeline is more editorial and composition, so you're not, you're not making the assets yourself, you are, you have artists under you who are making the assets and then you're doing editorial work or composition or something like, so someone's, I don't know if art director is exactly the right word, but this is, this is parallel to, you know, the, the people in tech right now that I think see the biggest buff, boost from, from what's happening right now is a technically trained project manager or product manager.

• 52:56Speaker 03

  And I know a couple of, of those guys who are talented enough to review their own code and understand when something is obviously stupid. And they seem to be doing plausibly good work. And so whereas they used to be managing three or four junior engineers, they just manage 20 clods or something, right? So anyway, the, the, this idea of if you're, if your position in the pipeline is editing, assembling, composing,

• 53:27Speaker 03

  like, like the big picture structure of somebody else's work, I think those are the people right now who are least disrupted and most, most benefited. Prime, you look like you're about to say.

• 53:41Speaker 02

  I'm waiting for Prime to unleash here. There was a stroke.

• 53:44Speaker 00

  I'm considering, I'm considering his position, which is that I'm just playing through my head, like, the biggest thing that I really enjoyed doing was not in fact managing juniors, but in fact, writing the code. And I've also had some of the hardest transitions in an AI world because I still just like writing the code and I, I find it less, you know, so I'm like, oh yeah, okay. I, I see myself in what you're saying is that there's a bunch of people and now this is where things, this is where the, I call the, I call it the classical bullshit thing, which is that people say they're good at this, but I don't think you can review code and actually be good at it beyond a certain amount of lines per day. So it's like, if you, if you're reviewing more than like 500 lines of code a day, I just don't, I just don't believe you.

• 54:26Speaker 00

  Like at some point you, there's like some line that exists somewhere where you're just like. Oh no, I really have to think about this.

• 54:32Speaker 01

  It's higher than 500.

• 54:33Speaker 00

  Okay, a thousand, right? I mean, but people like, I'm for, I could.

• 54:38Speaker 02

  I think what TJ is trying to say is like, he can do, you know, a lot more lines of code than average. Is what I think TJ is trying to say.

• 54:46Speaker 00

  There's a, there's a study.

• 54:47Speaker 02

  Maybe it's 500 for you, Prime.

• 54:49Speaker 00

  It is 500 for me.

• 54:51Speaker 02

  For TJ, it's like 10, 20,000.

• 54:54Speaker 01

  Yeah.

• 54:55Speaker 02

  No problem.

• 54:55Speaker 01

  10, 20,000, there we go, that's closer.

• 54:57Speaker 02

  No problem.

• 54:58Speaker 00

  That's why we call, that's why we call them, you know, JT and TJ. They're, they're, they're just mirrors of each other, okay?

• 55:04Speaker 02

  He reviews code, by the way.

• 55:06Speaker 00

  By the way, JT's Gary Tan, if you're wondering, even though it's JT. Uh, but, uh.

• 55:10Speaker 01

  Oh, that was a stretch.

• 55:12Speaker 02

  Yeah, he managed to get a new power cable from the Best Buy, how's he doing? Did he, uh, did he get in line there?

• 55:17Speaker 00

  I think he got his USBs figured out.

• 55:18Speaker 02

  Was he able to get that power, that MacBook powered up? Cause the whole future of civilization is riding on Gary, and if he doesn't get that power cable, I think we're all in a lot of trouble.

• 55:26Speaker 00

  If Gary's list, don't keep listing.

• 55:28Speaker 02

  Yeah, I don't know if you guys ever saw, there was a fantastic movie starring Ice Cube called War of the Worlds that came out recently. I don't know if any of you saw this movie?

• 55:37Speaker 01

  I, I watched it in five separate small clips.

• 55:40Speaker 02

  Alright, well, as, as you know, you think I'm joking, but as you know, the fate of humanity itself can very well hinge on one delivery of an Amazon thumb drive. So, I don't think what I just laid out is all that far-fetched. Just go watch the movie if you don't believe me, it's a documentary.

• 55:58Speaker 01

  That's what I heard, too.

• 55:59Speaker 02

  Yeah.

• 56:00Speaker 00

  Uh, I just am super proud that Ice Cube was like, give me that bag, I don't care what's about to come out the other day, just give me the bag. I, you know, I, I, oh, more power to that guy, but what I was gonna say.

• 56:09Speaker 01

  How many people do you think they asked before Ice Cube, who they like read the script and they're like, no, I can't do this, bro, I cannot do this?

• 56:18Speaker 02

  What are you talking about? No, in the meeting, they were like, do you think we can get Ice Cube for this? Nah, he's never gonna do it, just ask, what's the worst gonna happen?

• 56:23Speaker 01

  Just ask.

• 56:24Speaker 02

  And he was like, yes, I'll do it, they were like, oh my god, thank god we didn't have to go to Daniel Day-Lewis.

• 56:31Speaker 00

  Alright, I believe I have generally forgot what I was going to say, but I will just at least-

• 56:37Speaker 02

  You were saying there's a limit on code review. You're like, you're saying you don't believe, you're calling bullshit is what you're doing.

• 56:42Speaker 00

  Okay, there's, I forget where the professor was, I forget her name, I think it's Susan something or another. I just read it just two days ago. She's coming up with this term called-

• 56:49Speaker 01

  Crazy last name.

• 56:50Speaker 00

  Yeah, I know, cognitive debt. It is, and so instead of just being like tech debt, which is, here's part of our code in which we know is really, really bad, but we've kind of covered it up and someday we're gonna be able to come back to this and actually make it better. We can't add more features on this one side of our product. Cognitive debt is when you have like a senior leave your team, and then there's just a portion of your codebase that nobody knows how it works. And so, her whole argument is that these people effectively claiming that they're reviewing, as TJ said, 20,000 lines of code a day, really all you're stacking up is cognitive debt.

• 57:23Speaker 01

  I want to make it clear, I'm not saying I can review 20,000 lines of code, okay?

• 57:26Speaker 02

  Alright, 50,000, 60,000, whatever it is.

• 57:29Speaker 01

  That's way too low, that's way too low for me, guys.

• 57:34Speaker 00

  But you're getting this idea of cognitive debt, which is that we're stacking up something in which nobody knows how it works, and you now are only, like, your fate is directly tied to the performance of say Claude, or ChatGipity, or any of these programs, because you can't, like, me as the human eventually, like, I can't even go in there and make a meaningful impact in a day anymore, because it's just like, it's like me starting a brand new job at, you know, Google. It's like, okay, figure out the codebase, you're like, I don't know, there's millions of lines at this point. And so, I'm just curious what the future's gonna look like here in six months, because there's a lot of companies that are currently stacking cognitive debt, and we don't really know the outcome. I had a really good insightful question here, but I don't remember what it was, so that was my best swing at what I was thinking of.

• 58:17Speaker 01

  I'll just say, too, really quick, Prime, that I was reading somebody talking about this problem, and one of the things that I thought was really insightful about it was they were talking about how like, maybe even if 99% of the time, the LLM can understand all of it, and it works really good, like, there's so many catastrophic outcomes that can happen, like, for example, let's say- You're running a SaaS and someone depends on your site and something goes wrong. And then the LLM gets stuck in a loop and cannot solve, right? Which like everyone who's done this, it happens. It happens even on sometimes stuff where you're like, bro, it's literally, it's right here. Like, I'll just make the change. I'll make the change. That's fine. Put the token in the bag, bro.

• 58:59Speaker 01

  These hands were not meant for anything besides prompting, but I'll still do it. These hands were built for Excel, okay? Um, and so all, you know, I'll tippy typy in the, in the editor still occasionally, you know, and it's like, but so, okay, so then you imagine that and then now you're like, okay, I need to run my agents in a loop. They have to do all this crazy stuff. No one can understand the code. And then it's like three weeks of downtime.

• 59:23Speaker 01

  Like you'll just lose all your customers. You'll just all leave. So there's like so many things where I feel like people are not applying like a proper level of like even just simple common sense, game theory, you can call it whatever you want to make it sound cooler orbital data center. And orbital data knowledge, if you will, um, to this, to this problem where it's like, yeah, you can get to that point, but then what happens when something goes wrong? You like actually need to think about that if it's your business and not your hobby blog for Ruby on Rails boiling the lake, you know? I don't know. Sorry, Dimitri, you were gonna say something?

• 1:00:00Speaker 00

  Oh, let me just jump in really one quick second. Sorry, Dimitri. Uh, there was a paper just released. Just released right here.

• 1:00:05Speaker 01

  The classic guest experience.

• 1:00:07Speaker 00

  Yeah. No, sorry. Me and TJ are talking, everybody. Be quiet.

• 1:00:11Speaker 02

  Well, that's it for the standard. This is, sorry, we didn't get to talk to the guests at all, but maybe they could come on again next week.

• 1:00:16Speaker 01

  That's actually how we're doing this. We did clip a section out to put on YouTube and Bash happened to not talk a lot in that section like, guys, that was so rude. Bash never spoke that episode. And I'm like, no, she spoke a lot later. We had a whole segment for her, guys. Relax, relax. But anyway, sorry. Prime, continue on the thing.

• 1:00:34Speaker 00

  Sorry, I was just gonna say they did release this paper. Uh, there are some holes with which like models they tested, but effectively the floor rate, the bottom rate that if you give it a document and can it retrieve answers out of it, its hallucination rate was, or its incorrect response rate was at 1.19% at the most bottom rate. And so this is out of these like, and it gets worse as the context window gets open. So like, you know, just imagine what that means compounding in a codebase. At some point you could find yourself in a situation where. You'd like TJ describes where you're just you're beholden to you somehow conjuring the correct context and the correct prompt until you can master this or else you're just spinning tokens. And I've personally had this happen on a problem. So it's just a very exciting thing and it was very simple solution. All right. Sorry. Go on, Dimitri. You're very, very smart.

• 1:01:19Speaker 03

  Yeah. So I'm just going to say that on exactly that and, you know, connecting to what TJ was saying about the 300,000 line Ruby on Rails blog. I think people are easily kind of duped by confusing is this thing like a software tool or is this thing like a personality? So sometimes I like to I suggest this mental exercise. Whenever you get an AI output, I want you to ask yourself, if someone told me that they hired someone on Upwork to do this and they delivered it, how would I feel about it? Right? So for example, if you hired someone to make a very simple like 2010 era blog and they showed up with 300,000 lines of rail rails, you'd say something's wrong here. Right?

• 1:02:04Speaker 00

  But if there's 150,000 lines of tests, would you say there's something wrong there?

• 1:02:07Speaker 03

  Quite likely.

• 1:02:09Speaker 01

  Yes. Yes, I would. There's something wrong up here. There's something wrong up here, Brian.

• 1:02:15Speaker 03

  Right. So this thing is a it's an inhuman artifact. Right? So like on in the discussion with Casey, I was making this joke about like a four million line, four million line app to order pet food. Right? And it was an exaggeration, but it's only like a factor of 10 exaggeration, right? Like a 300,000 line rails blog is like at least 10 times the size it needs to be.

• 1:02:37Speaker 01

  It's made to do this.

• 1:02:38Speaker 03

  Right. It's made. Exactly.

• 1:02:39Speaker 01

  The original thing was Rails new blog or Rails.

• 1:02:41Speaker 03

  Yes.

• 1:02:42Speaker 02

  I was gonna say, there's probably just a built in thing in Rails to like have this happen. Yeah.

• 1:02:46Speaker 01

  This was how people were like, holy cow, Rails is amazing. Is DJ built a Rails blog on stage? I'm pretty sure. I'm pretty sure that's the initial thing.

• 1:02:56Speaker 02

  Yeah.

• 1:02:57Speaker 03

  So you have this inhuman artifact, right? The 300,000 line blog. And you also now have to rely on an inhuman tool to do anything to it, right? So you're you're like, first of all, you could be screwed because the tool can't can't do it, right? As you were saying, but like it just spins and doesn't solve a very simple thing. You could just be screwed and you're locked in, right? So you may not be locked into exactly the provider.

• 1:03:19Speaker 01

  Not the good way.

• 1:03:22Speaker 03

  Right? You are locked in somehow to using an AI tool to deal with it. Because like, what engineer? Let's say that the that the blog goes down tomorrow and it's like it's a big tragedy. Lives are on the line somehow. And you go and try to get an engineer and say like, we're going to pay you anything you want. We need you to dive into this 300,000 line rails blog and solve this subtle problem.

• 1:03:46Speaker 03

  Who's going to do that? Or at what price?

• 1:03:48Speaker 01

  Quick question, Casey, what would it cost to get you to go solve the 300,000 line rails problem?

• 1:03:55Speaker 02

  Um, so the answer is very simple. I'm gonna message DHH really quick and ask him how much he would charge. And I'm gonna add about 50 bucks to it. And and I'm gonna do it as a pass through.

• 1:04:09Speaker 01

  Smart. I love that. This is a really interesting strategy for monetizing contract work.

• 1:04:15Speaker 02

  Get someone who knows how to do it and then charge slightly more. That's that's my my motto.

• 1:04:20Speaker 03

  I love the strategy.

• 1:04:21Speaker 01

  That's my motto.

• 1:04:22Speaker 02

  But I'm gonna go ahead and guess that he will charge a lot of money. I'm guessing he won't be like $30. Like, I'm guessing it's gonna cost you a lot of money.

• 1:04:31Speaker 01

  Mm hmm. I'm sorry, I I interrupted you to ask Casey that. Go ahead, Dimitri.

• 1:04:35Speaker 03

  So just riffing on that, I think one of the things that. So there's something I partly I do with partial success in my own work. And I think many people are going to be doing this in the coming coming years is uh, working on um, driving AI outputs to something that might be human scale, right? So getting it to optimize for terseness or optimize for legibility in the human uh, in the human sense. Um, I don't know of any well established practices for this. Like I basically just mess around with it until I get it into a state of like, okay, fine. Maybe I'll accept 15,000 lines of rails for a blog. I'm definitely not accepting 300,000 lines, right? So I I think that that's definitely a, you know.

• 1:05:17Speaker 03

  That's something that is coming because it has to, right? I don't, like, we're not going to be shipping 300,000 lines of blog. Like, every single blog is going to be 300,000 lines of, like, not, so not just 300,000 lines of code, but 300,000 lines of completely custom code, right? So it's like, it's one thing if it's, I can't remember how big WordPress was, I saw someone do like a side-by-side of this thing versus WordPress. And WordPress was like, there are lots of like side modules and stuff, but they said that the core was like 150,000 lines, which, okay, fine, that's bloated as well, but whatever. But it's WordPress, and the whole world knows that codebase. Like metaphorically, the whole world knows that codebase.

• 1:05:56Speaker 03

  So it's not, it's not 300,000 lines that, not only does the whole world not know it, not even one person knows it, right? Not even Gary Tan knows it, right? So, I just don't think that that can work long-term. And, you know, to play the other side for a moment here, like, everything here is new. There are growing pains, people try weird stuff.

• 1:06:21Speaker 01

  Right.

• 1:06:22Speaker 03

  Like, early in any technology, or even like in games, like the early 3D games all looked weird and played weird until people figured out roughly how to get like stick controls and cameras working reasonably. So some of this is just, you know, people are working through the initial weirdness, and yeah, it's weird. So the part that I find a little frustrating is, we could be a lot more honest about that, right?

• 1:06:51Speaker 01

  Yeah.

• 1:06:51Speaker 03

  We could just say, hey, look, I made this thing. It happens to work for me, this 300,000-line thing. But also, obviously, this can't be, this can't be the path going forward, right?

• 1:07:04Speaker 01

  Or at least can't be the best thing possible, right? Like, probably the blog would still work at 200,000 lines of code.

• 1:07:12Speaker 00

  Uh, I don't know about that, TJ. Okay, this is a blog.

• 1:07:19Speaker 02

  I guess I would add something to that, which is, this is, like, if I had to summarize my primary frustration with AI currently, it is sort of just the condensed version of the things that Dimitri was talking about, which is basically like, it's being adopted too soon. That's what, like, because it's a gold rush and everyone fears being left behind, and like, you've got to get on the AI train and all that stuff.

• 1:07:45Speaker 02

  The result of that is people are using it prematurely. So they're tackling things with it that should not be tackled. Like, they should be tackled in an experimental sense, right? So, to be fair to Gary Tan, which is something I'm never gonna do again. But to be fair to Gary Tan this one time.

• 1:08:02Speaker 01

  Thank you.

• 1:08:03Speaker 02

  No one gives a crap what he's doing, right? So like, the, you know, he makes a blog, it doesn't matter. That's not gonna take down AWS, right?

• 1:08:11Speaker 00

  We haven't seen how much rail code there is.

• 1:08:14Speaker 01

  Also, we don't know. Maybe Kiro depends on the blog now, so.

• 1:08:19Speaker 02

  So it's just like, fine. Like, that's actually, Gary Tan making a 300,000 lines of code blog is actually very harmless to the industry, I would argue. So it's actually not that bad. You know, it's fun to kind of poke at him on this podcast or whatever, but like, actually, I don't have a problem with that. I really don't. Great, you know, he's playing around with this thing and we're learning something from that and hey, the results weren't that great, but, and maybe he's not ready to admit that yet, but like, you know, that's, we learned something from that, right? And that's all fine. The worst thing is when, yeah, like when Amazon starts using this at scale and that was a bad idea and now people suffer the consequences because the infrastructure gets more brittle and all this other stuff.

• 1:09:04Speaker 02

  And so, really, that's most of it. It's like, I would much prefer if we could have done this in a way where we were validating that the AI could really do this better than humans for whatever the task was and then we roll it out, that would have felt a lot more comfortable. And instead, we're very much riding the curve where like, oh, can an AI sort of maybe do this at all? Then we're, then we're doing that, like, in production as the actual model. And I understand why people are doing that because of the gold rush sort of, or the FOMO sort of problem. They don't want to be the last company to adopt. I get it, but the problem is like, I think we're gonna pay a lot of, I think we're gonna...

• 1:09:48Speaker 02

  Suffer a bunch over the next two or three years for no reason other than people, if they had just waited, like each task, if they just waited another six months or another year to like vet these things out and let the AIs get better at the same time and all that, we could have prevented it. They're like, they're riding just below where they should be instead of just above where they should be, right? I don't know how you feel about that, Dimitri, but that's kind of like the thing that I see being the bad part currently.

• 1:10:18Speaker 03

  So it's, it is perhaps worse even than what you are imagining right now. So multiple times, so you're talking about within the tech industry. I very frequently work with industries that are not, not tech, right? I have worked with people who are in charge of various kinds of regulatory committees. And for example, they have a dispute about how a particular category of product, I can't say what it is, but a particular category of product should be regulated. And they'll say, well, maybe we should get the AI to write the regulation. And I like, I have to talk them down and say like, look, wait, like, stop, you know, stop right where you are. You obviously have an extremely dangerous idea in your head, which is that this thing can, that this thing is smart in the way

• 1:11:03Speaker 03

  that you understand a human to be smart. And that when you ask it to do, write me, you know, 10 pages of regulations on the safe use of this device, that it's executing like human value judgments the way you might, right? And they don't know that, right? These are like, these are like smart people, like lots of degrees, 30 years of industry experience. These are not stupid people, but they just have very dangerous mental models of what these things are and what they can do, right? So like however bad-

• 1:11:29Speaker 02

  Well, they're getting told all the time. This thing is, this thing is literally God. This thing is literally God. It's impossible for it to make a mistake. It knows every book that's ever been read, every scientific fact of all time, and it can't be wrong. That's because me, Dario, or me, Sam, or me, Elon, or whoever, were saying, yes, and I created God.

• 1:11:48Speaker 03

  Yeah, and they say that exact thing to me that, well, all the, you know, like, all of the federal register, all the federal rules, right, all the federal register is in the trading data, right, so it should know all the rules, and I can just ask it to generate, and I spend a lot of my time talking people down from these kinds of ideas, and the AI companies absolutely do not make that any easier, because they're obviously highly incentivized to say the opposite, right?

• 1:12:14Speaker 01

  Right.

• 1:12:14Speaker 03

  Like, it's a lot harder, like, and partly, there's a, like, a, not a prisoner's dilemma is a Mexican standoff, I guess, where the, like, if, like, if whatever, Dario were to come out and say, you know, actually, let's talk about having reasonable expectations, this isn't going to solve all your problems in life, it's not going to get you a girlfriend, it's not whatever, right?

• 1:12:39Speaker 03

  That person would almost certainly be then at a disadvantage, at least in the financial markets, you know, compared to what, you know, Musk or Altman or Hasabi said DeepMind might be saying, right? I didn't mean to single out Hitler, I think the problem is pervasive.

• 1:12:57Speaker 01

  Equally, for each of them, they have this exact same problem, and they also need boundless amounts of capital to execute on what their current vision is, no malice required, just, they think the way to get really awesome AIs to build a trillion dollars of data centers, well, they don't have a trillion dollars on hand, they have to raise the capital, so they can't, like, it actually makes sense, it follows, yeah.

• 1:13:22Speaker 02

  Well, everyone is motivated by the same thing, everyone is worried about being

• 1:13:26Speaker 01

  Cars references.

• 1:13:27Speaker 02

  In second, third place, fourth place, whatever, right? So, if you're terrified of that, and you think that it will justify, you know, that justifies it, then, you know, the AI companies are behaving in that way for the same reason that the other ones are. What is, it's not that funny, the Cars references.

• 1:13:49Speaker 01

  He's being motivated only by Cars references.

• 1:13:53Speaker 02

  But we know that about him, we know that he's only like-

• 1:13:58Speaker 01

  That Twitch chat, just, Twitch chat noticing my joke always makes me laugh, sorry, Casey.

• 1:14:04Speaker 00

  Okay, so I want to throw one thing out there that I think one thing that is kind of, I would argue is being massively understated in this is that it's not that I think all these AI companies and all these people are thinking that they're going to be losing their job and they have to be keeping up with the times or else they're going to be left behind and in the permanent underclass. I do think a large amount of people just don't perform that hard on their jobs. I've worked with plenty of people who they just want to really arrive there and do three hours of work, right? We've seen the TikToks. We know this just simply exists. And if you have something that's going to take the 30 minutes you would normally spend on writing an email and trim that down to three minutes, you can just compress your four-hour workday into 20 minutes and you're just like, why would I not press the easy button?

• 1:14:46Speaker 01

  They're gonna press the button.

• 1:14:48Speaker 00

  And so for me, it just seems like a very simple, like a large percentage of this is just like, oh, this just makes all the little like mundane things I do not in software world super, super easy. And for those that just don't care, and I mean, we've all worked with plenty of people that can produce amazing code, including myself, and then you produce this amazing, and you're just like, oh, dude, I can just easy button this one thing out. Easy button, easy button it.

• 1:15:11Speaker 02

  But I don't, like, that's, that's on an individual basis. That's like somebody individually who decides to use AI and they're really not going to be the, like, the problem, quote unquote, because the problem comes from institutional adoption, right? The, like, that person is, is, is not really an issue for anyone other than like maybe, you know, if you're getting slightly lower quality work because the AI isn't doing as good a job writing the email, but it probably is. So like, I don't know that I'm that worried about even that. Because if someone was that checked out to begin with, like you say, like, I mean, how much worse is the AI really going to be? So the problem is more when you have this institutional adoption, because then what you're doing is you're forcing people

• 1:15:53Speaker 02

  who, the people who were taking their job seriously, to take it less seriously effectively, right? Because you're forcing them to use this tool and they may not be able to get the results that they want from the tool and you're forcing them to use it and all of that stuff. And so if that's premature, that's to me the problem. I don't see it as being a huge problem if a lazy person just wants to use AI to make themselves even lazier like because they were already kind of a problem to begin with. And like, you know, how much more of a problem are they really becoming? I don't know. To that, to me, anyway, that would be my gut reaction to that. But Prime, maybe you, I don't know, maybe you disagree there, though.

• 1:16:30Speaker 00

  It's not that, like, I mean, obviously, the institution is the catalyst, but when, you know, I don't know what percentage of people at these, like, super large companies tend to have a very large amount of checked out people. It's just like a reality.

• 1:16:40Speaker 02

  But they weren't, they were already non-contributors, sort of, is what I'm saying.

• 1:16:43Speaker 00

  They were sort of non-contributors, but they're also non, they also didn't make a big impact. Now they can move at a rate that is like unknown to them previously. And so now they can-

• 1:16:53Speaker 02

  But they won't, because they're lazy.

• 1:16:55Speaker 00

  They can make bigger impact than they've ever made before, right? They're like, I'm 10x more productive, and maybe I don't want you to be 10x more productive. Like, right now, I can tell you that I've had more problems on YouTube Studio than I've ever had in the last five years, I've had in the last year.

• 1:17:09Speaker 02

  I agree with that.

• 1:17:09Speaker 00

  It's almost like every single time I use that product, a new thing is just completely broken constantly. And it's just like, I don't, I know Google is like historically a place where you go not to work. Like, that's just like one of the, a big thing of the general software. And I know there's some places in Google that are very rigorous and very difficult to work in. I'm positive that exists, but I've met enough people to know that there's like a lot of coasting going on. And now there's a lot of changes happening, but everything feels broken. And I don't know what to attribute this to, other than like, hey, we've given a bunch of people easy buttons. Now everyone's moving at a rate faster than they normally would. But they still have the same decision-making level that they did before they went into it. Which is like, to me, the dangerous part is like, I don't want you moving 2x faster. I want you moving, I want you to move the same speed. Go slow.

• 1:17:53Speaker 02

  That would be terrible. If a bunch of people who don't really care are now suddenly doing a lot of quote-unquote work, that would be very bad, obviously. But I don't know.

• 1:17:59Speaker 01

  That is what appears to be happening.

• 1:18:03Speaker 02

  Then I agree, then I agree with you. That's pretty bad, if that's actually true.

• 1:18:05Speaker 01

  It doesn't even have to be they don't care. It's just they may not have even the skills to recognize. Like, Dimitri, your point of saying like, hey, I thought the AI could solve this problem well, but I don't, it actually can't. It actually can't write a good rigorous spec for this thing for 10 pages. Or like, I'm a junior dev, I don't know that these five things are actually hidden footguns that I shouldn't merge, that are going to turn into gigantic foot cannons in PR 2, 3, 4, 5. But now I could just merge those in and they're like a cascade of, you know, effects, because nobody is putting the stop to those things. That part, you know. Does strike me as kinda dangerous.

• 1:18:42Speaker 00

  Dimitri, I do wanna circle back to something you said. You said you're working on trying to minimize these outputs. Uh, with like, okay, hey, we have 300,000 line Ruby blog, but really that should be... You should be able to get that down to 50,000 lines, 100,000 lines, right? You're trying to work on how to reduce the entropy, not grow it. Uh, how like, is there actual meaningful progress being made in that region to the point where year over year, you're saying, hey, this would have taken 300,000 line Ruby blog post, but now with our work, we're at 275? And is there any sort of like, direction that you're saying, hey, we're actually improving this kinda stuff? Cause that's, to me, that's very appealing. Like, I'd much rather see it play code golf than play whatever it's playing right now.

• 1:19:23Speaker 03

  Uh, so that's a, uh, this is a small slice of the industry where, uh, where I'm working and I'm not aware of any, uh... I, I, I know very few people who are even talking about trying to solve this problem, right? Um, on my side, I do this all through, uh, you know, sort of like meta-practices of... I mean, just the most basic, starting from the most basic thing, which is, I have some project, let's just say hypothetically, a blog, right? I know roughly what the components of the blog should be. I'll make like an architecture diagram, metaphorically speaking. Uh, and then I'll say, hey, I, like, this thing should be ballpark 2,000 lines of code. And they'll have it generate that and separately evaluate that, right?

• 1:20:05Speaker 03

  And then write out an interface file and then separately generate another module of, okay, we've got whatever, like, the backend and the ORM. That's one thing. It's standalone. It's done, right? And then I'll go and do whatever, like, here's the load balancing layer, right? If you have like a super high-performance blog or something. Um, I've found that's, uh, generally my, the thing that I would like to encourage people to do is, like, instead of trying to solve the biggest, most hypothetical, uh, game you can right away, just like, try to maintain quality and increase your productivity by 10% and see if you can do that, right? Um, and that's, so like, people are trying to go from, uh, you know, like, whatever my current pace is, I'm gonna try to go 10 times as fast.

• 1:20:49Speaker 03

  And, you know, I mean, that, that would be great, but actually, uh, in the history of computer programming, like, a 10 or 20% productivity improvement is already enormous, right? Like, there are very few things that actually make progress, right? So, what I encourage people to try to do is, can you just get 10% better using... Using AI, and if you frame it that way, I approach things very differently, which is I sort of spec out, this is how I would do the project myself. Here are the components, here's how they talk to each other, write out a spec for the interface, and then generate each thing separately. And so I have like 20 AI-generated modules that are a couple thousand lines of code each, and then I just stitch them together at the end with like 500 lines of code that I wrote

• 1:21:32Speaker 03

  using the interfaces that I spec, and then it filled out. And there I'm able to generate things that are ballpark the same size of code that I would generate. AI is more verbose than I would be, but I come from a mathematical computing background, so my style is very, very terse to begin with, right? I think you can generate quite reasonable artifacts that way. I don't know of any standard organized push to try to do what you suggested, Prime, which is, okay, I got the inhuman artifact, the 300,000 lines, can we now shave it down? I haven't seen anything like that that works. Now, I've tried here, you know, take these 50,000 lines and can you reduce it down to 40,000 lines?

• 1:22:17Speaker 03

  And it's extremely unreliable. I haven't done that test in a few months, so you've probably heard the meme that like everything changed December of 2025, and there's some truth to that. It's not as true as some people are suggesting.

• 1:22:31Speaker 00

  Can I follow up with that after you're done with what you're about to say? I actually do want to ask you about that.

• 1:22:35Speaker 03

  Yeah, I'm done with this.

• 1:22:37Speaker 00

  Oh, just yes. Okay, so I have a hypothesis that the reason why people are seeing the big change that they're seeing in December 2025 is not because the new model was just like 20x better, but because we've been investing non-stop effort into all these harnesses, and they just have gotten better and better and better over time. So this nominal improvement in the model actually made something that perceivably was a larger improvement, but it actually is just the stuff around the model that has so vastly improved over the course of the last year and not the model itself.

• 1:23:09Speaker 03

  Yeah, I mean, I would agree with without like seventy percent. I mean, there is substantial improvement in

• 1:23:14Speaker 00

  I'll take a C.

• 1:23:15Speaker 03

  Like four in four point six, but but also you're absolutely correct that I would attribute most of the excitement of the like post twenty post Christmas twenty twenty five meme is like sufficient maturation of these meta practices like, you know, agent loops and like agent teams and and stuff like that. So I think broadly, I agree, although there really was a meaningful improvement with four point six.

• 1:23:43Speaker 01

  I've got one last bigger question that I wanted or like topic that I wanted to talk about that I wanted to make sure we covered from the podcast. Prime, did you have anything else you wanted to add or Dimitri say anything else there?

• 1:23:53Speaker 00

  Dimitri and Casey, are you still OK going? Because we're a half an hour over our projected amount of time. And I don't want to take your guys' time if it's too valuable.

• 1:24:01Speaker 03

  I should probably go in like five minutes.

• 1:24:03Speaker 01

  OK.

• 1:24:04Speaker 00

  But TJ just has one quick, big topic he wants to talk about.

• 1:24:06Speaker 01

  Really quick, big topic. OK. I gotta get out the way for it, too.

• 1:24:09Speaker 00

  I thought that was a fake one.

• 1:24:11Speaker 01

  Oh, no, you gotta have one that's a green screen and then one that's a real one. That's that's the trick. That's the trick. OK, it's not see through, though, so I have to look away when I'm ready to get. So I'm just gonna draw this really quick. Just kidding, that side's dead. There we go. Supply and demand. I have a quick question about this. There you go. That's all I need.

• 1:24:29Speaker 03

  OK, simple topic.

• 1:24:31Speaker 02

  That was that was a really, really good diagram, by the way.

• 1:24:35Speaker 01

  Uh, it's one that a lot of people aren't familiar with, so I wanted to make sure that we drew it out for for those that aren't out there. There's two parts, two part question, just so you know where I want to go with this. The first one is sort of like, I don't feel people meaningfully talking about, like, let's say, we a hundred or a thousand X or like a million X demand for tokens, uh, which like would have to be the case if everybody's using tokens for all their jobs. Aren't we gonna like a hundred billion X or three hundred million X?

• 1:25:03Speaker 00

  It's gonna be a big number. Yeah.

• 1:25:04Speaker 01

  I'm using way more tokens than like my dad. My dad like occasionally asks ChatGPT something. He doesn't even know about deep research mode. Right? Like. So I can burn a million tokens before even noticing, right? So it's like, so there's that part of the equation where if the demand is going to go crazy on one side, is it not going to push the price of tokens up higher even if we have technical things? But on the flip side of that, of this, like, we're getting tokens cheaper and all this other stuff. And you guys talked about Javon's paradox. So I just want to at least give a spot for you to at least bring up this topic of some things like, hey, if we're going to get tokens a bunch cheaper, but then we're going to keep pushing up demand for tokens, is that going to make it more expensive?

• 1:25:47Speaker 01

  And what does that mean for like, everything that people want to do with tokens? They want to do agent loops, they want to, everyone can't possibly just have an agent loop running 100 million tokens a second. So I don't, it's a big, broad question. Just interested in your thoughts sort of on like, those market pressures, where you see that? And like, how that affects people's usage of AI if it actually does get broadly adopted?

• 1:26:12Speaker 03

  I guess I'll say two things. One, connecting to the previous conversation of the 300,000 line blog. Obviously, that's generating, that's consuming and generating a lot more tokens than you might think would be required to write a blog in Rails, right?

• 1:26:25Speaker 01

  Right.

• 1:26:26Speaker 03

  So there, there is that. There, there's this question of, how long will we be in a period of subsidized growth with multiple players? So that no one can really afford to try to squeeze the market for margin? And, you know, as I said with Casey, the big thing everyone is worried about is somehow someone gets a position in Gen AI that is as dominant as Google had or has in search, right? So Google, for a long time, had like 90 plus percent of the market and the next player was like 8% or something, right? So it was like 90% Google, 8% Yahoo, or then later Bing, and then like 2% random other stuff, right? At least in the US market.

• 1:27:09Speaker 03

  So I should say that, but almost all my experience is in the US market, right? So, I mean, notably, once Google got that dominant position, they were able to eat tons of the margin in advertising, right? And, and so, without someone else, without some competing search engine to force Google to reduce margin on, on ad clicks, well, they just sat and ate all the, you know, almost all of the margin in, in the online advertising business. If that happens, it could be very scary economically for anyone who's relying on AI, right? Because right now, we're, right now, we have not only this, like, VC honeymoon period

• 1:27:54Speaker 03

  of they don't really have to make the money back right now, right? And that, that phase could last a long time, like Uber was in that phase for like 10 years, roughly. So, so we have this, like, at some point, the honeymoon will be over, and possibly also at some point, there will be a Google of Gen AI, and it might even be Google, right? So, like, the Google of Gen AI might be Google. We've seen what they've done with a Google-style advantage in the past in terms of how much of the value in the market they were able to capture. Right. And so, I think, like, that, I, we won't know anything about that for, for years, but I think that's, that's the biggest factor. Right.

• 1:28:34Speaker 03

  I, I do think that the, the open stuff is getting better and better, and I think it will be good enough, I mean, it's already good enough soon, actually, that you can use it as a substitute in many cases. The, the main, excuse me, the main thing that is missing in the, in the, in the open stuff is the relatively polished product wrapped around it and, like, all the extra features that go into the chat. Now, I, I understand, like, you and I are using it through the API, but, like, the, the Right. The mass of the market that still has not moved through the phase of, hey, what the heck is this thing and can I, can I use it? They're going to go through the chat interfaces first, right?

• 1:29:17Speaker 03

  Even if they eventually end up using, using it through the, through the API.

• 1:29:23Speaker 03

  So yeah, I guess the open models are really quite good and getting better. So at some point, that will have to come to a head where people will say, okay, look like, yeah, Claude is great, but you know, between DeepSeek and Quen and Mistral and Lama, I can stitch together a pipeline that does 90% of what Claude does and all it costs me is electricity, right? Right. And that's so far on the other end of the economic structure that I don't have good predictions there. Yeah, okay. I frequently set up such systems for, you know, for customers where we just do like, everything is open because like, whatever, for regulatory reasons, it has to be on premises.

• 1:30:07Speaker 03

  Nothing can leave, there can't be some third party involved in the deal, whatever, right? So that's so far on the other side that it's hard to compare directly because it's like, setting it up is also more complicated. Right. But I think probably, well, not probably, for certain, there are people right now who are trying to build kind of a like, bring your own open model and they'll just host it and like pipe stuff together for you. Something like that has to succeed in the next few years. I haven't seen anyone who's like, has a strong lead there, but something like that, I think, has to, has to exist in the market if only as a, as a check on, on how greedy the, the commercial players can be. So.

• 1:30:51Speaker 03

  I guess, I don't know if that answers your question, but, sorry, Prime, go ahead.

• 1:30:54Speaker 00

  Just a quick question. If, if, let's just say all things are given the same, I don't know much about kind of the infrastructure overhead that OpenAI or Claude currently has. Like, how much room do they have to be able to grow? But if everybody were to turn on a Claude bot tomorrow and they all just ran 100,000 tokens through, which is not a very hard amount to run through, or maybe 250,000 tokens and just in America, I mean, that would be hundreds of trillions of tokens that just weren't there beforehand. Like, how can that, in this theoretical situation, would we see, I would assume the infrastructure would be so overwhelmed that there would, like, we would have to skyrocket price? Would that be the only path forward? So if something doesn't come out of this, then price does have to go up if usage goes up.

• 1:31:39Speaker 02

  Or throttle speed. Or throttle speed, which effectively will reduce the usage.

• 1:31:44Speaker 01

  Yeah.

• 1:31:45Speaker 03

  But that's why they're like, everyone is fighting for rights to build data centers and get electricity and hydropower, because this is exactly, you're thinking of it the same way they're thinking about it, at least in public, which is like, we are maybe 10%, 20% into market penetration of AI use. So like, they're hoping to get to 100% penetration, right? So that's like five to 10 times where we are now. In order to do that, they need vastly more physical resources just to run the thing. Never mind making better models, anything else. Just freeze, like freeze right now, everything you have and just serve it to 10 times as many people doing, not, and not just 10 times as many people, but like 10 times as many people doing maybe 10 times as many tasks, right? Because maybe right

• 1:32:27Speaker 03

  now, we're only using it for coding, but later we'll use it for, you know, I don't know.

• 1:32:33Speaker 01

  Well, like Cursor, Cursor's got remote agents. It takes a video and sends you a video of the output to see if the thing actually still runs, so that you can know, like, did, did, did your front end change actually work?

• 1:32:46Speaker 03

  Yes.

• 1:32:46Speaker 01

  Like, that burns a lot of tokens. It's a super cool feature, but like, that's a ton of tokens.

• 1:32:51Speaker 02

  Dimitri said he had to go.

• 1:32:53Speaker 00

  Yep.

• 1:32:54Speaker 02

  Dimitri.

• 1:32:54Speaker 01

  Oh, sorry. Yeah, yeah, sorry.

• 1:32:55Speaker 02

  You have to let him go.

• 1:32:56Speaker 00

  Dimitri, where can everybody find you at? What's your most like favorite place that we could link you at?

• 1:33:01Speaker 03

  Uh, it's just a touch to, to Casey's regular thing at Computer Enhancers, Waiting Through AI. Uh, that's Casey and me roughly once a week. Uh, and then if you want to find me specifically, for whatever reason, it's DimitriSpanos.com.

• 1:33:14Speaker 01

  Sweet.

• 1:33:14Speaker 00

  DimitriSpanos.com.

• 1:33:17Speaker 01

  We'll link that in the description for people later as well.

• 1:33:19Speaker 00

  Yeah, I just want to make sure I get it. Uh, PhD?

• 1:33:23Speaker 00

  Do you have PhD level intelligence?

• 1:33:24Speaker 01

  I'm doctor.

• 1:33:25Speaker 03

  I am try, I am generally anti-credentialedist, but yes, I do have a PhD.

• 1:33:29Speaker 00

  Okay.

• 1:33:30Speaker 01

  Nice. Yeah, well, that's like, uh, yeah, me too. If I had a doctorate, I'd be against credentialist too, but then I would say it like I'm cool as well.

• 1:33:37Speaker 03

  I'm not against credentials. I'm against credentialism.

• 1:33:42Speaker 00

  Alright, well, thank you very much, Dr. Spanos.

• 1:33:45Speaker 02

  Thanks, Dimitri.

• 1:33:46Speaker 00

  We do need to get you back on here, hopefully our style, which is very different than Casey's, which involves a little bit more joking and orbital data centers. Hopefully you enjoyed your time here. We certainly enjoyed you. Chat was wild. They want you back. A lot of people that bring back Dimitri. They really, really appreciate you, so.

• 1:34:04Speaker 03

  Yes.

• 1:34:05Speaker 00

  Thank you very much for joining us, and this was a great conversation.

• 1:34:08Speaker 03

  Yeah, alright. I'm out.

• 1:34:11Speaker 02

  Bye.

• 1:34:12Speaker 00

  Bye.