042 The rise of GTM engineering, GitHub Fake Stars, AllBirds AI

[00:00:00] Speaker A: Way. But for now, I'm so full of opinions. But okay. Might do look. Does look good. Okay, I'm ready. Okay, let's do it. Hey, welcome back to the Gregory and Paul Show. I'm Gregory. [00:00:13] Speaker B: I'm Paul. [00:00:15] Speaker A: And we break down latest SaaS, startups, AI. We love to talk about memes. We got a great show planned for today, and if you haven't noticed, we're now streaming on Thursdays. We thought that would be a better day to do the show. I think a lot of people are checked out on Friday afternoon, especially as summer's coming up. [00:00:38] Speaker B: Weather's nice. [00:00:39] Speaker A: Oh, my God. Hey, I remember when I worked in big advertising back in the day, we had summer Fridays. [00:00:48] Speaker B: Beautiful. [00:00:49] Speaker A: That was like a classic New York thing. It's so long ago where, like on Fridays they let in the summer, they let everyone, like all the all kids go down to the Irish pub early. Which was fun. Yeah. Okay. So for the show today, besides my corny dad jokes, we'll discuss the rise of GTM Engineering. We're going to talk about the fake star GitHub economy. We'll touch on the the all new and improved allbirds. [00:01:23] Speaker B: That's right. [00:01:25] Speaker A: I have my favorite section. Gregory's a grumpy old man. Federal Reserve bank conspiracy theory corner. People challenge me on Twitter about this. Like, do not go there. You don't want to talk to people [00:01:36] Speaker B: arguing with you about. [00:01:37] Speaker A: They don't want to talk, they don't want to talk. Don't talk to me about Federal Reserve Bank. It's never, it'll never end. Okay, we're going to look at LinkedIn data that maybe says AI is not what all the layoffs are about. We'll talk about the AI bubble. I know Paul has a lot of opinions on that. I have some gripes about AI writing I want to cover. We'll do some things on Cloudflare and then we got some VC news. Maybe a meme. Paul, do you want to kick off the first discussion about the rise of GTM engineering? [00:02:11] Speaker B: Yeah. So gtms has been. GTM itself. Go to market has been a term that's been coined by, I don't know who coined it. Maybe Clay. It's. [00:02:25] Speaker A: Yeah, I would give them credit. GTM Engineering. They really took that term and popularized it. [00:02:31] Speaker B: They ran with it. Right now there's this concept of marketing engineer, which I would think is this whole whole entire called the melication of marketing. Masculinization of the marketing job. You know? You know, I, I, I think it's true. I Think this, the industry. [00:02:54] Speaker A: I think this is a, I think this is a trick that is as old as hills. Like if you go to a university, everything is like rebranded as like a technology or an injury. Political science. They, this has been around for a long time. Like everyone always tries to re, rebrand everything as a, as like a science because it has more perceived credibility. And I think that's the same thing is going on. I, I don't buy the narrative that it's some like masculinization of, of something personally. [00:03:23] Speaker B: But so, okay, so there was a video going around on X or that was reposted from TikTok. [00:03:28] Speaker A: I saw it. [00:03:28] Speaker B: This woman went into saying, hey, as soon as a job gets status, men starts to chase it and it gets masculinized. [00:03:41] Speaker A: I don't buy any of this. [00:03:42] Speaker B: I, I think it's, there's some, there's some truth to it. Right? Like, so the example is that back in the, before the 80s, before the computer, a programmer was a female job, right? A calculator, a person who literally did the calculations and did the numbers by hand. And then as soon as it became a thing that actually makes money and status mail took it over. And now when you think of a, a programmer you usually think mail marketing. [00:04:12] Speaker A: I think this is, I think this is just like, this is just another like social media narrative to get everyone all riled up. Like, yeah, I don't, like, I don't buy any of it. Like I, in fact I watched that video and I thought the whole thing was ridiculous. Like, like I actually did a search for like what did IBM engineers look like in the 60s? Guys. Yeah, so like there's all kinds of ways to spin this. Like it is true. Or at least I have read. I wasn't around in the 1890s when they had teams of calculators who wrote up all of those books that had lookup tables and, and supposedly they were mostly like upper middle class women which there weren't many of people because there weren't that many upper class people, the British Empire who did those jobs. That's what I've been told. Like I said I wasn't around, but I just think this is just like a, a crappy narrative. Like that's why I went back to like the university thing. I think the real story is that people love to like somehow take things that are not science and then pretend that they are science. And I've always ultimately been against this in, in marketing because I don't believe it's science. And, and I'VE actually, I've discussed this a lot. I believe it's science because I think science needs to be repeatable. If you look at like, what is the definition of science, how does science work? You need to be able to conduct an experiment that has a repeatable outcome. Like, marketing does not have repeatable outcomes. It's not a science. Like, it's like we buy a hundred dollars in ads and it's always this, it's not always that. [00:05:51] Speaker B: But do you think, like there could be a potential to make it into a reputable science? Right? Like that's. Don't you. [00:05:58] Speaker A: Great question. [00:05:59] Speaker B: Don't you think that there is some secret sauce that. [00:06:03] Speaker A: Okay, so I successfully pivoted discussion away from this dumb conflict between men and women in the workplace. [00:06:08] Speaker B: I'll. I'll give you. [00:06:09] Speaker A: Did I, did I do that? [00:06:10] Speaker B: I'll give you that. Okay, so basically this entire industry with the marketing engineer, right? We can pivot. [00:06:16] Speaker A: We can pivot back to it. I do have. [00:06:17] Speaker B: Anyway, no, I, I think, I think it's true. Right, so AI is obviously reducing the job market for, for software developers. Let's say we gotta, gotta figure out something. [00:06:28] Speaker A: We. Not. That's not. We're not sure about that. Right? There's all those charts that show software engineering job. We'll get to that one later. Okay, let's keep going on this. The science of marketing. The science of marketing. [00:06:39] Speaker B: Let's say that the perceived. That's what's going on in the market. Right. I myself pivoted from software into. I'm gonna now call myself a marketing engineer. Right. [00:06:51] Speaker A: And vibe marketer. [00:06:52] Speaker B: A vibe marketer. That was before, but I think we've now graduated into a marketing engineer. I, I think there is some science to it. The reason why we're looking for the science, I think is because we're trying to figure out how to properly sell to men. [00:07:12] Speaker A: I mean, look, I think everybody wants it to be a science. Like they want it to be repeatable. And that's what a business would want. It's. That's super clear. Right. And so I just don't know if it's a science. So this has always been my take on like advertising. So there's a lot of things that people in marketing do, but I think they're really hard to guarantee that you get a result, you create content or you do a positioning exercise. But like, the actual outcome of these things I think is sometimes nebulous or hard to define. And advertising. One of the things where I think you can, like, I would use a term, I would, I would frame it like there's a strong possibility that you'll get a repeatable outcome. And I, and I like to say that that's why advertising survives, right? Like, like we spend a million dollars a month on ads, we will get some result. The results will vary, but there's probably some statistical way to look at it and get similar results. Although it's not perfect, it's far from perfect. Like I've seen it like not work. But over the long term, if you spend enough, you'll get a result. Right? So it's very much like, I suppose, like the stock market, right? Like there's volatility. Sometimes volatility may be really extreme, but if you spend enough money and you do it long enough, you will get a measurable result that's fairly repeatable in advertising. [00:08:31] Speaker B: I think, I think you nailed the problem and I think it's solvable. Solvable problem. It is, it is a data problem. As in it's too expensive to get enough data to make judgment calls. So. [00:08:44] Speaker A: Correct. That. Correct. That's where it usually comes down to, is that people can't afford to spend enough. Right. So the companies that do have like billion dollar budgets, like it's a hundred percent math. [00:08:55] Speaker B: Correct. So the marketing, let's say the hypothetical marketing engineer, if it becomes a thing, it will try to bring down that cost so that all companies can collect enough data to make a process repeatable fill up. [00:09:09] Speaker A: So that's always been the, that's been the theory, right. But like generally what I've seen is that people can't collect. You need a lot of signals, like you can't collect enough signals and they're not. And that because like, okay, so this, this is where, this is where, okay, this is interesting. This is where it goes into like you have to actually understand statistics. And I think most people don't or they willfully deny like how statistics actually work. You need a true random sample. That I think is ultimately why most marketing measurement I think is garbage. [00:09:39] Speaker B: So AI is actually really good for this because everything that AI does is completely, utterly random. [00:09:46] Speaker A: But you need signals from external signals about what you're doing though. That's a good point. Like artificial data, man. There are ways to like mitigate this. I like it. I think, I think it's. [00:09:55] Speaker B: So the entire industry is moving towards, okay, this is kind of ties into what the heck tech is, even a marketing engineer, right. So the whole entire industry is basically going towards what I call like synthetic audiences. It's Basically, like, what's the difference between a random shopper somewhere versus, like, you. You build a hypothetical AI shopper. Okay, they're both basically the same thing. [00:10:19] Speaker A: One doesn't like Katy Perry. [00:10:21] Speaker B: One doesn't like Katy Perry. [00:10:25] Speaker A: That's different. [00:10:26] Speaker B: Or, yeah, Katy Perry, Justin Trudeau, whatever. Okay, but, like, basically they're both act randomly and then you try to influence it, and then you can model out, like, statistically how, let's say 10,000 AI agents would buy your stuff. [00:10:43] Speaker A: Yeah, this idea has been around a long time. Like, prior to, like, the. Let's call it. I called this today with someone else, the third AI boom. I think I've been through three AI booms. Uh, I still think this is a valid idea, though, that, like, there's synthetic data sets that we could use and we could test against it. But. So I love all that. But I think the problem is ultimately, like, if you're a small company, like, you have a million dollar. A month. A month marketing budget, it's just not enough. Like, even though the synthetic data says something, you. You need it to have enough signals for it to work, you know, in a repeatable way. So, so, okay, here's a good example. There were those people who cracked the lottery. Do you remember this? He was like a math professor in Tennessee, like, a. And he found a lottery where ultimately the odds were such that if you bought enough tickets, you could game it. So the. I'm not an expert on lotteries. I don't play a lot of these things. But, like, usually there's like. It's like a billion options or something. Like, the numbers are so big statistically that you can't. You can't buy enough tickets to game it. But he found certain lotteries where, like, they had a statistical flaw in it. [00:11:58] Speaker B: There's a flaw. [00:11:59] Speaker A: And so they literally bought like, thousands of tickets or something, some enormous number. And because he was able to reach a certain threshold, he started to win on a repeatable basis. And so I like this example because I think this is advertising. Like, if you. If you can find an area where the statistical pool is small enough and this all lines up, it will be repeatable. It's just like, that's really hard to. To do. And there's not a lot of opportunities like that, so you end up in the larger pool. [00:12:27] Speaker B: Fair. [00:12:28] Speaker A: Where the signals are just. [00:12:29] Speaker B: Okay, fair. We're just framing it now. [00:12:32] Speaker A: See, we know. We know how data science actually works. This is a. This is ultimately. I can't. This is ultimately where I think A lot of people struggle is like, this is kind of a long, boring conversation. People get to like, and they're like, just do the marketing. [00:12:45] Speaker B: Like, whatever, just do the marketing. [00:12:50] Speaker A: Like, it's like, ultimately, like, is it a $1 billion Coca Cola Global budget? No. Okay, then we don't need a PhD economist to work on it. [00:12:59] Speaker B: Yeah, but, you know, marketing engineers. [00:13:01] Speaker A: All right, what, what else do you want to say about marketing engineering? I think this is a great topic. [00:13:04] Speaker B: I, I love it. I love this view. [00:13:08] Speaker A: You love marketing engineering? [00:13:09] Speaker B: Buy my marketing engineering service. [00:13:11] Speaker A: I, I. So I do think there is something to be said about the rebranding of the, of the, the space. And so, yeah, I would take it a different direction. I think that, like, Silicon Valley loves to rebrand and rename things. [00:13:26] Speaker B: Yes. [00:13:27] Speaker A: That's, that's where I think this all stems from, is that these, there's like, there's always this young cohort of kids go to San Francisco and start these companies and they're like, want to reinvent the world, which is awesome. And I was one of those people. And I guess, like, in my heart, I'm still one of those people. I think it's great. I'm hugely supportive of it. And so I think part of the, like, impetus or the enthusiasm or they get caught up in this whole idea of, like, reinventing everything. [00:13:50] Speaker B: Yes. [00:13:50] Speaker A: They start, like, applying new names to things that they maybe even think are new, but they've been around. And so I think, like, marketing maybe has some. I'm going to use a term like legacy to it that doesn't necessarily align with how high tech startups work. And I think that that is why the term cohort became really popular, because I think it's more aligned with, with startups and their, like, worldview and how they, how they operate. Right. So, So I think it's cool. And this GTM engineering thing, I agree 100%. Clay and a couple other companies out there really popularize this. These tools are really complicated and you need to know a lot. So I, I talk to people a lot lately who are really excited about this. I met a guy who, like, he had a title like GTM Engineer, and he's like, did I just sit in quad code all day long and just kind of vibe stuff? And it was a. Yeah, I like [00:14:46] Speaker B: the, I like, I like what is happening to the industry. I don't think we're going to go back to like the, the madman days where men just sit around and smoke cigars and drink whiskey. [00:14:58] Speaker A: But, you know, this is I love this, actually. I, I've used this many times. There's an episode of Mad Men where they go and buy a mainframe computer. Do you remember this one? I was a giant fan of the show, actually. Remember, like, yeah, it's great. It's the best one. It's like, it's kind of like the Silicon Valley episode. [00:15:20] Speaker B: It's like. What do you mean? Meets Wesley. Yeah, yeah, right. [00:15:22] Speaker A: He's like, he's like, he's talking about media buying. He's like, oh, we do media buying, but we use a third party that has a computer. So we do buy through computer. We just don't have our own computer. And, and Draper's like, what, what are you. So he buys one and puts it in the lobby behind glass so everyone [00:15:37] Speaker B: can see that they're legit. They're. [00:15:40] Speaker A: They have a computer that's awesome. That it's like, it's like, yeah, they. Sterling Cooper moves to San Francisco and the first thing you do is like put a computer in there room. [00:15:50] Speaker B: So basically what we're saying is every marketing agency, the traditional like New York marketing agency is going to buy, hire a marketing engineer. [00:16:00] Speaker A: They should get. That's exactly what they should do. Should get a bunch of GTM engineers to sit in the front room and just be in Claude code all day long so they can like. [00:16:08] Speaker B: That's right. All right, I think, I think, I [00:16:10] Speaker A: think, I think we've nailed this topic, actually. Okay, let's move on to the fake GitHub Star economy. This one is fascinating to me. [00:16:21] Speaker B: Okay, so like, I don't know if people know about this, but on GitHub, which is a platform that software people use open source projects and software people use to host their code base. And like VC specifically used the concept of stars. Stars is just like people bookmarking this repo as a way to gauge if a. A project is popular or not. So a lot of the founders and open source projects kind of like figured out that this is something that VCs care about and they started gaming the ecosystem. So a report came out that says there's a whole entire underground market of buying and selling GitHub stores. [00:17:06] Speaker A: All right, so you go to your repro, so it's okay. So GitHub is a place where engineers like upload code. That's right. And then it's got all kinds of like social networking features. Right. So if you're not familiar with it, like you can have a company and you can belong to the company, right? [00:17:19] Speaker B: Yeah, that's right. Just like, yeah, organization. [00:17:22] Speaker A: It's LinkedIn for people that are even more nerdy than like people that go on LinkedIn. [00:17:26] Speaker B: Yeah, that's right. [00:17:27] Speaker A: And then so your, your is the. Is the. Are the stars for your project? Are they project level? [00:17:33] Speaker B: Yeah, they're project level. So project. [00:17:35] Speaker A: Right. [00:17:36] Speaker B: Project level. [00:17:36] Speaker A: There's so yeah, it's very obvious, right? Like oh, this is the cool project that I found on there and I'm like using some of the source code, I'm going to give it stores. And so the idea that people would game that is totally logical. [00:17:47] Speaker B: Of course. Yeah. There's a good wins law which is if you make any metric measurable and you try to make that the target, it will be gained. Sorry, Good heart's law. Like so if you make GitHub stars a metric that you care about, if the VC says hey, I want to see 10,000 stars on this repo before I invest a hundred thousand dollars. There are an entire economy will form around. [00:18:17] Speaker A: I think, I think there's like a specific. I didn't look this up. I think there's a specific project that [00:18:23] Speaker B: achieved [00:18:25] Speaker A: a certain number of stars in a certain period of time that no one had ever done and they forgotten it got like the attention and raise a bunch of money. I think that's exactly where this came from. I forgot that someone was open. Was there something before that though? I mean, Open Claw is a great example. But we know it's not fake, right? But, but Open Claw was popular. There was, I. There was someone who created something and it was like a very. You know, because like Open Claw has a like a user experience kind of thing that people can like touch. There was a repro where someone got like a bunch of stars and it got really big. Anyway, it's. It makes sense that that would be gamed now. But I, I was, I guess I was like a bit surprised when I read this. Like, and then, and then I thought about it. I was like, of course it's not surprising, but it's because vcs are gullible. You said it. You said it. [00:19:19] Speaker B: I'm gonna come. I say it. Like a lot of VCs has no idea about anything. [00:19:24] Speaker A: So I mean, you know, we know that the. There's like, there's fake content all over the Internet, right? Fake reviews, fake Yelp stars, fake Reddit posts, fake AI generated LinkedIn comments. Right. So the idea that like GitHub would have a star economy where people are buying stars, like you buy Twitter followers in the old days and stuff, it's Totally logical. I mean, they'll clean it up and they'll try to get rid of it. And it'll be really apparent too, when you go in there and you're like, it's. You don't think so? [00:20:00] Speaker B: No. Okay. So like, you have to look at the incentives, right? Like, what's the incentives for them to clean this up? There's a lot of questions for them to clean up. Social media is with like on X, there's some incentives with the bot traffic because that deprecates the. That makes the ad dollars. [00:20:19] Speaker A: So they claim. [00:20:21] Speaker B: So they claim. That's right. [00:20:24] Speaker A: The only place, right? Like, oh, my God, dude, like, Elon made such a stink about the bots. Then he bought it and he looked at all the data and like, basically hasn't said a word of the bots ever, ever since. No, it's all real, believe me. Oh, my God. [00:20:43] Speaker B: The only platform that actually click legitimately cleaned this up is product. [00:20:48] Speaker A: Okay? [00:20:48] Speaker B: Product on, legitimately cleaned up a lot of the, the, the body and the fake stuff. But then what happens is I'm kind of like revealing the secret all but a real human economy formed around. So that's. [00:21:03] Speaker A: You and I have talked about this too, right? So we need a law for this. This rule which is like. It's like. I would call it maybe the whack a mole rule. So when you clean up, like the, the. When you clean up, let's say, like fake accounts, it just creates an economy for real accounts. [00:21:22] Speaker B: Right? [00:21:23] Speaker A: Exactly. They're actual people. That's what I always called a. A Muppet account was that it's run by a real person, but it's just manipulated. And I, and I believe for a long time that, like, this is what nation states are doing and other people are doing is like, they don't use bots. They literally have like thousands of people that are employed. And I think that, like, I guess I'm getting too into this. But like, I imagine that like nation states, let's use that term, they have like, it's like a. It's like a marketing agency. They have like a leadership and directors and there's meetings and they're on this team. They're on that team. And like, it's. It's like a marketing initiative and they're just Muppet accounts, right? They go on there and they pretend to be somebody and it's all. That's why I like calling it marketing. It's not fake. It's just marketing. [00:22:15] Speaker B: It's just marketing. And then it's Just gaming gamification of stuff. [00:22:20] Speaker A: Right. They're just gaming, they're gaming the platform, but they're not violating in the terms of service. Like they're not doing anything that you're not supposed to do. It's not a bot, it's not fake. And like you and I have meetings about what we're going to talk about on this live stream. That's. That's appropriate. Right? Like I would hope we have a meeting. We don't just get on here and wing it. [00:22:37] Speaker B: Right, couples. [00:22:37] Speaker A: Okay, okay. The fake. The fake GitHub Star economy. What do we have next? [00:22:42] Speaker B: Oh, you want to talk about all birds? [00:22:44] Speaker A: Oh my God, yes. [00:22:46] Speaker B: Let's talk. [00:22:47] Speaker A: Okay, I, I have to, I have to, I have to pitch this one or present this one. So I never owned a pair of all birds. And you start with that. I did an event because someone was talking to me about this the other day. I saw a friend of mine and they're like, oh, remember that event you did? I ran. I did my first conference ever in I don't remember 20, 2014, 2015. And the founder of Albert's presented as one of the. He was one of the guest speakers that someone introduced me to before they had like launched or they were like brand new. And he was the most awesome guy. So he was a professional. Former professional soccer player from New Zealand. He was on the national team. And that was when I was like at a peak of like bicycle racing. And so we really related on all this athletic stuff. We got along really well. And so I had him speak. [00:23:39] Speaker B: Yeah. [00:23:40] Speaker A: And he, he like basically was in the process. He didn't launch allbirds at the event, but he was in the process of launching it. And it was one of the first speaking opportunities that he took on was to talk about allbirds and come on and talk about being a founder and stuff. And of course like six months later they like went ballistic because my friend was saying like, yeah, I saw that event, I bought some all birds in it. And then like six months later, they're everywhere. And you know, as like a lot of these Zerp era, let's call them trends, the, the meteoric. Meteoric rise is followed by a catastrophic decline. Right, right. For whatever reason because this is not, it's not a tech company, but for whatever reason, like their popularity followed that kind of rise and fall. And so I guess they have, they've sold the. Whatever assets are left. Yeah. Patents or copyright, whatever they have has been sold and so now they've been like rebooted. It's like, it's not really a spac. It's a reverse merger where the stock ticker is live on an exchange and some new company or new product or new group of managers, they like technically buy the company or make some strategic investment into the company so they can assume the public listing. And now it is a. What do they call it? [00:25:09] Speaker B: AI computer infrastructure. [00:25:12] Speaker A: Yeah, yeah, I'm reading the thing right here. They've $50 million convertible financing facility. The facility, which is expected to close during the second quarter of 2026, will enable the company to pivot its business to an AI compute infrastructure with law with a long term vision to become a fully integrated GPU as a service and AI native cloud solution provider. In connection with this pivot, the company anticipates changing its name to New Bird. [00:25:47] Speaker B: New Bird. [00:25:48] Speaker A: I love it. I didn't even check stock market today. Like is this thing a hundred thousand dollars a share or whatever? Like last night it was, it was skyrocketing. I should look it up. Yeah. Like everyone was like, of course this is gonna go. [00:26:03] Speaker B: Yeah, it's up, gonna go crazy. It was up maybe 800 at the highest. It was up 800% yesterday. There's no way it stayed up today. No way. [00:26:16] Speaker A: So it was trading at 2.2.57 and then it went to maybe like 1523. I see 23. And then it came down already today, like 20. And that's. It's back at 12. So you miss, you missed it, Paul. [00:26:31] Speaker B: I missed the pump. [00:26:34] Speaker A: You missed it. Oh my God. It's a, it's. This is not a good investment, by the way, just in case you're listening and you are, you aren't sure our games. I don't. [00:26:46] Speaker B: This is not investment advice. Let's, let's, let's not say good or definitely not investment advice. [00:26:51] Speaker A: I definitely don't recommend it. I'm trying to remember like which one of these pump and dumps I did make money in. There's a point where I, I would throw money at it. [00:26:58] Speaker B: Did you? [00:26:59] Speaker A: Because it was fun. Oh, I know. I actually made a lot of money in the open door stuff. [00:27:05] Speaker B: Open door, Yes. [00:27:07] Speaker A: I don't know why I was like, I don't know, I, maybe I had like a free moment and I'm like, I was actually thinking to myself, got all of the reduction in interest rates or. Yeah, no, the, the increase though. So the end of the increase of interest rates is going to create a dynamic where I think it's gonna be a lot of like distressed Property sales. I was like, open might actually be a good company. So I bought it. It was like right at the beginning and then it all went crazy on Twitter and I saw that and I wanted. I'm out of this, dude. Like, I made some money. [00:27:40] Speaker B: Yeah, yeah, yeah. It was all from one guy. Like he went to Drake's house to like pitched open door. I don't even know the story. [00:27:48] Speaker A: Yeah, the story, dude. Just for the entertainment alone, it's worth like $1,000. Sometimes I'm like, this is just. Just to like pay attention and have some skin in the game. It's been fun. So, okay, are we done with. [00:28:00] Speaker B: So summary. Do you endorse this pivot from Allbirds to Newburgh? [00:28:07] Speaker A: I, you know. Well, look, I'm. I'm always going to take the optimistic side. Like, I think that like, you know, they. They found a way to maximize the assets that they had. That's what I would say. They, they were whatever. Whatever was left. They said, okay, we're gonna. They got money for that. Great. So they, they had their shoe business. They sold it to somebody who's expert in that business. Awesome. They found a new investor who's like, I think all this public company infrastructure is valuable. So I think from that perspective, I think it's great. I even, I even think at like a high level GPU as a service is a good business. Do I think like this specific GPU as a service business is the one to go for? I met guys doing GPU as a service. Like, God, it was a long time ago, maybe two years ago, like when it was like, really hard to get additional GPUs. [00:28:56] Speaker B: It's still really. It's still really hard. [00:28:59] Speaker A: Yeah. I was like, that's a really good. So it's a sound business. I don't know if this one is a sound business. [00:29:06] Speaker B: I just think it's all a bubble. We're in a bubble. It's gonna pop. Just don't know when. All right, let's move on. [00:29:12] Speaker A: Okay, good. Well, that. That brings us to the next item. Grumpy old man. Federal Reserve Bank Conspiracy theory corner. Don't get me too riled up. Some guy, like, found me on Twitter and he started. I started. I was posting charts of the Federal Reserve bank and he like, he went after me and I was like, dude, you don't know. You're talking to man. And I went in my whole thing about, like, how Federal Reserve banks should be basically dismantled. I think we still need it. But the mechanisms that they used to like, set Interest rates are completely, they're beyond antiquated. Like we could have that all be done algorithmic. That's how most things are set now. Anyway, like, why do we have some like group of old grumpy guys that go into some corner and like magically pretend to know what to say? And anyway, so what I did want to talk about was this guy Graham Stephen, who is a like a finance youtuber and he talked about selling all his real estate holdings in Los Angeles. And this went viral. [00:30:13] Speaker B: Okay. [00:30:14] Speaker A: On Twitter he's complaining about the cost associated with it. And it's just a lot to manage and it's difficult. And my take on this was that really what he's talking about is the end of Zurb. So I think during the 0% interest rate run up over the last. I don't know, start with Bernanke, right? So it went up for. Bernanke was a Federal Reserve president for people who don't. Aren't on a first name basis with all of the ins and outs and, and the people who manage the Federal Reserve Bank. He was there. He's the one who like put rates to zero. Like boomed assets, right? Stocks, real estate, everything went to the moon. And that went on for like a long time. And I think that was primarily responsible for the fact that real estate, in my opinion, is really overvalued. I sold my home in California. I believe really deeply in this. I just thought that the whole thing was ridiculous. And like, I continue to see news items like this that like people are looking at real estate going like it's not a great investment. And what he ultimately said was that he sold the real estate because he believed he could only get like 4% appreciation and that that would be a better use of his money that I have in a home to just put it into like stocks, bonds, ETFs, things that pay 4% because you don't have to do all of the like, you know, upkeep and repairs and taxes and all of those things. So that's it. That's all I have to say. [00:31:38] Speaker B: Yeah, it sounds like a. His problem. It's just like one person. Okay, first of all, fine. It's a smart capital allocation move. Yeah, right. Like, okay, makes sense. 4%. If he's barely getting 4% from a property, put it into risk free Treasuries, bonds, savings accounts, whatever the thing. Fair. But like, it's just, I think it's a. His problem. What else is there anything to talk about? This you. Do you think that like, do you Think it's a wider problem of the system. [00:32:16] Speaker A: Well, okay, so what happens is there's all these people out there who are crazy and they spin this into like, don't ever buy a home. Don't buy real estate. It's bad. And I don't believe that. [00:32:25] Speaker B: Okay, you don't believe that. Okay, great. [00:32:27] Speaker A: No, but I don't believe it's a fantastic investment. I think that like, everyone, everyone, there's time in your life when I think it's appropriate to own a home. And the reason it's good is because like, right. Even if it doesn't appreciate all that much, you can pay down the mortgage and you'll have an asset then that you can sell. And like you had to pay rent anyway. [00:32:43] Speaker B: I believe. So really, we're just overcorrecting for the over investment. [00:32:50] Speaker A: Yeah, it's the Federal Reserve bank did it. [00:32:57] Speaker B: Fair enough. [00:32:58] Speaker A: The Fed did it. [00:33:00] Speaker B: Just blame it all on the Fed. Fair enough. You know, Fair enough. [00:33:03] Speaker A: All right, Nobody, nobody wants to hear about this anymore. Let's just, let's just go on. [00:33:08] Speaker B: So like the same thing is happening Toronto. Right. Like, there's a lot of like, right. Leaning newspaper that's coming out and say, hey, this investor lost, let's say half a million dollars on buying condos in Toronto. [00:33:23] Speaker A: Yeah. [00:33:24] Speaker B: That they can't close on it. Do I feel bad for them? A little bit, yeah. They lost half a million dollars of their savings or their money. But at the end of the day, it's like you bought a 400 square foot condo for almost a million dollars. That was a terrible decision. [00:33:43] Speaker A: Condos, there's a whole different. So that there's. In most places, condos are on the decline. So. Okay. Actually I can tie it back to like business general condos. I think they tend to be a bad investment because developers can always build more. There's no, they're the, the, there's supply and demand dynamics mean that when you buy a condo, they're not likely to go up because people can build newer, better versions of it. Single family homes in the United States just be very specific in certain areas, not everywhere. They tend to go up because it's very hard to build more of them. That's it. It's supply and demand. There's nothing else. So the condo market doesn't have the same supply and demand dynamics that single family homes do. And it doesn't apply everywhere because I looked at this one point, like there are these distressed single family homes in like the Midwest, like in Kansas or something, and they're they can't be sold or the market doesn't like, ever turn in favor of ownership because they're so far from anywhere. That way you could like, get a job. Like, you'd have to be some kind of remote worker who wants to live somewhere really far from like a major even airport in Kansas, which would make it really difficult even to be like a. Yeah, we had that, I don't know, remote GTM engineer or something. [00:35:07] Speaker B: Right, we had that. We had like a cottage country boom in Canada during COVID Yeah, during COVID So people bought like two, three hours outside of the. The city centers for like regular city housing price and they got burnt. [00:35:25] Speaker A: I mean, yeah, there's. That's like just vacation real estate. Those markets are very susceptible to volatility depending on. [00:35:33] Speaker B: Yeah. Economy Realize that like, you know, return to office is a thing. Do you want to drive two, three hours a day to your office? Probably not. And now you know. Yeah. [00:35:45] Speaker A: All right, all right, let's go on to. Actually, this is a nice segue into this LinkedIn data story. [00:35:51] Speaker B: Okay, tell us. [00:35:52] Speaker A: So, yeah, lots of people are talking about. Talking about layoffs. Right, Right. Lots of. There's lots of left, actually. I read the aggregate statistic was like, there's been a million people laid off in tech over the last year and a half or two years. That's a big number. [00:36:04] Speaker B: Who recently? Snapchat recently. [00:36:07] Speaker A: Yeah, they had layoffs this week. Right. Thousand people. [00:36:11] Speaker B: I did not know that. They. Apparently that's 10% or 16%. Did you know that 5,000 people worked at Snapchat? [00:36:22] Speaker A: The numbers are so that. So, okay, so that's what this. [00:36:26] Speaker B: 5,000 people. [00:36:28] Speaker A: Oh, my God, dude, 100. So that. That's what people are saying with the block layoffs. So, like, if you compare block to companies that are like in a similar space like Robinhood, they have. They have like half the employees. [00:36:43] Speaker B: Okay. So yes, it's bad for thousands of people getting laid off. But like, why do these people. Why do these companies have tens. [00:36:50] Speaker A: Yeah, they way they completely over H place. I know, it's crazy. So that's what this. So they. I think he's like the CFO of LinkedIn. I just want to make sure. Yeah. Oh, no, he's the chief. Oh, this is interesting. Chief Global affairs and legal Officer H. And he's weighing on this. He's saying that, like, LinkedIn data shows that it's not really AI. That was. That was interesting, you know, which I believe. And I believe, like, what you're saying too, is that we over hired companies. Over hired. They have too many people. I guess they did it because they thought Covid was going to go on forever and the exponential growth would just continue. [00:37:38] Speaker B: Yes. The chart saw that all of these Internet companies, e commerce, Internet usage companies, social media saw like a massive spike. Right. They thought that it was going to go on forever. A really good example is Chess.com so like during the pandemic, Chess.com like 4x in terms of like daily usage. And they got. So they're what they're lucky is that first of all they're not a public company. Neither are they VC funded. They're kind of like bootstrapped. So they didn't have the pressure to grow. So they didn't. I don't know if they hired. [00:38:14] Speaker A: They've been like a hire a bunch of. Yeah, that happened in a bicycle industry. So during COVID way more bikes than ever were sold. The numbers are astounding. And all the guys knew that worked like bike stores, stuff. Like they knew for sure. So those guys knew for sure that it's Covid. Like it was, it was pretty apparent. And it went on for like way longer than they had thought. Like they were out of bikes. They couldn't get more bicycles. And that industry, you know, I guess like the bike industry is pretty old, right? 100, 100 years. Right. So the factories and the manufacturers actually refused to increase production capacity. I think it's actually very difficult to increase capacity of a bicycle manufacturing plant. They're like, that's all we can do. We're not going to add more. They didn't go around building bicycle plants everywhere and they were 100% correct. [00:39:09] Speaker B: Is. Is the best bikes made in Italy? Is that a thing? What's. [00:39:14] Speaker A: Dude, they're made in Taiwan, man. [00:39:15] Speaker B: Okay. Of course, of course. [00:39:17] Speaker A: Like all. Basically they. This, this is really off topic but like bicycle manufacturing, the carbon fiber technology, they are like the best at it in Taiwan. And I think like is it a Taiwanese brand though? My understanding is like there's one or two factories that make all the brands. [00:39:35] Speaker B: Of course. Of course. [00:39:36] Speaker A: And, and like the Italians like get it made to spec and then they deliver the carbon. Different brands of different things. They deliver the carbon like basic frame model to Italy and then they, they finish it there and stuff. [00:39:48] Speaker B: Right, right. So it's like yeah, it's like mating Taiwan assembled in Italy. So it's probably just a bunch of. [00:39:54] Speaker A: Yeah, actually this is super interesting where it relates to like a lot of things we talk about is in bicycle design. They have very sophisticated AI powered software that can simulate any environment and simulate racing and riding. Yeah, because of this software. So these is like wind tunnels now. They don't have to do that. They have legislation software. It means that the design of all bicycles is converging on the same design. So basically there's only one design that's more aerodynamic than all the other ones. So all the differentiation in terms of like the look and feel with manufacturers, if you, if your focus is to make the fastest bicycle, they all look the same. Which is why like there's like one or two manufacturers now, because everybody basically wants the bikes to look almost identical. And they do some like small things here and there just to kind of give it, you know, branded elements or make it unique and interesting, but you can't get an advantage in the design to make them go faster. And I actually think this, the reason I brought this up is like I believe this phenomenon exists in a lot of places. I think this is even in marketing, like at a high level a lot of like marketing thing is converging onto the same approach because that's what works the best. I really believe that different categories of course I think work differently, but there's a certain type of like thing that works. And like going back to our original conversation, there is more data and more measurement than we've ever had. And on the consumer side they do get a lot of data. So consumer startups, consumer brands, anyone selling a consumer product on LinkedIn, on Instagram, they do have enough signals to optimize that in a really data driven way. And I think that's why like the products and the advertising and marketing, it's all converging on very similar type of product approach because like it's similar like the bicycle design as an analogy where there's only one way to be more aero. And so that's why everyone looks like that. I think at a high level that's happening in a lot of things in business and in life. [00:42:01] Speaker B: It's because we're optimized something so well that we're hitting what physical units. [00:42:08] Speaker A: We're actually really good at optimizing things and we have really good data that's actionable at scale and we have tools that can do it. And so it means that like there's only one solution. There's not like multiple solutions. [00:42:19] Speaker B: Right until big breakthrough happens. [00:42:22] Speaker A: Yes, it took me a while to wrap my head around it that like, oh, there's only one design that's the ultimate in terms of aerodynamics as a bicycle like when you think about it, it's actually quite logical. Yes. And then I realized this. Yeah. This and this probably exists in a lot of things. I don't think it exists in everything, but I think it exists in a. Yeah. Yes. [00:42:43] Speaker B: So like for example, ev. Right. That battery tech we're. You don't have really, really good wearable. We talked about this in the last week show. Yeah. Is because we're limited by battery tech. Right. So we, we don't have like supercomputers in our ear yet can power it. There's no way to do it. [00:43:02] Speaker A: I got a super computer up here, buddy. [00:43:03] Speaker B: Talk, talk, talk between your ears. [00:43:06] Speaker A: Talk about yourself between the ears. Come on. [00:43:12] Speaker B: Okay. [00:43:12] Speaker A: Okay. LinkedIn data AI. Hi. What do we have next? [00:43:15] Speaker B: We gotta. [00:43:16] Speaker A: This is yours. The AI bubble. So you think we're at the peak. Peak AI. [00:43:21] Speaker B: I think we're. We're at the peak or very near the peak. So let me, let me like justify with, with a couple signals I'm looking at. One is the companies and the people that they're hiring, the way that they're talking about token maxing is starting to diverge. So companies at enterprise level, at the leadership level, let's say, are starting to feel like why the heck are we spending $10 million a year on tokens when we can't, definitively, you know, tell if this is increasing our productivity or increase our revenue. However, all of these foundational model companies like OpenAI Claude Anthropic, of course they want you to maximize in token spend. They spent billions of marketing says, hey, telling both the business leaders and the software developers or you know, the workers, if you're not spending $10,000 in token budgets a month, you're going to fall behind. Jensen Hu famously said this on V of the all in episodes as well. Right. Like he's framing it. You have to Token max. Yeah, of course I think the incentives are not aligned. The, the reality is not pointing to this. So one is the dollar budget behind Token is not turning out the productivity gains. So the worker themselves think that they're getting. Let's say they have to say that they're getting too. [00:45:01] Speaker A: This is why I didn't do a COD bot. Like I talked to everybody and I got really excited about it. I like almost pulled the trigger on this thing. [00:45:08] Speaker B: Right. [00:45:08] Speaker A: And then at the last conversation with somebody, like I literally had my finger on the button and he's like, dude, I'm spending thousand dollars a day on. I was like, what? When I heard that, I went like, exactly Forget it. [00:45:20] Speaker B: So it's. So the people who's doing that are like fanboys, Right. They're all. [00:45:25] Speaker A: Yeah, they're enthusiasts. And of course, you know. [00:45:28] Speaker B: Yeah. Like a new trend hits. Like, what's those collectibles, Labu? Like, people spend thousands of dollars collecting those things. It's a trend, it's a fact. And then there's like real enterprise people who's like, looking at this, the CFOs, let's say, are looking at this. They're like, this doesn't make sense. [00:45:48] Speaker A: And then I think this is, I think it's exactly how the AI bubble pops. I agree. [00:45:52] Speaker B: Right. Once the adults, like the CFO get [00:45:55] Speaker A: into the room, it starts to work at scale and then people are like, where's all the cost savings? And like, oh, it's actually more expensive. And we're beholden to two or three companies. We can't just like hire any employee we want and have more flexibility. [00:46:08] Speaker B: Correct. [00:46:08] Speaker A: I think it's going to end up being a lot of drawbacks. [00:46:10] Speaker B: Correct. Yeah. So the only thing that's holding back this bubble right now is people are still saying, I would spend $10,000 a month in AI, get 2 to 3x boost. It's still cheaper than hiring another developer. Right? That's the only logical argument. [00:46:28] Speaker A: Yeah. Well, that's why software and development is one being the most disrupted. [00:46:33] Speaker B: Correct. [00:46:34] Speaker A: Because they were all very high paid, very difficult to deal with. My personal opinion. [00:46:39] Speaker B: Correct. [00:46:40] Speaker A: And in short supply. And so that is being challenged. But I think in a lot of other. [00:46:46] Speaker B: Yeah. [00:46:47] Speaker A: So this, we've talked about this before too. This came up like a long time ago. Like a lot, not just marketing, but a lot of other areas in companies like the employees are cheaper than engineering. Right. So like, it doesn't necessarily make sense to replace somebody. I mean, that was. So when I was looking at Clawbot, I needed help with like my newsletter and some things and I, I looked this and I said, can hire someone in upwork for like a fraction of this. And that's what I ended up doing. I went and got someone that I've actually worked in the past. I didn't hire my upwork, but I love working with and it's been fantastic. And it's way cheaper than a cloud bot. And I don't have to like deal with all of the maintenance and upkeep and security risks and all of that. [00:47:28] Speaker B: Exactly. So like two things. So either software cost, hiring a software development cost is going to dramatically decrease and pop the bubble, or I think it's the other way around, which is people are going to start realizing that they're not actually getting, getting 2 to 3x productivity. [00:47:47] Speaker A: Oh dude. I think it's so obvious like what happens. Like look, I've been through more bubbles than I care to like admit, right? Like I saw the dot com bubble. I remember like the Web 2.0 excitement. I remember the mobile bubble which was the most fun. That was my favorite one personally. [00:48:07] Speaker B: Nice. [00:48:08] Speaker A: I've seen three different AI like bubbles perhaps. Yeah, so, so this one is really interesting. Like I think there is a real core invention like driving this. Like of course the technology that they have is, is quite remarkable. Right. But like a lot of new technology, like I've seen this happen. Like the most like remarkable technology isn't all always great in terms of driving business. It's not always ROI positive. [00:48:37] Speaker B: Yeah, right. [00:48:38] Speaker A: And so I think when like one, like maybe when they both go public, I think that'll pop the bubble actually. I think like they'll go public. They've raised so much money that like I don't even understand how the public markets absorb these companies. Like who's going to buy shares in Anthropic or OpenAI believing the companies are going to be worth more? How much more could they be worth? They're almost worth more than every company in the planet. Right? Like these companies are valued at, they're not like valued at 50 million or 100 million. They're, they're, they're like billions. Insane. It's insane. [00:49:15] Speaker B: Open AI is going to go onto the market for trillion, right? [00:49:18] Speaker A: It's like basically one of the most valuable companies in the world. And the way that, at least the way I understand it, the way you make stock is like the company has to be worth more for your stock to be worth more. So do I believe OpenAI is going to be like go up 10 times? No, no, I don't think that, I don't think so. [00:49:35] Speaker B: So we'll, we'll, let's see, my timeline prediction is we'll know we'll have some kind of signal in the market noise in about a month. I think that's the timeline. [00:49:45] Speaker A: I think your time frame is actually dead on. I think this whole year there's going to be a lot of experimentation, there's a lot of interesting things happening, but by the end of the year we'll have a good sense of like. Yeah, yeah, yeah, I, I'm with you. [00:50:00] Speaker B: Okay. [00:50:01] Speaker A: Okay. This is mine. AI writing. I'll just go over this quickly because I had this interesting exchange with somebody recently, but they just kept complaining that what I had written was AI. And it was an odd conversation because, like, oh, it's too AI. I'm like, all right, I'll go and edit it a little bit. And I edited it, and [00:50:24] Speaker B: they were [00:50:24] Speaker A: like, this is still too AI I was like, okay, let me see what I can do. I know. I just like, whatever. And then finally I wrote them back and said, like, look, I wrote this from hand. Like, I've been, like, writing, let's call it, say, professionally for, like, 15, 20 years. Yeah, of course it sounds and reads like AI because AI is trained on all the stuff I wrote. I write like AI it's not the other way around. And it was, like, an interesting discussion. It didn't go any further than that, right? So I was just like, I don't know if we're a good fit to, like, did you. [00:50:57] Speaker B: Did you use too many EM dashes? [00:50:59] Speaker A: So that's the funny part, right? And I. I posting on Twitter where I was like, okay, in my opinion, this is what I think crappy AI slop writing looks like where it's, like, riddled with emojis. They don't use complete sentences, or they maybe go back and forth between completences. They don't use proper paragraph structure. It's just junk, right? So, like, if you're doing all of that, meaning, you're writing, I think, in a grammatically correct way, you're using professional language, you use proper paragraph structure, you're communicating in what's a professional manner? Like, how can you say it's AI or it's not AI? There's a few tells, like M dashes, and there's all these delves and stuff, but, like, everyone's figured out how to remove that from it. So I don't. I don't even know. When you get to that level, does it matter anymore? Right? Like, I don't know the answer. Actually, the other funny part was, like, last thing I'll say is, like, every draft I submitted to this person past every single AI detection tool, and they wrote me back and told me that because I wrote it. That's how I know it passed. They're like, oh, it's passed all. I'm like, yeah, I imagine it would pass because, like, I wrote the thing. Of course it passed. But now we're in this place where, like, if you write in a professional manner, you're basically writing like AI. [00:52:30] Speaker B: Yeah, fair that I. I see. I see this is super interesting because, like, it's. It doesn't really matter if you use AI or not. You just need to know who you're writing for. Maybe it is a generational thing. So, for example, if you're writing proper grammar, right. On Reddit, that the audience will think I do that. Right? [00:52:54] Speaker A: Is that. Is that what people think? That's obviously, they think. They think you're old. That's. [00:52:58] Speaker B: That's right. Well, like, I don't want to say it's old. Right? Like, for example, on. Maybe. Maybe it is a generational thing, but for millennials. For millennials, right. If you're just, like, looking at a piece of content. I want some kind of proper grammar and paragraph structure. I. You know, X. Sometimes you see where it's like, two words per line with spacing. I'm looking at this. I'm like, who. Who. Who talks like this? Who. [00:53:28] Speaker A: Who writes like, dude, I do not. I. I don't. It's called. Oh, my God. It's called a broem. And it was like, it sounds created. I actually know the history of this. There's a guy, it was like, 10 years ago, I met him. He. He was one who invented that, like, weird format on, like, LinkedIn. And he invented it because, like, it was a way to gauge the algorithm was fairly simple at the time. And he invented that, like, to game the algorithm. Yes, and that's where that came from. [00:53:56] Speaker B: Okay. So, interestingly, I think that the algorithm, the social media generation, all of their writing is literally to game the algorithm versus maybe, like, our generation. We grew up with, like, proper. Like, our. Our entire. My entire writing was to game my English teacher. So for them, [00:54:22] Speaker A: exactly, you know, oh, my God. [00:54:25] Speaker B: What would my, like, grade 12 English teacher will work per, like, mark for my English writing would be. And definitely not the two words per line. Tweet. [00:54:40] Speaker A: No, I hate that. I always did. I always like the younger generation. [00:54:43] Speaker B: Like, I get that, but the younger generation, they're. They're. They're like, that's their criteria now of good writing. Yeah. [00:54:53] Speaker A: I used to be, like, really against this stuff. And then I. I've kind of, like, softened my approach on this. Like, I hated the fact that, like, texting and, like, texting style started, like, being incorporated into the business world. Like, I found that to be. That was a long time ago. I was like, this is wildly inappropriate. I. I kind of, like, kind of got with the program, but I'm still against it. And I hated all of the emojis being used, but now they're, like, built into, like, asana and notion. Like, you kind of have to use them. [00:55:27] Speaker B: Okay. [00:55:28] Speaker A: And so, I don't know, I feel. I feel like I gotta. I feel old. [00:55:35] Speaker B: Okay. This is cool. Because when I first started working, writing an email was a scary thing because, like, like the professional email writing language is like very formal. Yeah. But then over the last 15 years, I realized my generation started becoming more and more, you know. You know, we're becoming founders, we're becoming CEOs and CMOs. Email became drastically more casual. Right. [00:56:07] Speaker A: You can use business. I mean, the whole world, not just business, everything has become more casual over the last, like 20 years. [00:56:13] Speaker B: Right. I think that's probably because my generation grew up on text. It's a lot of condensed, semi formal, not very formal. [00:56:20] Speaker A: I don't even. Dude, I don't even know the full. I flashed all. I don't even know the full explanation. I. Some of me thinks that it's the success of technology companies. So when I first got into high tech, it was a very niche kind of west coast thing that, like, people in New York did not take all that seriously. And these companies were not the biggest companies in the world. And then that has all shifted. Right. So all these companies are just like, incredibly successful. And so, like, all the cultural things that they adopted have become mainstream. [00:56:54] Speaker B: Is. [00:56:54] Speaker A: Is like the most, like, boring, probably accurate explanation of all this stuff. [00:57:01] Speaker B: Right. So west coast culture kind of permeated America a little bit. [00:57:05] Speaker A: All business. So the business isn't. So I remember in San Francisco, like, I don't know, 2015 or 16, when people were like, moving their headquarters from New York to San Francisco. [00:57:18] Speaker B: Yeah. [00:57:19] Speaker A: And they like, they're like, we got to get cool and like, use emojis and emojis free. It was kind of funny. I was like, oh, interesting how this is all. All playing out. Yeah, it, you know, the. The evolution of communication. This stuff happens. Right. And what was perhaps formal becomes antiquated and what was informal because you look at stuff that's written like, along, like the 19th century. Like, it's written in a much more formal way than, like, I even like to understand to some degree. I don't really. I don't even. I don't. I feel like I know that I'm missing stuff because it's so formal and so different than how we communicate today. So I don't know. This leaves us with like, AI content. I think it just devalues. Writing in general is what I think happens. So if everyone can like, write. This was my take with, like, when it first emerged was like, with marketing that AI means like everything that was done in a very professional manner that was, it was hard to do now becomes a commodity. And that was one of the reasons I, like, I made a lot of adjustments to my personal image, like to make it more casual on purpose. [00:58:31] Speaker B: So do you think it will come in waves? So, okay, for example, music. Right. Music is always, you know, 2000s right now is coming back. Do you think writing will have the same kind of cycle? [00:58:49] Speaker A: I don't know. It's really hard to say. [00:58:51] Speaker B: Yeah, it's really hard to say. [00:58:53] Speaker A: I think the tools are just going to get better and better and there's going to be. So I guess, okay, I think in two or three years this won't be an issue anymore. I think everyone's. Except that we have AI and it does writing. And so you just need to write in an appropriate way. And if it's AI, whatever, it won't matter. [00:59:12] Speaker B: I, I get that. Right. [00:59:13] Speaker A: Like, that's the thing. That's the thing. What happens like long term is it just becomes something we do. Like, like no one says, like, did you hand calculate this and do long division? You're like, of course not. [00:59:25] Speaker B: Yes, but then how do you influence what people read? Right. Okay. [00:59:31] Speaker A: I think reading is going to become less popular. I think a lot of like writing will be lost as an art form. Yeah, I really believe that. As someone who, like, I'm really passionate. I love writing. I don't love reading. [00:59:41] Speaker B: I love books. You can't get the same types of informational falls off that basically we means that we. [00:59:50] Speaker A: Dude, people look at the numbers, man. People are reading way less. It's going to be like a lost art. Like another 25 years. Like people that like, write. [00:59:58] Speaker B: No, I don't, I don't believe that's [00:59:59] Speaker A: going to be like a very niche, niche thing. [01:00:04] Speaker B: No, I don't believe that. I think, I think it's, it is a generational thing. I think even with the J's, they're peaking with the, the social media. [01:00:11] Speaker A: But dude, no one reads books. Not that everyone ever did, but I think no one reads books now. [01:00:19] Speaker B: Okay, So I, I was no 1. [01:00:23] Speaker A: No 1 reads white papers anymore. I used to like write and read white papers, believe it or not. Like, I've just given up. Like, I don't think anybody cares. I don't think anyone reads them anymore. I even was looking at a research report today that actually had documented this. [01:00:37] Speaker B: Yeah. [01:00:37] Speaker A: That like white papers are not popular. I don't think people read like they used to. I think the Future is going to be video content. Like what? Like our live stream, like YouTube video. Like, I think it's going to be audio and video. I think that's going to be much more popular. I think like Mandami and like his videos is a huge part like why he got elected. I think that's the future of like a lot of communication. [01:01:02] Speaker B: But the, the problem with that is like, it's not a very good way to encourage people to do critical thinking. [01:01:10] Speaker A: I'm not saying I like it. [01:01:13] Speaker B: I get it, I get it, I get it. I'm just like, my opinion is that you need both, right? Like you should read so that you can think about stuff. [01:01:21] Speaker A: Of course people should read. People should eat their vegetables. People should go to the gym. Anyway. Okay, Cloudflare, you've got. Is this, is this a security thing? [01:01:31] Speaker B: Yeah. I'm just going to wrap it up with Cloudflare. Okay. So it's super important because I do think Cloudflare is becoming really, really fast. The only company that matters for developers if they're building with AI. I'm not going to get deep into it because I still, I myself has not dug through everything that they've released this week. This week is cloudfler's agents week. They've released maybe like half a dozen tools to help developers build faster, build better, build more secure AI agents directly in the cloud. Stepping back a little bit, there's really no company that's solving this problem besides like infrastructure level companies like AWS and Google Cloud, they are now solving problems that developers building AI have. No other company has been doing this. So very, very cool. I think this is actually kind of like falls into everything that we talked about today, which is like the peak bubble, peak vibe coding peak. People just kind of trying to prompting junior their way into a product. This is what real engineering building with AI building 4 AI looks like. So I'm really excited to dive into everything they've released. They did not sponsor me. [01:03:07] Speaker A: I've already moved on in my head. I'm looking at the final meme of the meme of the week. [01:03:11] Speaker B: All right, let's do it. [01:03:12] Speaker A: Can we, can we, can I share it here? Let me, let me share it here. Yeah, you got it. Maybe because this meme is perfect. [01:03:25] Speaker B: What is this week? All right, give me a sec. [01:03:30] Speaker A: I got, I got it. [01:03:31] Speaker B: Cut. Okay, [01:03:34] Speaker A: there we go. Has Nike considered pivoting from shoes to AI data centers? I think that, I think that is excellent. That's not a great chart, huh? What if that's a Five year chart. Oh, my God, what a company. [01:03:54] Speaker B: Oh, my God, what a company. What a fall. [01:03:56] Speaker A: Oh, it's so painful. I can't even. I can't even talk about it. [01:04:00] Speaker B: Yeah, man, they pivot to AI. That's what good companies do. [01:04:04] Speaker A: Final words, you know, I got the startup pitch competition coming up on May 12th at Entrepreneur first in San Francisco. I'll start reviewing. I'm gonna look at all the decks. We have five slots for pitches. It's gonna be awesome. There'll be 10 slots for demos. A lot of people are interested in demoing. That's cool. So I'll start to look at those stuff, then start sending out a few. Let's say, start to determine who the selection is going to be for that. And then we still have the space at Snowflake in September, which people have been signing up for. [01:04:38] Speaker B: Awesome. [01:04:38] Speaker A: I want to do another event at the end of the year. I'm trying to think like, if November, I haven't found a space and so it'd be like two months after. But I think it's worth it. I wanted to do four. I want to do one a quarter this year. So I'm still trying to plan for like one more. I haven't really decided exactly what it's going to be like. TechCrunch is too close to the Snowflake event, so have to find some other, other opportunity. But I think November will be good if I do it. If we get it done before Thanksgiving, I think people will be excited. [01:05:16] Speaker B: Very cool. I'll be at the next one you'll [01:05:19] Speaker A: be in San Francisco for. In May. [01:05:23] Speaker B: In May, yeah. Beautiful time to visit and have you, [01:05:26] Speaker A: of course, interested in attending, like go to Aluma and sign up the links all over the place. Yeah, I'll send it to you. We can't post them on social media anymore because it doesn't get any traction. So I don't even bother. I just tell everyone, like, send me a message, reply and I will send to you. All right, Paul, are we done for the day? [01:05:45] Speaker B: We're done. [01:05:46] Speaker A: Thank you. [01:05:46] Speaker B: Later, guys.