1 00:00:01,000 --> 00:00:01,930 Brian: By the way, how's Canada? 2 00:00:01,930 --> 00:00:04,329 Ha How are your relatives handling this? 3 00:00:04,420 --> 00:00:05,320 Troy: pissed, man. 4 00:00:05,320 --> 00:00:05,500 They're 5 00:00:05,739 --> 00:00:06,970 Brian: I know they really are. 6 00:00:06,970 --> 00:00:08,079 Like, this is like, 7 00:00:08,202 --> 00:00:09,131 it's kind of crazy. 8 00:00:09,131 --> 00:00:10,169 Troy: Don't poke the beaver. 9 00:00:12,195 --> 00:00:12,485 Brian: Okay, 10 00:00:13,170 --> 00:00:15,450 on that note, let's get started. 11 00:00:38,248 --> 00:00:42,418 I always forget to say welcome to people versus algorithms show about 12 00:00:42,538 --> 00:00:45,238 media, technology, culture. 13 00:00:45,816 --> 00:00:50,796 I'm coming to you with AirPods joined by Troy Young and Alex Schleifer. 14 00:00:51,486 --> 00:00:55,126 I wanted to start this week by talking a little bit about abundance. 15 00:00:55,431 --> 00:00:57,471 Have you guys, I, I got my copy. 16 00:00:57,531 --> 00:00:58,911 I haven't started reading it yet. 17 00:00:58,911 --> 00:01:03,051 It's a new book by Ezra Klein and Derek Thompson. 18 00:01:03,621 --> 00:01:09,531 The DC dork set have been waiting for this, like with bated breath, like, and it's landing at a great time. 19 00:01:09,531 --> 00:01:09,801 Right? 20 00:01:09,801 --> 00:01:19,401 Because the whole book is about how progressives in, in particular need a, a more positive agenda to put forward 21 00:01:19,461 --> 00:01:23,831 to counter obviously what they're losing right now, which is supportive people. 22 00:01:24,401 --> 00:01:30,701 One poll that came out recently had the approval rating of the Democratic Party at 27%. 23 00:01:31,631 --> 00:01:32,471 That's low. 24 00:01:32,621 --> 00:01:33,431 That's not good. 25 00:01:33,941 --> 00:01:40,311 So they're advocating for a pro-growth, progressive agenda that shifts away a little bit from redistribution and, 26 00:01:40,311 --> 00:01:45,471 and focuses on building more, more housing, more infrastructure, more energy, more innovation, et cetera. 27 00:01:46,101 --> 00:01:46,821 And. 28 00:01:47,271 --> 00:01:50,871 I think this is an interesting marketing challenge and I wanna sort of then weave 29 00:01:50,871 --> 00:01:55,791 it into the media industry, which I think needs its own abundance agenda. 30 00:01:56,271 --> 00:01:58,431 Troy: I thought I had an abundance agenda already. 31 00:01:58,821 --> 00:02:01,431 Brian: Well, I think it needs a different abundance agenda. 32 00:02:02,211 --> 00:02:04,911 There's, there's an abundance of like SEO content. 33 00:02:04,911 --> 00:02:05,481 That's true. 34 00:02:06,141 --> 00:02:06,561 But 35 00:02:06,591 --> 00:02:10,911 Troy: that Alex, were you in the 27% in support of the Democrats? 36 00:02:10,911 --> 00:02:12,471 You found that they're doing a good job? 37 00:02:13,046 --> 00:02:13,586 Alex: Yeah. 38 00:02:13,676 --> 00:02:16,286 No, I, I was, I wasn't, I don't think that I'm, I'm not surprised. 39 00:02:16,286 --> 00:02:21,716 I think everybody, even people that will 100% vote Democrat don't seem to be happy with them. 40 00:02:21,836 --> 00:02:25,826 I'm surprised that they're, I'm surprised anybody can say that they're doing a good job. 41 00:02:26,846 --> 00:02:32,306 Like whether, you know, I mean, whether it was like Schumer agreeing with Schumer or not, it was just all a mess. 42 00:02:32,306 --> 00:02:34,196 They don't look aligned on anything. 43 00:02:34,856 --> 00:02:36,776 They're not reaching out to people. 44 00:02:37,886 --> 00:02:39,116 They seem confused. 45 00:02:39,616 --> 00:02:45,399 The Gavin Newsom podcast, like they seem entirely split on, on that as a strategy as well. 46 00:02:45,399 --> 00:02:51,879 It, it, you know, meanwhile, I think the Republicans look like for whatever it's worth, are totally behind the sky. 47 00:02:51,879 --> 00:02:54,309 So it, it, you know, it looks weak. 48 00:02:55,404 --> 00:02:58,974 Troy: Hey, do you think the book I mean the timing is extraordinary. 49 00:02:58,974 --> 00:03:01,884 What a, what a what a dream for the publisher and for, 50 00:03:02,464 --> 00:03:04,564 Brian: And a great duo, you know, 51 00:03:04,674 --> 00:03:07,818 Troy: it, for those guys, but maybe it should be called The Naive Agenda. 52 00:03:08,087 --> 00:03:08,357 Yeah. 53 00:03:08,440 --> 00:03:11,327 It's like, well, these are big ideas, right? 54 00:03:11,327 --> 00:03:17,747 To, to shift, you know, our thinking to a build mindset, to outcomes, to 55 00:03:17,747 --> 00:03:24,067 making you know, this, to, to, to making government effective, right. 56 00:03:24,097 --> 00:03:26,947 Making the bureaucracy effective, but like, has it ever been effective? 57 00:03:28,492 --> 00:03:33,262 I mean, isn't like, it's great if, if the government can, can, can make more 58 00:03:33,262 --> 00:03:38,632 things for more people and make more people happy and we can do all the things. 59 00:03:38,752 --> 00:03:46,432 I mean, there's complete alignment on many levels with what I, what what Ezra would say is that the, there's, there's a 60 00:03:46,432 --> 00:03:55,519 kind of a build priority or kind of build agenda, and then there's the mo moral kind 61 00:03:55,519 --> 00:04:00,949 of decision making that informs, you know, what is the right thing to build and do. 62 00:04:00,949 --> 00:04:06,019 And that the liberals are, are better equipped to make good, good kind of moral decisions. 63 00:04:06,469 --> 00:04:09,109 But like it that it feels like. 64 00:04:09,304 --> 00:04:11,824 Ni it's just like shockingly naive to me. 65 00:04:12,334 --> 00:04:19,084 It's just like, I, I, I, I want, so we're gonna make, I mean, I guess if you look at it in a broad historical 66 00:04:19,174 --> 00:04:26,014 context, faced with urgency in, you know, fighting a war, coming out of a war, 67 00:04:26,314 --> 00:04:30,604 you know, putting a person on the moon, we've seen the government activated. 68 00:04:30,604 --> 00:04:37,088 But, and maybe, maybe there's, we just have to admit there's way too much plaque in government right now. 69 00:04:37,418 --> 00:04:44,258 And so we've, we've set kind of rule set upon rule set, which has prevented us from, from, from doing anything. 70 00:04:44,328 --> 00:04:51,018 But I, I get it well timed in all of that, but does it, does it feel just naive to you? 71 00:04:51,467 --> 00:04:57,862 Brian: I mean, I don't know if it feels naive, like I understand saying, well, it's impossible to do. 72 00:04:57,862 --> 00:05:01,972 I mean, the government has, you know, created an interstate highway system. 73 00:05:01,972 --> 00:05:02,782 It did. 74 00:05:02,872 --> 00:05:07,312 The Man on the Moon thing, it, it's done a bunch of stuff, won some wars and what and whatnot. 75 00:05:07,960 --> 00:05:08,140 Troy: No. 76 00:05:08,140 --> 00:05:08,980 Wars are good. 77 00:05:08,980 --> 00:05:10,750 Wars are good for mobilization 78 00:05:11,094 --> 00:05:12,594 Brian: Yeah, it's good marketing. 79 00:05:13,209 --> 00:05:14,769 Alex: Look at what's happening to Canada. 80 00:05:15,444 --> 00:05:15,654 Brian: yeah, 81 00:05:16,409 --> 00:05:16,884 people are coming 82 00:05:17,079 --> 00:05:17,739 Alex: Yo Europe. 83 00:05:17,769 --> 00:05:18,129 Oh, Europe. 84 00:05:18,189 --> 00:05:18,879 I mean Europe. 85 00:05:18,879 --> 00:05:20,394 Europe's never felt as United. 86 00:05:20,832 --> 00:05:22,512 Brian: to me it's more about putting, putting 87 00:05:22,827 --> 00:05:29,097 Troy: but if Donald Trump hadn't have come along and I'm not like supporting Donald Trump, I'm just saying that if he 88 00:05:29,097 --> 00:05:35,397 hadn't been this free radical disrupting the way we think about all of this, would, would this moment have arrived? 89 00:05:35,695 --> 00:05:37,440 Brian: No, I don't think so. 90 00:05:37,440 --> 00:05:40,650 I mean, because this is like, you know, usually political parties need 91 00:05:40,650 --> 00:05:45,360 to be cast out into the wilderness in order to reform themselves. 92 00:05:45,360 --> 00:05:46,320 This is just a Right. 93 00:05:46,320 --> 00:05:46,530 No. 94 00:05:46,620 --> 00:05:51,870 Otherwise they're like any bureaucracy, they're not gonna change unless forced to change. 95 00:05:52,020 --> 00:05:57,450 And so that's an interesting time and that's why this is like setting off what's kind of been a delayed 96 00:05:57,540 --> 00:06:02,130 civil war to me within the Democratic Party about what it really wants to 97 00:06:02,220 --> 00:06:04,020 Troy: dude, I think this is problematic. 98 00:06:04,020 --> 00:06:12,720 Basically what he's saying is outsourcing right to contractors, creating this gigantic, you know, outsource bureaucracy 99 00:06:12,720 --> 00:06:20,120 where government is used as flow through contracting requirements that have made it impossible to get anything done. 100 00:06:20,180 --> 00:06:25,550 And the ability to sue people has created this stasis in government. 101 00:06:26,240 --> 00:06:30,770 And what Ezra would say, the best place to listen to him, I think 102 00:06:30,770 --> 00:06:34,130 is prob Did you guys listen to, he was on Tyler Cohen's podcast. 103 00:06:34,700 --> 00:06:36,530 He's been all over the podcast world. 104 00:06:36,530 --> 00:06:38,210 Ezra has doing the rounds. 105 00:06:38,299 --> 00:06:40,229 but he's like, I love Doge. 106 00:06:40,289 --> 00:06:42,959 It's just, I think that they don't have to do it that way. 107 00:06:43,799 --> 00:06:49,739 It, you know, like, it becomes a question of how not what they're doing, the work that they're doing is important, 108 00:06:49,739 --> 00:06:54,989 essential, but like, they're making, you know, they're bad people making, 109 00:06:55,439 --> 00:06:59,489 you know, some questionable decisions, but like, that thing is needed. 110 00:07:00,839 --> 00:07:01,259 I don't know. 111 00:07:01,259 --> 00:07:07,559 I, I think it's, it, it's, it's, it only feeds into the, kind of, GOP agenda. 112 00:07:07,814 --> 00:07:09,079 Alex: You think the book does? 113 00:07:09,164 --> 00:07:13,154 Troy: I think that it's hard for people to say, well, yeah, you gotta radically 114 00:07:13,154 --> 00:07:18,524 downsize and disrupt you know, government and bureaucracies, but do it nicely. 115 00:07:19,029 --> 00:07:21,674 I, I just don't, I don't know that it's ever done nicely. 116 00:07:21,674 --> 00:07:21,734 I. 117 00:07:22,194 --> 00:07:23,059 I don't think you can. 118 00:07:23,664 --> 00:07:23,904 Alex: Yeah. 119 00:07:23,904 --> 00:07:24,414 Yeah, I know. 120 00:07:24,414 --> 00:07:30,649 But there's, there's I mean there's doing it not nicely and there's doing it with just like a, a bludgeon the 121 00:07:30,649 --> 00:07:34,339 way it does now, and with glee and with, you know, holding chainsaws. 122 00:07:34,339 --> 00:07:35,389 I think people are getting 123 00:07:35,389 --> 00:07:37,099 might get a little tired of that. 124 00:07:37,099 --> 00:07:39,199 Brian: There's the reality show aspect to it, right? 125 00:07:39,199 --> 00:07:41,719 I mean, I think that's part of the marketing, you know? 126 00:07:41,719 --> 00:07:42,049 Right. 127 00:07:42,049 --> 00:07:48,679 Like, so I think to me what was interesting is less almost the substance of it and more as a branding. 128 00:07:49,099 --> 00:07:50,089 Exercise, right? 129 00:07:50,089 --> 00:07:51,769 Like you have to brand a party. 130 00:07:51,799 --> 00:07:57,439 And like in America, you're basically, this is a product you're selling to do all of America. 131 00:07:57,769 --> 00:08:04,339 And generally this consumer market needs some kind of coherent vision right around, 132 00:08:04,339 --> 00:08:08,929 and you can't just be for a bunch of collection of niche special interest. 133 00:08:09,344 --> 00:08:16,964 Issues and you need to come up with some kind of underlying philosophy that you can then package up and sell. 134 00:08:17,084 --> 00:08:21,404 And like Trump has been really good at spectacle, he's been very good 135 00:08:21,404 --> 00:08:26,234 at very simple messaging that breaks through to low information voters. 136 00:08:26,624 --> 00:08:30,014 And, you know, we talk on this podcast all the time about the information 137 00:08:30,014 --> 00:08:35,624 space and the decentralization of media and all of the implications of that. 138 00:08:36,014 --> 00:08:39,674 And I think there's a lot of sort of similarities between what the 139 00:08:39,674 --> 00:08:45,944 institutional media world faces when, with what the Democratic party faces. 140 00:08:45,944 --> 00:08:49,004 I know there's sort of thought of, at least on the right as intertwined, 141 00:08:49,588 --> 00:08:49,738 Troy: That's a 142 00:08:49,783 --> 00:08:54,103 Brian: really they, they do need to come up with some kind of positive agenda. 143 00:08:54,103 --> 00:08:56,503 And I'm often thought struck by this. 144 00:08:56,923 --> 00:09:02,623 I wrote about it a little bit today about how so many publishers are so mired in 145 00:09:02,623 --> 00:09:07,603 cost cutting and in rationalizing their businesses that they're depressing. 146 00:09:08,083 --> 00:09:15,073 They're depressing to talk to, they're depressing to hear from, and, and it's just like, I, people say that, they're 147 00:09:15,092 --> 00:09:18,073 like, I sometimes people are like, oh, wow, you're so, I'm like, you. 148 00:09:18,073 --> 00:09:19,513 Like I'm not even negative. 149 00:09:19,513 --> 00:09:20,233 This is a thing. 150 00:09:20,233 --> 00:09:27,763 Like, this is, and it, when you don't have that sort of positive viewpoint, people don't really, aren't attracted to you. 151 00:09:27,823 --> 00:09:28,273 I mean, like 152 00:09:28,288 --> 00:09:28,948 Troy: You know what? 153 00:09:28,948 --> 00:09:36,598 Having you Brian Morrissey be a cheerleader for the publishing industry is really bizarre. 154 00:09:37,468 --> 00:09:38,188 I mean, given, 155 00:09:38,273 --> 00:09:39,103 Brian: mean cheerleader? 156 00:09:39,598 --> 00:09:43,588 Troy: I mean, how, given my history with you, I used to have this 157 00:09:43,588 --> 00:09:47,278 argument with you about being a cynical bastard all the time. 158 00:09:47,278 --> 00:09:49,798 I would march on over to the Digiday offices and 159 00:09:49,873 --> 00:09:51,433 Brian: I was just being clairvoyant. 160 00:09:51,493 --> 00:09:52,903 I was just being clairvoyant. 161 00:09:53,518 --> 00:09:59,998 Troy: But, but you know, it, it, it should no longer come a surprise to anyone that Donald Trump rolls outta 162 00:09:59,998 --> 00:10:03,628 bed in the morning and thinks of the most outrageous thing that he can 163 00:10:03,628 --> 00:10:08,638 say within the kind of boundaries of a broader platform and philosophy. 164 00:10:08,818 --> 00:10:16,018 And even this week, like I'm Canadian, obviously, I tune into some of these things, but, you know, repeatedly calling 165 00:10:16,018 --> 00:10:23,968 it, you know, you know, governor Trudeau, the 51st state, they would be better off if they just like gave it all up. 166 00:10:23,968 --> 00:10:25,618 We're protecting them anyway. 167 00:10:25,738 --> 00:10:28,078 We don't need anything from Canada. 168 00:10:28,288 --> 00:10:34,678 And just like completely doubling down on something that clearly, you know, I would say in lots of ways is 169 00:10:34,843 --> 00:10:40,708 I, I is, is not being well received other than it's an incendiary message 170 00:10:40,738 --> 00:10:46,438 that, you know, people can, that will win the media battle that day. 171 00:10:47,263 --> 00:10:48,193 It's insane. 172 00:10:48,680 --> 00:10:51,740 Alex: if, if, if you look at Ezra client's book, by the way, great beard, huh? 173 00:10:52,130 --> 00:10:54,140 Like the, whoever told whoever, like, 174 00:10:54,620 --> 00:10:55,430 Troy: He's handsome now. 175 00:10:55,430 --> 00:10:55,640 He's 176 00:10:55,850 --> 00:10:57,470 Alex: oh, he, oh yeah, he's hot. 177 00:10:57,961 --> 00:10:58,771 Troy: jacked up too. 178 00:10:58,771 --> 00:11:00,181 He is all ripped up. 179 00:11:00,481 --> 00:11:02,352 Alex: yeah, he got, he got ready for this press tour. 180 00:11:02,761 --> 00:11:07,202 Uh, I, I, I think, I mean, you read that book and it's like a good strategy, 181 00:11:07,442 --> 00:11:09,092 Troy: Wait, you read the book? 182 00:11:09,152 --> 00:11:11,492 Alex: no, but let's say, I mean, you, I'm saying you, 183 00:11:11,897 --> 00:11:13,217 but, but, but essentially, right? 184 00:11:13,217 --> 00:11:13,937 Isn't it like. 185 00:11:14,068 --> 00:11:18,988 You know, spend more on infrastructure, just like reduce, like, any 186 00:11:18,988 --> 00:11:23,268 kind of like, what is it, like regulatory stuff that slows it down. 187 00:11:23,268 --> 00:11:25,608 Infrastructure, infrastructure. 188 00:11:25,608 --> 00:11:27,978 Stop fighting between each other and let's get this done. 189 00:11:28,278 --> 00:11:30,708 I mean, that, that sounds like a great plan. 190 00:11:30,713 --> 00:11:36,288 It, it is just, I, it feels like the way people are reviewing it is that in today's world of messaging and the 191 00:11:36,288 --> 00:11:43,408 way Trump messages things and the way everything's just like, fucking trash fire every day, that's not going to reach out. 192 00:11:43,408 --> 00:11:48,628 And I don't think the, the plan doesn't seem to be read on its merits and people don't think the Democrats can 193 00:11:48,628 --> 00:11:53,758 win with it because it is not a media strategy in for today's world, right? 194 00:11:53,874 --> 00:11:57,294 should, should the, you know, V 3.0 or whatever we wanna call 195 00:11:57,294 --> 00:12:00,564 it of the Democratic Party, be something that's more of like a. 196 00:12:01,419 --> 00:12:05,379 A beast that's more capable of fighting Trump in his arena? 197 00:12:05,379 --> 00:12:10,994 Or is it or, or, or should it be about like, Hey, people are going to get tired of this shit, you know? 198 00:12:11,224 --> 00:12:16,174 And, and, you know, maybe just like a reasonable plan is what we'll want in three years. 199 00:12:16,592 --> 00:12:23,282 Brian: I think the case for that is that, you know, I think Tesla is down on like 30%, like, on the year. 200 00:12:23,467 --> 00:12:25,057 Alex: I track it every day in the morning. 201 00:12:25,057 --> 00:12:26,197 I, I watch it when I 202 00:12:26,257 --> 00:12:27,607 Brian: you wake, that's what you first do. 203 00:12:27,607 --> 00:12:27,757 You 204 00:12:28,027 --> 00:12:28,222 Alex: That's 205 00:12:28,297 --> 00:12:30,517 my, I, I, it's wonderful. 206 00:12:30,892 --> 00:12:31,197 Brian: obviously 207 00:12:31,377 --> 00:12:34,017 Troy: you're gonna be attracting the lucid stock, 208 00:12:35,770 --> 00:12:35,950 Brian: this 209 00:12:35,950 --> 00:12:36,730 is very tied to 210 00:12:37,180 --> 00:12:38,305 Troy: a, it's a, penny stock. 211 00:12:38,659 --> 00:12:41,149 Brian: Elon Musk's role in Doge. 212 00:12:41,209 --> 00:12:43,819 And, and the fact that the spectacle, right? 213 00:12:43,819 --> 00:12:49,179 Like there's only, there's only there's only so much I think people can take with, with the spectacle of this. 214 00:12:49,179 --> 00:12:53,349 I, I suspect as always that they're overplaying their hand here. 215 00:12:53,579 --> 00:12:54,029 I don't know. 216 00:12:54,179 --> 00:12:55,109 Time will tell, I 217 00:12:55,139 --> 00:13:02,249 Troy: Listen, if someone told me that you could align a more reasonable moral agenda, a more 218 00:13:02,249 --> 00:13:05,939 reasonable liberal agenda with a high functioning government, I'm all in. 219 00:13:06,438 --> 00:13:06,738 I'm in. 220 00:13:07,225 --> 00:13:07,675 You got me. 221 00:13:07,675 --> 00:13:11,215 I'll, I'll, I'll walk with Alex to the, to the voting booth. 222 00:13:11,965 --> 00:13:12,715 but in the 223 00:13:12,895 --> 00:13:14,185 Alex: can't, I can't vote. 224 00:13:14,185 --> 00:13:14,755 So, you know. 225 00:13:14,755 --> 00:13:15,930 We'll, I'll just watch you do it. 226 00:13:16,375 --> 00:13:17,335 Troy: okay, you can drive me in. 227 00:13:17,335 --> 00:13:17,935 You're lucid. 228 00:13:17,935 --> 00:13:22,634 but in the meantime, I, I just, I, I, I can't see it, but good on 'em. 229 00:13:22,634 --> 00:13:23,504 I mean, they're desperate. 230 00:13:23,744 --> 00:13:24,464 Alex: But what is it? 231 00:13:24,469 --> 00:13:26,234 What, what, what, what is it that they do? 232 00:13:26,504 --> 00:13:28,154 I mean, I, I think for me, 233 00:13:28,364 --> 00:13:28,964 Troy: is it that they do? 234 00:13:28,964 --> 00:13:31,064 Is, is a, is a really good question. 235 00:13:31,398 --> 00:13:36,308 Alex: I, I mean, you know, the, the, the only thing, the only kind of messaging that I've seen breakthrough 236 00:13:36,308 --> 00:13:40,808 is like, you know, cyber trucks and fires and, and free Luigi. 237 00:13:41,108 --> 00:13:42,158 You know, it's like the, 238 00:13:42,398 --> 00:13:43,118 the rebellion. 239 00:13:43,148 --> 00:13:44,468 The rebellion seems to be 240 00:13:44,513 --> 00:13:46,493 Troy: you know where it's gotta go, Alex. 241 00:13:46,523 --> 00:13:52,343 And, and, and I think this is just inevitable and it has to go to a pro technology message. 242 00:13:52,673 --> 00:14:01,893 It invariably you know, AI is going to massively change how services are delivered through the bureaucracy and 243 00:14:01,923 --> 00:14:05,673 the party that is best able to convince voters that that's in their interest, then 244 00:14:05,673 --> 00:14:10,233 they can actually affect that is gonna have an advantage, but it has to come. 245 00:14:10,653 --> 00:14:13,623 AI is the substrate on on, on which the new 246 00:14:13,668 --> 00:14:15,273 Alex: but people don't see that as a win. 247 00:14:15,333 --> 00:14:15,843 Like people 248 00:14:16,023 --> 00:14:19,203 Troy: I mean it's early on that message, I miss saying it will go there. 249 00:14:19,353 --> 00:14:23,883 Part of the conversation between Tyler Cohen and Ezra Klein was that like. 250 00:14:24,573 --> 00:14:31,083 Tyler was just saying like, you gotta admit that, you know, you're, if you, if you were to fund something like the new 251 00:14:31,083 --> 00:14:36,633 USAID or whatever government department you wanna talk about, you're gonna be able to do it with a couple hundred people. 252 00:14:36,633 --> 00:14:38,523 And they kept saying a GI. 253 00:14:38,523 --> 00:14:44,223 It's interesting to me that a GI has become part of the lexicon as being not speculative, but real. 254 00:14:44,868 --> 00:14:47,823 Alex: But it is, it is, to be clear, it is entirely speculative. 255 00:14:47,823 --> 00:14:48,663 We don't know if we're 256 00:14:48,783 --> 00:14:49,293 Troy: Right. 257 00:14:49,323 --> 00:14:52,173 But I'm, I'm just saying that, that the Tyler throws it around. 258 00:14:52,173 --> 00:14:54,153 Like it's not if that's, it's just when, 259 00:14:54,561 --> 00:14:54,861 Alex: Yeah. 260 00:14:54,866 --> 00:14:56,901 That, that, that, that type of talk is crazy though. 261 00:14:56,901 --> 00:14:58,401 It's, it's absolutely crazy. 262 00:14:58,431 --> 00:15:05,601 The, the jump from a GI from what we have today to a GI It is, it is so massive and I, I know that I'm like the 263 00:15:05,601 --> 00:15:12,595 a usually the, the, the AI pusher here, but that, that type of language is really not useful Because we have yet to see 264 00:15:12,595 --> 00:15:18,925 like large scale you know, use of, of the current generative AI models in ways 265 00:15:18,925 --> 00:15:22,735 that are reliable enough to get anything done that's, that's particularly useful. 266 00:15:23,125 --> 00:15:25,375 And so I don't, I don't know if that's a great messaging. 267 00:15:25,375 --> 00:15:26,755 I think, I think we see it when we see it. 268 00:15:26,755 --> 00:15:33,955 I think if anything, this type of talk, it needs to kind of be underplayed and, and maybe brought into a 269 00:15:33,955 --> 00:15:38,905 conversation about the modernization of document of, of government for efficiency using technology. 270 00:15:38,905 --> 00:15:40,105 I wouldn't use AI at all. 271 00:15:40,361 --> 00:15:41,351 Troy: That's what I'm saying. 272 00:15:41,351 --> 00:15:42,671 I, yeah, practical. 273 00:15:42,671 --> 00:15:43,031 You're right. 274 00:15:43,331 --> 00:15:44,591 But thank you for clarifying. 275 00:15:45,352 --> 00:15:45,772 Okay. 276 00:15:46,132 --> 00:15:46,672 ' Wow. 277 00:15:46,725 --> 00:15:49,515 That's about as political as I'd like to get Brian, you know, 278 00:15:49,800 --> 00:15:54,780 Brian: but like, no, I want to tie that because like, I think that the, the sort of counter to that is the look backwards. 279 00:15:54,780 --> 00:15:56,550 And I see a lot of that in the media industry. 280 00:15:56,550 --> 00:15:57,450 A lot of nostalgia. 281 00:15:57,455 --> 00:15:59,430 And I like, I like some of nostalgia. 282 00:15:59,430 --> 00:16:03,840 I did not get to enjoy the 19, 1990s magazine industry. 283 00:16:04,050 --> 00:16:04,830 But there's a lot of 284 00:16:05,160 --> 00:16:06,990 Alex: That, that's, oh, that's the chip. 285 00:16:07,020 --> 00:16:09,270 That's where, that's where the chip on the shoulder comes from. 286 00:16:09,420 --> 00:16:11,730 You see, Troy did, that's why he has, that's 287 00:16:11,850 --> 00:16:15,600 Brian: Troy, I, I don't know, do gray, I, what was Montreal Magazine? 288 00:16:15,600 --> 00:16:16,800 I don't know if there was that much. 289 00:16:16,800 --> 00:16:17,190 There was no 290 00:16:17,430 --> 00:16:18,840 Troy: Oh, nineties magazines. 291 00:16:18,840 --> 00:16:21,330 I, no, I, I got there to refactor them. 292 00:16:21,330 --> 00:16:27,780 Alex, I made a lot of money in the magazine business, but I, I was there to break it, not, not to fit, not to 293 00:16:27,780 --> 00:16:31,095 Alex: You were the original, like you were the Dojo print media. 294 00:16:33,615 --> 00:16:34,163 Um, 295 00:16:34,245 --> 00:16:34,815 Brian: much. 296 00:16:34,875 --> 00:16:35,085 Alex: but, 297 00:16:35,199 --> 00:16:40,689 Brian: But Grayden Carter has a new book out about the, the, the sort of heyday of magazines. 298 00:16:41,169 --> 00:16:47,290 Michael Greenbaum New York Times Media editor, I believe is he has a Conde Nast history coming out. 299 00:16:47,830 --> 00:16:56,200 I, Troy, I think you shared that guy's tweet about making $500,000 for three, for three magazine story 300 00:16:57,025 --> 00:16:58,990 Troy: And this was in, this was in the nineties. 301 00:16:58,990 --> 00:17:01,390 That's a lot more than $500,000 today. 302 00:17:02,177 --> 00:17:05,207 Brian: wrote today, I was like, I, I'm every single freelance. 303 00:17:05,537 --> 00:17:10,777 Magazine writer today probably read that with the same face that 304 00:17:10,787 --> 00:17:17,357 the Rick character had during that monologue on White Lotus as stupefied. 305 00:17:18,090 --> 00:17:20,065 Because that's the, that's the alternative, right? 306 00:17:20,065 --> 00:17:26,915 And, and that's why there needs to be some kind of positive and dynamic agenda, not just managing decline. 307 00:17:27,135 --> 00:17:31,935 But Troy, what, so you, you wrote in the, in the PVA newsletter, and we talked about it a little bit 308 00:17:31,935 --> 00:17:39,780 last week about, about this idea of franchise value and and how most, not most, I'd say a lot of particularly 309 00:17:39,780 --> 00:17:46,470 publishing brands are sort of moving more towards the right, they're moving into survivor category or arbitrage. 310 00:17:46,680 --> 00:17:52,710 And that's just, it's not, that's, that's the point I'm trying to get at is like, that's not very inspiring. 311 00:17:52,710 --> 00:17:57,870 You know, you're not going to track the best people to an industry that's managing decline. 312 00:17:58,215 --> 00:18:03,615 At the end of the day, I know media always attracts it, but I like that to me is, is like a fundamental challenge 313 00:18:03,615 --> 00:18:10,665 is how you get out of triage mode and start to paint some kind of picture of 314 00:18:11,055 --> 00:18:16,948 growth at the end of the day and not just financializing these assets in quotes. 315 00:18:17,488 --> 00:18:17,848 Troy: Right. 316 00:18:18,178 --> 00:18:19,018 What's your question? 317 00:18:19,356 --> 00:18:20,256 Brian: Well, how do you do that? 318 00:18:22,965 --> 00:18:23,325 Troy: Uh, 319 00:18:23,415 --> 00:18:24,675 what, What, a great question. 320 00:18:25,005 --> 00:18:25,605 Good question. 321 00:18:25,605 --> 00:18:25,905 Brian. 322 00:18:25,905 --> 00:18:25,965 Um. 323 00:18:26,816 --> 00:18:27,596 Brian: That was always when 324 00:18:27,941 --> 00:18:29,801 Troy: Well, I find it just for a moment. 325 00:18:29,801 --> 00:18:31,091 Can we pause on this? 326 00:18:31,091 --> 00:18:35,051 Like that you're making a couple hundred grand a story and that the, 327 00:18:35,116 --> 00:18:40,661 the, the, the Vanity Fair as a whole was, was nicely profitable at the time. 328 00:18:41,261 --> 00:18:46,481 And, and that in order to get there, in, in, and, and by the way, paying 329 00:18:46,481 --> 00:18:51,851 lots of people, including like, I mean, just amazing cost structure. 330 00:18:51,881 --> 00:18:56,291 You know, Annie Leitz shoots crazy, crazy, you know, expense lines, all that. 331 00:18:56,891 --> 00:19:06,561 And you have the premium, the perception of premium and the massive benefit of, of complete access. 332 00:19:07,011 --> 00:19:16,261 The best writers, the best photographers, such that your, your ad rates, are so high and advertisers are willing to pay a 333 00:19:16,261 --> 00:19:22,141 premium that you can still run a run a, a profitable business, one that's leveraged. 334 00:19:22,621 --> 00:19:25,981 Magazines were beautifully leveraged because you made one 335 00:19:25,981 --> 00:19:29,671 thing and sold it over and over and over and over again, right? 336 00:19:29,671 --> 00:19:34,721 Like it was a really nice, that's why media when it works is so beautiful because it's, it's a 337 00:19:35,026 --> 00:19:37,841 Alex: And that's why, and that's why software is even better. 338 00:19:38,081 --> 00:19:39,851 Troy: Yeah, it, well, it's the same idea, right? 339 00:19:39,851 --> 00:19:45,041 And it's all about mar marginal, marginal revenue and marginal profit, not unit costs. 340 00:19:45,671 --> 00:19:50,011 So, yeah, no, I, I long for those days and I, and I, I, I sort of, came 341 00:19:50,011 --> 00:19:53,821 into the business with the attitudes and cost structures of those days. 342 00:19:53,821 --> 00:20:01,531 So, you know, I, we had, I think in the US 22 or 24 after the Rodale acquisition, something like that. 343 00:20:02,031 --> 00:20:07,471 You know, magazine brands and, you know, more than a dozen publishers 344 00:20:07,471 --> 00:20:11,881 and, you know, 20 plus editors, all that made really good money. 345 00:20:12,751 --> 00:20:20,961 And you know, facing a market where I would say that the talent was way more highly leveraged in digital media. 346 00:20:21,291 --> 00:20:26,091 That even the senior people in digital me, media companies that, that magazine 347 00:20:26,091 --> 00:20:30,189 people looked down their nose at, made you know, far, far less money. 348 00:20:30,729 --> 00:20:36,639 And now we're, we're completely on the other side of that where, you know, the, the businesses just aren't 349 00:20:36,639 --> 00:20:43,269 sustainable anymore and are really being harvested for, you know, what is really great IP value in many cases 350 00:20:43,269 --> 00:20:47,829 where these, you know, brands have built up, you know, that, that kind of brand equity over years and years and years. 351 00:20:47,829 --> 00:20:51,969 So, I don't know, I don't know where you see this kind of leverage. 352 00:20:51,969 --> 00:20:58,034 I think Brian, in something like a podcast like, you know, your friend, 353 00:20:58,034 --> 00:21:02,250 kara Swisher you know, came out and said she's making $20 million a year. 354 00:21:02,630 --> 00:21:08,960 You know, we know that the p and l is, you know, decent over at Vox Media on their, you know, 355 00:21:09,290 --> 00:21:11,115 Alex: How are they making $20 million a year? 356 00:21:11,390 --> 00:21:16,010 Troy: How is she, you know, I, I, I don't know what that particular podcast makes. 357 00:21:16,010 --> 00:21:19,580 I know it's really popular and I don't know what else she does to make money 358 00:21:20,010 --> 00:21:23,550 you know, speaking gigs and, you know, she has a couple podcasts, all that. 359 00:21:23,790 --> 00:21:29,908 My point is, is that something that has the cost structure of Pivot makes a lot of money because it's 10 people, 360 00:21:30,232 --> 00:21:35,002 you know, and so, so you do see that media leverage in, in those kinds of business. 361 00:21:35,002 --> 00:21:36,442 You see it with creators. 362 00:21:36,832 --> 00:21:39,952 You just don't see, you know, it at an industrial scale. 363 00:21:40,250 --> 00:21:40,490 Brian: Yeah. 364 00:21:40,490 --> 00:21:46,150 I think what I, I was listening to Sarah person at the PCEO and she was talking about revenue per head. 365 00:21:46,330 --> 00:21:50,140 Like I think that is like an interesting metric for a lot of these businesses 366 00:21:50,200 --> 00:21:55,480 and how you get that to fine, you're not gonna get it to Nvidia levels, but. 367 00:21:56,001 --> 00:21:58,761 You know, e during the last year, it's like, it would be like 368 00:21:58,761 --> 00:22:03,471 $200,000, you know, revenue per employee at some of these companies. 369 00:22:03,741 --> 00:22:05,871 And when you look at, 370 00:22:06,111 --> 00:22:06,531 you know, 371 00:22:06,576 --> 00:22:08,916 Alex: to be clear, that's very, that's very low. 372 00:22:09,231 --> 00:22:09,771 Brian: Yeah. 373 00:22:09,801 --> 00:22:11,121 Punch bowl is like a million. 374 00:22:11,331 --> 00:22:11,811 Right. 375 00:22:12,261 --> 00:22:18,206 And that's sort of where I think a lot of these businesses go, where the numbers of 376 00:22:18,476 --> 00:22:19,646 Troy: Until they get judged. 377 00:22:19,886 --> 00:22:20,426 But yeah, 378 00:22:20,734 --> 00:22:23,344 Brian: well that's what I mean, like, I mean, you, you have to get that 379 00:22:23,344 --> 00:22:26,464 efficient in these, and you can, in some of these businesses, they're just 380 00:22:26,464 --> 00:22:29,914 Troy: my point is, is that they tap the rich veins of government to drive 381 00:22:29,914 --> 00:22:33,677 high subscription prices, which is why they have a million dollars per head. 382 00:22:33,970 --> 00:22:37,210 Brian: you think that the punch bowl, well maybe, I mean, I don't know 383 00:22:37,300 --> 00:22:39,280 Troy: Yeah, I think they probably run a good business hats off 384 00:22:39,280 --> 00:22:41,590 to them, but I think they have a nice subscription business 385 00:22:41,650 --> 00:22:43,810 Brian: there's leverage in a lot of these different like businesses. 386 00:22:43,810 --> 00:22:45,790 I did, I have a podcast coming out with the dude. 387 00:22:45,820 --> 00:22:46,450 Perfect. 388 00:22:46,510 --> 00:22:47,200 CEO 389 00:22:47,290 --> 00:22:49,240 Troy: making, you have leverage in your business. 390 00:22:49,985 --> 00:22:53,015 Brian: I mean, per employee, it's, it's a very, it's very high. 391 00:22:53,345 --> 00:22:54,113 Troy: It starts to smell 392 00:22:54,173 --> 00:22:56,453 A little like a million dollars probably. 393 00:22:56,843 --> 00:23:00,683 Brian: there's, there's, there's a lot of, I gotta smear myself in many 394 00:23:00,683 --> 00:23:04,833 directions, however but no, but I, I, I did it with like the, do you know dude? 395 00:23:04,833 --> 00:23:05,523 Perfect. 396 00:23:05,943 --> 00:23:06,573 Alex: yeah. 397 00:23:06,843 --> 00:23:09,513 Brian: The, they, you know, trick shots. 398 00:23:09,573 --> 00:23:14,803 They started Texas a and m students, I guess in 2009, they uploaded some, you know, video 399 00:23:14,863 --> 00:23:15,103 Alex: Yeah. 400 00:23:15,103 --> 00:23:18,193 Try try to bounce a ping pong ball into a red cup 401 00:23:18,578 --> 00:23:21,458 Brian: So, early early mover advantage. 402 00:23:21,518 --> 00:23:24,608 I mean, they had like 73% margins. 403 00:23:24,608 --> 00:23:24,878 Like 404 00:23:25,570 --> 00:23:26,195 Troy: Well, sure. 405 00:23:26,533 --> 00:23:27,743 Alex: ping pong balls are cheap. 406 00:23:28,177 --> 00:23:28,567 Brian: Yeah. 407 00:23:29,057 --> 00:23:33,437 So it's not like media is a terrible business, but then you look at like, some of these old sectors, 408 00:23:33,947 --> 00:23:41,867 you know, the New York Times now represents 7% of all US newspaper jobs, like just the New York Times 409 00:23:42,506 --> 00:23:45,026 Alex: And it's interesting how much of, how much of that, if, if 410 00:23:45,026 --> 00:23:48,146 you took out like games and stuff like that on top of it, right? 411 00:23:48,266 --> 00:23:49,676 Like it would probably be higher. 412 00:23:50,047 --> 00:23:54,351 Brian: You know, and even, but I mean, some of, and particularly really strong, like some something 413 00:23:54,351 --> 00:23:58,107 like The Economist that's not that big of a company really, you 414 00:23:58,167 --> 00:23:59,157 Troy: 300 people. 415 00:23:59,157 --> 00:24:00,302 300 in the newsroom. 416 00:24:00,857 --> 00:24:01,277 Brian: yeah. 417 00:24:01,517 --> 00:24:05,327 I mean, to to cover the whole world with that, that's pretty effective. 418 00:24:05,327 --> 00:24:05,837 I thought. 419 00:24:05,927 --> 00:24:07,397 I was like, that's pretty impressive 420 00:24:07,457 --> 00:24:07,967 considering the 421 00:24:08,207 --> 00:24:10,157 Alex: is the Economist a good business? 422 00:24:10,494 --> 00:24:11,664 Troy: It's a profitable business. 423 00:24:11,664 --> 00:24:12,624 It's probably 10%. 424 00:24:12,624 --> 00:24:13,044 Alex? 425 00:24:13,530 --> 00:24:14,040 Alex: Okay. 426 00:24:14,235 --> 00:24:16,575 Troy: mean, it's, it's, it's a, it's a one of one. 427 00:24:16,965 --> 00:24:23,015 It's, it's definitely back to Brian's original, original question, it definitely has on the continuum from 428 00:24:23,315 --> 00:24:28,325 franchise value in the middle survivor on the far right, arbitra ar arbitrage. 429 00:24:28,685 --> 00:24:30,155 It's a franchise business. 430 00:24:30,155 --> 00:24:37,805 It's a business that can't, that has, I think pricing power, market power, emote a global brand prestige 431 00:24:37,865 --> 00:24:42,695 and through all of that just has a kind of associated economic benefits. 432 00:24:43,145 --> 00:24:50,705 You know, I I, I think that they, they have a rare luxury of being able to employ 300 people's, a big newsroom these days, 433 00:24:51,169 --> 00:24:55,009 it is among the handful of media businesses that still have franchise value. 434 00:24:55,487 --> 00:24:58,157 Brian: And then, I don't know if you saw this week, but the skim. 435 00:24:58,172 --> 00:24:59,162 It got traded. 436 00:24:59,192 --> 00:25:04,382 Now, this would've been big, this would've been big news about like 10 years ago, or less than 10 years ago. 437 00:25:04,442 --> 00:25:06,422 But it was just kind of like a footnote. 438 00:25:06,852 --> 00:25:14,054 Ziff Davis acquired it, which is firmly, I believe we can say, on the right side of, of your continuum. 439 00:25:14,054 --> 00:25:14,414 Correct. 440 00:25:14,414 --> 00:25:14,744 Troy? 441 00:25:15,164 --> 00:25:15,974 Am I, am I being 442 00:25:16,034 --> 00:25:19,049 Troy: I mean, we, we would put them between Survivor and arbitrage. 443 00:25:19,049 --> 00:25:19,379 Yeah. 444 00:25:19,439 --> 00:25:19,709 But 445 00:25:19,879 --> 00:25:20,169 Brian: okay. 446 00:25:20,234 --> 00:25:20,564 That's, 447 00:25:20,579 --> 00:25:24,139 Troy: them in the bucket of Vivec is kind of a genius 448 00:25:24,464 --> 00:25:24,756 Brian: Yeah. 449 00:25:24,794 --> 00:25:26,024 No disrespect 450 00:25:26,624 --> 00:25:26,984 to the 451 00:25:27,029 --> 00:25:30,719 Troy: that business, I think enviable from a profit perspective, 452 00:25:30,719 --> 00:25:33,719 if they're stock prices lagging, the market doesn't like it. 453 00:25:33,719 --> 00:25:35,429 It's a really complicated business. 454 00:25:35,429 --> 00:25:39,029 It has a lot of weird platform dependent shit in there. 455 00:25:39,389 --> 00:25:42,089 But he's like, you know, the garbage man of the industry. 456 00:25:42,149 --> 00:25:42,929 That's unfair. 457 00:25:43,139 --> 00:25:43,979 He's the 458 00:25:43,979 --> 00:25:44,249 uh, 459 00:25:44,739 --> 00:25:45,159 Brian: Uh Oh. 460 00:25:45,554 --> 00:25:48,284 You know what they say in Washington, a gaff is when you tell the truth. 461 00:25:48,617 --> 00:25:48,797 Troy: No 462 00:25:48,797 --> 00:25:51,707 he is like the Fred, you know, he, he's of the Fred Sanford of media. 463 00:25:53,097 --> 00:25:54,302 Brian: It keeps getting better. 464 00:25:56,702 --> 00:25:57,962 We should have it back on. 465 00:25:58,149 --> 00:25:58,329 No. 466 00:25:58,329 --> 00:26:04,299 Look, a lot of brands have, have, have gone that have maybe I would say lost their luster a bit. 467 00:26:04,359 --> 00:26:06,549 You know, Mashable, quartz, et cetera. 468 00:26:06,579 --> 00:26:08,259 You know, it's part of the life cycle. 469 00:26:08,259 --> 00:26:10,488 Um, Cnet went over to 470 00:26:10,638 --> 00:26:12,403 Troy: PC Meg is what started it. 471 00:26:12,403 --> 00:26:12,683 Yeah, 472 00:26:13,100 --> 00:26:15,470 Brian: yeah, they operate these businesses really well. 473 00:26:15,530 --> 00:26:21,940 And but yeah, I mean, that to me is like, it's gonna end up becoming the skim is another sort of cautionary tale. 474 00:26:21,940 --> 00:26:23,050 Do you know the skim 475 00:26:23,170 --> 00:26:26,665 Alex: Well, I was gonna to say, I'm, I'm, I'm embarrassed to like, not know the skin. 476 00:26:26,665 --> 00:26:27,085 What is the 477 00:26:27,340 --> 00:26:28,120 Brian: No, that's okay. 478 00:26:28,120 --> 00:26:28,330 It 479 00:26:28,390 --> 00:26:28,540 was, 480 00:26:28,690 --> 00:26:32,985 Troy: they're, they're really tight, you know, kind of sultry pants made by Kim Kardashian. 481 00:26:33,585 --> 00:26:35,105 Exercise, wear athleisure. 482 00:26:35,470 --> 00:26:36,250 Alex: I'm wearing some now. 483 00:26:38,440 --> 00:26:45,460 Brian: No, it is a, it is, it was one of the original sort of email companies, it was an email newsletter 484 00:26:45,490 --> 00:26:53,200 for young women that would summarize the news in a very relatable way 485 00:26:53,425 --> 00:26:55,885 Troy: It inherited the legacy of Daily Candy. 486 00:26:56,370 --> 00:27:00,750 Brian: if Daily Candy was the original that would've been like a talk about a business that 487 00:27:01,200 --> 00:27:02,355 Alex: So it was a, it was a, it 488 00:27:02,370 --> 00:27:02,633 Brian: at a 489 00:27:02,640 --> 00:27:03,420 different time. 490 00:27:04,011 --> 00:27:07,131 Troy: it was one of the original newsletters built a big list. 491 00:27:07,161 --> 00:27:09,741 They monetized, they kept going, and then 492 00:27:10,373 --> 00:27:10,703 Alex: but like 493 00:27:10,748 --> 00:27:12,818 Brian: They raised $30 million. 494 00:27:13,066 --> 00:27:15,196 30 million for a newsletter. 495 00:27:15,676 --> 00:27:16,066 That was 496 00:27:16,111 --> 00:27:20,341 Alex: I mean, I mean, you know what, but honestly, if I heard that today, I wouldn't be surprised because we're 497 00:27:20,341 --> 00:27:25,231 hearing of some newsletters like Lenny's and stuff like that, reaching, you know, a million subscribers. 498 00:27:25,231 --> 00:27:28,351 I mean, I wouldn't be surprised if, if you told me today one of these 499 00:27:28,351 --> 00:27:31,801 Substack newsletter raised 30 million, I wouldn't be surprised, you know? 500 00:27:32,236 --> 00:27:35,206 Kara Swish, Kara Swisher is making 20. 501 00:27:35,606 --> 00:27:39,706 And I know most of that is, is podcasts are much more viable than newsletters. 502 00:27:39,706 --> 00:27:45,616 But how doesn't like selling to, so explain it to me because I, I, I hope there are people in the audience that 503 00:27:45,616 --> 00:27:54,228 are as up to speed as me about this, but isn't selling to Z Davis kind of like, you know, going to a farm upstate, 504 00:27:55,145 --> 00:27:55,610 Troy: I, sorry. 505 00:27:56,225 --> 00:27:56,825 Alex: like, I don't know. 506 00:27:56,825 --> 00:28:01,145 You know, when you tell kids the dog went, went to a farm upstate, like isn't it like 507 00:28:03,690 --> 00:28:06,455 you, you kind of, it sounds nice, but it really isn't. 508 00:28:07,703 --> 00:28:11,799 Brian: it, it's def it's definitely on, on SEO Glue factory highway. 509 00:28:12,091 --> 00:28:13,461 Alex: maybe it's not, he's not a trash 510 00:28:13,498 --> 00:28:13,678 car. 511 00:28:13,757 --> 00:28:15,797 maybe he's just com composting. 512 00:28:16,110 --> 00:28:20,909 You know, it's a, it's a recycling factory, but, so, so, but it doesn't sound like a great exit. 513 00:28:20,939 --> 00:28:21,179 Right. 514 00:28:21,269 --> 00:28:22,619 Brian: Look, they have a playbook. 515 00:28:22,619 --> 00:28:23,669 They have a, right. 516 00:28:23,669 --> 00:28:24,569 I mean, is that fair? 517 00:28:24,569 --> 00:28:26,099 You know the business better than I do. 518 00:28:26,099 --> 00:28:29,023 Troy, they have a playbook, then they're gonna run the playbook. 519 00:28:29,510 --> 00:28:35,750 Troy: they're gonna do what they do, which is central infrastructure, very business-minded GMs. 520 00:28:36,436 --> 00:28:39,886 Manage the business extremely, you know, tightly. 521 00:28:39,886 --> 00:28:47,986 And, you know, I, I, I think that these days you're better to be on the side of, you know, buying stuff cheap than 522 00:28:47,986 --> 00:28:53,926 buying stuff expensively and hoping that you're gonna maintain or create premium value or franchise value. 523 00:28:53,926 --> 00:28:54,761 So it's smart. 524 00:28:55,254 --> 00:28:56,799 It's, you know what, it's, what is it? 525 00:28:57,009 --> 00:29:00,106 It's a 3 million email addresses and decent readership. 526 00:29:00,556 --> 00:29:00,916 Why not? 527 00:29:01,250 --> 00:29:01,370 Alex: Oh. 528 00:29:01,370 --> 00:29:04,280 They raised 30 million on 3 million email addresses. 529 00:29:04,325 --> 00:29:04,655 Troy: No, they 530 00:29:04,697 --> 00:29:04,865 raised 531 00:29:05,030 --> 00:29:06,110 Brian: no, they've been shrinking. 532 00:29:06,611 --> 00:29:08,191 So I mean, you know, this 533 00:29:08,246 --> 00:29:09,416 Troy: Used to be five, 534 00:29:09,416 --> 00:29:09,836 I think. 535 00:29:10,261 --> 00:29:13,621 anyway, it's not that it's, I hate to be a dick here, but it's not that interesting. 536 00:29:16,621 --> 00:29:17,551 Brian: that says it all, 537 00:29:17,641 --> 00:29:20,521 Troy: we should, we should, we should just fucking move on, 538 00:29:20,903 --> 00:29:21,563 Alex: Yeah, I think we're all 539 00:29:21,683 --> 00:29:23,243 Brian: all right, let's move on. 540 00:29:23,273 --> 00:29:24,893 that's that's fine. 541 00:29:25,343 --> 00:29:26,033 That's fine. 542 00:29:26,433 --> 00:29:31,463 This was something that was brought up by by ab he talked about this acquisition that, that just happened. 543 00:29:31,463 --> 00:29:38,513 But to me, what was interesting is this idea of, you know, we're really past the era of, of keyword targeting. 544 00:29:38,663 --> 00:29:39,923 I mean, keywords were like. 545 00:29:40,388 --> 00:29:43,928 Sort of, they built the search advertising ecosystem. 546 00:29:43,928 --> 00:29:47,738 It's the one sort of home run of digital advertising really. 547 00:29:48,188 --> 00:29:51,068 And now we're moving to a world where you just described your 548 00:29:51,068 --> 00:29:54,368 perfect customer and then, you know, it's, it's the outcomes era. 549 00:29:54,403 --> 00:29:58,238 And, and that's, and that is the, you know, describe your 550 00:29:58,238 --> 00:30:01,598 perfect customer and then let the machine go find that customer. 551 00:30:02,178 --> 00:30:07,573 I, I think that's gonna be, I mean, I don't, I, I wanna have a positive agenda for publishers, but like, 552 00:30:07,573 --> 00:30:12,913 that's, that's a very attractive proposition for just about any for just about any marketer, I would think. 553 00:30:13,363 --> 00:30:18,853 And that's gonna have major impacts, you know, as that happens throughout the entire media ecosystem. 554 00:30:19,345 --> 00:30:20,155 Your thoughts, Troy? 555 00:30:20,631 --> 00:30:23,541 Troy: Sorry, I was texting ab, what was the question? 556 00:30:23,996 --> 00:30:25,526 Brian: Basically about like, you know. 557 00:30:25,933 --> 00:30:34,043 Moving beyond keyword, keyword targeting and, and moving into just describing your perfect customer and 558 00:30:34,043 --> 00:30:41,605 then letting the machines do, do, do the work and how that's gonna have a massive impact on the entire ecosystem. 559 00:30:42,014 --> 00:30:44,084 I mean, this is sort of where we've been going with P 560 00:30:44,429 --> 00:30:45,059 Troy: um, 561 00:30:45,224 --> 00:30:48,734 yeah, I, I think that, that it will happen. 562 00:30:48,734 --> 00:30:54,044 But marketing as, you know, like everything that's scarce in the world is a zero sum game. 563 00:30:54,654 --> 00:31:04,614 So e eventually, if that's an effective acquisition method, it just gets priced into your cost of goods sold and prices 564 00:31:04,614 --> 00:31:08,364 go up and it benefits the people that own the algorithm and the distribution. 565 00:31:08,844 --> 00:31:16,464 And, you know, then people get forced out because their roas or their return on ad spend gets to a place where 566 00:31:16,464 --> 00:31:21,324 it's not economically sensible to, to keep spending more on a customer. 567 00:31:21,324 --> 00:31:22,374 But we're already there. 568 00:31:22,967 --> 00:31:26,927 We're already there with like automating acquisition in, in 569 00:31:26,927 --> 00:31:31,427 effect, turning marketing into distribution as, as a, as a COGS item. 570 00:31:31,877 --> 00:31:35,057 So I, and I don't, I don't really think that changes anything. 571 00:31:35,387 --> 00:31:36,317 You know, what's it called? 572 00:31:36,497 --> 00:31:39,617 It's Google Max or whatever, or, or, you know, 573 00:31:39,647 --> 00:31:42,280 meta, meta has their own version of it. 574 00:31:42,280 --> 00:31:46,420 And to me that's at the scale level, that's gonna be a cost of entry. 575 00:31:46,420 --> 00:31:52,870 And you're gonna see people, like, I know that Neil was, is really encouraged by his, what is this thing 576 00:31:53,185 --> 00:31:54,535 Brian: Decipher now. 577 00:31:54,535 --> 00:31:57,955 Decipher Plus, that is, that was actually very interesting and that I just 578 00:31:58,030 --> 00:31:59,590 Troy: Well, is it in, is it interesting? 579 00:31:59,590 --> 00:32:02,290 I mean, it, it, it, it is interesting in that good for Neil. 580 00:32:02,915 --> 00:32:05,414 He's realized it, it, you know what it is? 581 00:32:05,500 --> 00:32:06,670 Well, I will describe it. 582 00:32:06,730 --> 00:32:12,100 It's, it's an ad network owned by a publisher that attempts to use non 583 00:32:12,100 --> 00:32:18,430 cookie data and give you something that rivals or builds on contextual ad 584 00:32:18,430 --> 00:32:18,910 placement 585 00:32:18,985 --> 00:32:20,485 Brian: it's intent data. 586 00:32:20,995 --> 00:32:23,725 Neil would, Neil would, would brand it intent data, 587 00:32:23,935 --> 00:32:24,355 Troy: Great. 588 00:32:24,435 --> 00:32:30,855 So where it starts is publishers like Neil have a lot of clicks on Buy Now buttons 589 00:32:31,065 --> 00:32:37,715 and, and pages in his portfolio that show where consumer's interested in a product. 590 00:32:37,985 --> 00:32:38,225 Right? 591 00:32:38,225 --> 00:32:44,135 Alex, you land on a page that says Best Air Fryers, you know, for someone in Northern California or 592 00:32:44,265 --> 00:32:44,525 whatever. 593 00:32:45,002 --> 00:32:50,342 And so you know, that is a light signal or a strong signal depending on how 594 00:32:50,342 --> 00:32:54,002 far down the funnel you go to say that you're interested in air funnels. 595 00:32:54,002 --> 00:33:02,672 You start to, or air funnels, air funnels, air fryers, and then you put that into your DMP and you start building a profile 596 00:33:02,672 --> 00:33:05,732 around the consumer that says that they're interested in X, Y, and Z. And 597 00:33:05,732 --> 00:33:09,302 you do that over enough pages and you can get a good, good profile of someone. 598 00:33:09,302 --> 00:33:10,262 That's what he's building. 599 00:33:10,262 --> 00:33:15,452 And now, like everybody in a publishing business of that scale would wanna do is 600 00:33:15,452 --> 00:33:20,462 say, it's not only useful to us, we can target customers on your pages as well. 601 00:33:20,896 --> 00:33:23,206 Right, so you can become part of our ad network. 602 00:33:23,206 --> 00:33:29,722 Not dissimilar by the way, to what Vox does with their ad network, which is called it's called 603 00:33:29,872 --> 00:33:30,622 Brian: I need to be able to 604 00:33:30,622 --> 00:33:39,255 Troy: So it's logical that he's doing this because back to the franchise value to arbitrage, you know, big picture 605 00:33:39,255 --> 00:33:43,526 is, you know, Tash Meredith isn't gonna sit pretty on that continuum, right? 606 00:33:43,982 --> 00:33:45,062 All recipes. 607 00:33:45,607 --> 00:33:50,677 Brian: I, I mean, I will say this, I've been very impressed that by, you know, because they're publicly 608 00:33:50,677 --> 00:33:58,597 traded, you know, they report their grids and they have defied a lot of these headwinds in many ways. 609 00:33:58,597 --> 00:34:04,657 Now they sort of divide out their core properties from, I mean, God forbid if you work on one of the 610 00:34:04,657 --> 00:34:08,077 non-core properties and they're just telling the world like that, you know, 611 00:34:08,122 --> 00:34:08,902 Troy: he's good. 612 00:34:08,932 --> 00:34:09,682 He's good. 613 00:34:09,682 --> 00:34:10,492 He is smart. 614 00:34:10,522 --> 00:34:11,842 He's good leader. 615 00:34:11,962 --> 00:34:15,952 You know, there's good assets in there, but big pictures, there's lots of pressure on the business. 616 00:34:16,446 --> 00:34:17,436 You wanna have him back on? 617 00:34:18,039 --> 00:34:20,139 Brian: So you're not that bullish on Decipher Plus. 618 00:34:20,479 --> 00:34:23,059 I just think it's good that a publisher's even coming out with stuff 619 00:34:23,059 --> 00:34:27,169 like this, I mean, my bar is fairly low at this point because like all, 620 00:34:27,736 --> 00:34:28,006 Troy: I 621 00:34:28,126 --> 00:34:31,001 Brian: mean, I joke with Mark Stenberg all the time about, I'm like, my God. 622 00:34:31,001 --> 00:34:32,201 Like another layoff story. 623 00:34:32,201 --> 00:34:32,381 Like 624 00:34:33,011 --> 00:34:33,521 Troy: I love it. 625 00:34:33,521 --> 00:34:34,991 Brian, I love your optimism. 626 00:34:35,051 --> 00:34:36,281 I'm very optimistic. 627 00:34:36,281 --> 00:34:38,021 Brian: in Miami for the LA for two days. 628 00:34:38,141 --> 00:34:40,811 Troy: No, it's just the turnaround is astounding. 629 00:34:41,021 --> 00:34:41,921 It's astounding. 630 00:34:41,921 --> 00:34:46,751 'cause I would've walk, walked into your office talking about decipher and you would've crapped all over me. 631 00:34:47,153 --> 00:34:52,223 But you would, you would've said something like, but isn't it just an ad network, isn't it? 632 00:34:52,908 --> 00:34:54,678 Brian: It's a managed service provider. 633 00:34:54,678 --> 00:34:55,788 That's what you would tell me 634 00:34:58,218 --> 00:35:00,048 And I would say, right, an ad network. 635 00:35:00,487 --> 00:35:04,927 On Happier Note, did you see that one in four programming Jo Jobs has, has, has vanished. 636 00:35:05,471 --> 00:35:09,221 Apparently that's the new, that's the new metric. 637 00:35:09,701 --> 00:35:12,941 Is this gonna be like the sort of metric for all of the, for, 638 00:35:12,941 --> 00:35:16,181 for so many of these different fields, like one in four go away? 639 00:35:16,689 --> 00:35:18,369 Alex: I mean, programming is pretty 640 00:35:18,524 --> 00:35:18,664 Brian: happens. 641 00:35:19,090 --> 00:35:19,960 Alex: only 642 00:35:20,275 --> 00:35:24,205 job that can be pretty efficiently replaced in parts 643 00:35:24,205 --> 00:35:25,135 by AI today. 644 00:35:25,150 --> 00:35:31,160 You know, I'm, I'm not a believer that like maybe as many jobs will be replaced by as, as are being touted now. 645 00:35:31,160 --> 00:35:33,650 Like, programming is so specific when you think about it. 646 00:35:33,650 --> 00:35:42,100 It's really like people who talk to machines and we've invented this new language that supports that tasks really, 647 00:35:42,100 --> 00:35:48,086 really well because, you know, programming is, is a contained number of, of things 648 00:35:48,086 --> 00:35:51,686 that you just put together and you can run it in a computer and see how it works. 649 00:35:52,076 --> 00:35:58,461 So yeah, I mean, I see it, I see it, I see it coming from for, for programming or engineering pretty rapidly. 650 00:35:58,561 --> 00:36:01,351 I think there will be all sorts of job built around computers. 651 00:36:01,351 --> 00:36:07,471 You know, it used to be like the job used to be to be able to like, think through math problems and put them 652 00:36:07,471 --> 00:36:14,621 into punch cards and then, you know, people invented languages that became closer and closer to human language. 653 00:36:14,956 --> 00:36:17,111 And now it's just, it's human language. 654 00:36:17,111 --> 00:36:24,056 But you still need a very technical mindset and, and to, to make anything worth of value. 655 00:36:24,056 --> 00:36:25,346 It's just you need less people, 656 00:36:26,056 --> 00:36:30,431 Troy: It is just that, you know, when your mom would say, oh, what does your son do? 657 00:36:30,641 --> 00:36:33,641 And your mom would say, my son works in computers. 658 00:36:34,131 --> 00:36:35,811 You can't, you can't say that anymore. 659 00:36:36,208 --> 00:36:38,158 ' cause everybody works in computers now. 660 00:36:38,188 --> 00:36:39,538 We're all just computers. 661 00:36:39,930 --> 00:36:43,170 Brian: Yeah, I had an Uber driver the other, the other week who was, 662 00:36:43,230 --> 00:36:46,980 he was a student, and my wife was like, oh, what are you studying? 663 00:36:47,220 --> 00:36:49,852 And he was like, he said, oh, programming. 664 00:36:51,112 --> 00:36:54,652 And I was like, oh, well then you'll have like lots of job opportunities. 665 00:36:54,652 --> 00:36:55,672 And I was like, gonna speak up. 666 00:36:55,672 --> 00:36:56,662 And I was like, no, I'm not gonna do it. 667 00:36:56,782 --> 00:37:04,611 Troy: Yeah, I mean, I, I, I guess the answer that, that you're looking for is we're all gonna be more technol, 668 00:37:04,731 --> 00:37:15,831 technologically leveraged, I would say, Alex, and yeah, you can't, you can't build a system just by like typing an engli, 669 00:37:15,861 --> 00:37:20,541 like an English language request into an LLM and getting some software back. 670 00:37:20,721 --> 00:37:26,121 You can't, you still have to understand interconnectivity between different components. 671 00:37:26,121 --> 00:37:28,071 You have to understand system design. 672 00:37:28,281 --> 00:37:29,871 You have to understand databases. 673 00:37:29,871 --> 00:37:34,381 You have to understand relationships between you know, different parts of the system. 674 00:37:34,381 --> 00:37:35,011 Like these. 675 00:37:35,011 --> 00:37:36,811 Jo, this isn't going away tomorrow. 676 00:37:36,871 --> 00:37:37,051 This 677 00:37:37,186 --> 00:37:41,056 Alex: The jobs are the jobs that I think, I think, I think working in 678 00:37:41,056 --> 00:37:45,746 computers, like our moms used to say you know, those jobs are changing though. 679 00:37:45,746 --> 00:37:51,661 I think there was a massive jobs, which was pretty low level engineering at the top line, right? 680 00:37:51,661 --> 00:37:55,651 So a lot of people building interface stuff, front end stuff, 681 00:37:55,651 --> 00:37:59,891 stuff that is pretty basic, but was being rebuilt over and over. 682 00:38:00,131 --> 00:38:02,021 I think some of these jobs are going away. 683 00:38:02,301 --> 00:38:07,671 But I think with the demand scaling up there's still, you know, there's still people like putting those servers 684 00:38:07,671 --> 00:38:11,421 together and configuring everything and making all that stuff happen and 685 00:38:11,828 --> 00:38:13,538 Troy: take five people to make a website. 686 00:38:13,538 --> 00:38:13,958 Alex, 687 00:38:14,333 --> 00:38:14,753 Alex: yeah. 688 00:38:14,813 --> 00:38:15,023 Yeah. 689 00:38:15,023 --> 00:38:20,535 No, and, and, so I think the demand's just gonna become higher, but it's just that we're becoming. 690 00:38:20,565 --> 00:38:26,103 It, you, a few decades ago, you needed to be somebody who knew how to use a computer to use a computer, right? 691 00:38:26,103 --> 00:38:28,113 Like, today, we all have a phone in our pocket. 692 00:38:28,143 --> 00:38:28,713 That's fine. 693 00:38:28,713 --> 00:38:31,323 And then it's, I think it's a pretty natural progression. 694 00:38:31,543 --> 00:38:37,973 what I don't like is that people conflate that with replacement of jobs across many other industries. 695 00:38:38,363 --> 00:38:42,103 I think, I think there is definitely some risk in the creative arts. 696 00:38:42,313 --> 00:38:45,908 And it's very strange because like bo, like the way generative AI 697 00:38:45,908 --> 00:38:50,703 works it, it can create art which is very non-deterministic, right? 698 00:38:50,733 --> 00:38:51,963 Very yeah. 699 00:38:51,963 --> 00:38:57,973 And then it can, it can also replace people code, which is very deterministic because it's, it's easy to test code. 700 00:38:58,353 --> 00:39:00,843 But then everything in between, all the other jobs. 701 00:39:00,843 --> 00:39:04,923 I think it's, it's, it's a lot, it's a lot harder to see just a direct path of like, 702 00:39:05,353 --> 00:39:07,278 Brian: Okay, so you're saying this is not like. 703 00:39:08,013 --> 00:39:11,463 This is not like a harbinger of things that come to other professions, 704 00:39:11,463 --> 00:39:15,813 but this is, it's fairly unique to programming because it's so 705 00:39:15,968 --> 00:39:17,553 Alex: I, I think it's very subtle. 706 00:39:17,553 --> 00:39:25,413 I think we have, I think there are a few minor technology miracles that need to happen to even, you know, I, I, the way I 707 00:39:25,413 --> 00:39:32,073 see a GI is like speed of light, you know, like we can get close to it potentially, but, but I don't think we can, we can 708 00:39:32,193 --> 00:39:34,773 you know, I don't think it's certain right now that we can ever reach it. 709 00:39:35,103 --> 00:39:37,323 And the systems will become smarter. 710 00:39:37,533 --> 00:39:44,803 The systems will become more specialized but it is not a, a direct line and it won't impact everything. 711 00:39:44,923 --> 00:39:51,729 Similarly, meanwhile, like we're still not seeing enough happening around making these systems more reliable. 712 00:39:51,939 --> 00:39:55,719 And I think unless they become very, very reliable, a lot of stuff that, 713 00:39:55,869 --> 00:40:00,159 people talk about is kind of, is, is is a flight, you know, it's like, is vaporware. 714 00:40:00,499 --> 00:40:06,379 The, the challenges right now, and what I find very frustrating is that all the AI companies to, to keep their kind of their 715 00:40:06,379 --> 00:40:11,859 value up and to raise the insane amount of monies that they need to burn to compete 716 00:40:12,209 --> 00:40:16,379 including open ai, have to be parabolic in the way they talk about stuff. 717 00:40:16,619 --> 00:40:22,439 Because you can't raise, you know, if you open ai, you can't raise $40 million that you're just essentially 718 00:40:22,439 --> 00:40:25,979 going to put in an incinerator if it's just going to be like, yeah. 719 00:40:25,979 --> 00:40:32,369 And it'll, you know, it'll generate emojis faster or it'll be able to write a book better because there's no money in that. 720 00:40:32,709 --> 00:40:36,129 So they have to talk about kind of these incredible age agentic 721 00:40:36,399 --> 00:40:39,309 systems that will do all these tasks for you and stuff like that. 722 00:40:39,339 --> 00:40:43,969 And, and we're not we're nowhere near, like, we're nowhere near in that, in that area. 723 00:40:44,269 --> 00:40:48,044 So I. You know, I, I'm not saying it won't happen. 724 00:40:48,354 --> 00:40:52,074 I think, I think there just needs to be a little bit more of an intelligent conversation around it. 725 00:40:52,074 --> 00:40:58,764 And engineering programming is, is is exceptionally kind of geared towards 726 00:40:59,219 --> 00:41:03,029 being able to be replaced by AI or, or fundamentally changed by ai. 727 00:41:03,369 --> 00:41:06,691 but maybe just that changes a lot of stuff because it means, you 728 00:41:06,691 --> 00:41:10,351 know, software keeps eating the world, but at a much faster pace. 729 00:41:10,531 --> 00:41:17,671 And other jobs get replaced by stuff that isn't ai but was facilitated because all of a sudden, you know, a bunch of 730 00:41:17,671 --> 00:41:21,331 people starting creating a bunch more software and that software replaces jobs. 731 00:41:21,331 --> 00:41:26,351 You know, if I'm making any sense here, I think the conversation needs to be a little bit more nuanced than it is today. 732 00:41:26,840 --> 00:41:27,170 Does it make 733 00:41:27,250 --> 00:41:29,680 Brian: You know what I've been using AI for lately. 734 00:41:29,740 --> 00:41:31,300 I, I started a 735 00:41:31,300 --> 00:41:33,850 project for, yeah, companionship. 736 00:41:33,850 --> 00:41:37,450 But actually it's partially that because I started a project with. 737 00:41:37,951 --> 00:41:41,131 I think I've mentioned it here, like I write this, this, I've been writing this 738 00:41:41,131 --> 00:41:44,401 journal for the last two and a half years where I just write every day about like 739 00:41:44,701 --> 00:41:48,631 business, what's on my mind and stuff, and it was just useless data. 740 00:41:48,841 --> 00:41:56,401 Little did I know, I upload all of it to a project with like my p and ls from the last few years and it's 741 00:41:56,401 --> 00:42:03,781 like this financial analyst that is this business analyst that I'm, it, it gave me all kinds of different things. 742 00:42:03,781 --> 00:42:09,631 I mean, I think the problem is, it's like, what I realize with this when I ask it to like analyze things is 743 00:42:10,051 --> 00:42:14,011 it's spitting back at me, just my view of the bi, like I'm not getting 744 00:42:14,011 --> 00:42:18,511 a different view, but it's sort of packaged as if it's like a consultant. 745 00:42:18,931 --> 00:42:24,271 Who knows, you know, like in consulting deals, it's like, well, just tell me what the result you want 746 00:42:24,271 --> 00:42:27,871 because like, that's why I'm here to, you can use it like internally. 747 00:42:28,216 --> 00:42:28,456 Alex: Yeah. 748 00:42:28,456 --> 00:42:28,726 to 749 00:42:28,726 --> 00:42:28,876 to 750 00:42:29,281 --> 00:42:29,941 Brian: basically. 751 00:42:30,001 --> 00:42:30,496 Yeah, yeah, yeah. 752 00:42:30,547 --> 00:42:30,886 It does. 753 00:42:31,201 --> 00:42:34,921 It validates your own, like my own thoughts. 754 00:42:35,411 --> 00:42:37,841 I don't, it's not very, it's not unbiased. 755 00:42:38,011 --> 00:42:40,591 But it is, I, I, I find it useful for sure. 756 00:42:41,086 --> 00:42:45,916 Troy: I had two items that I wanted to bring up and one was really an extension of what you guys are talking about. 757 00:42:45,916 --> 00:42:52,696 By the way, Alex, one thing to watch out for on the LLM progress side, or I think there's a lot of conversation 758 00:42:52,696 --> 00:42:59,806 this week around model context protocol, MCP, which there's a client and a server, and essentially standardizes 759 00:42:59,806 --> 00:43:05,836 like HTTP connections between LLMs and databases and other services, which 760 00:43:05,836 --> 00:43:10,306 makes it easier to plug in different LLMs to an end up like a service stack. 761 00:43:10,306 --> 00:43:13,156 And we'll, we'll kind of start to facilitate more. 762 00:43:13,540 --> 00:43:20,350 Practical agent behavior from, from, from LLMs in, in a way that I think is, is a, and, and, and all it is is, I'm not 763 00:43:20,350 --> 00:43:28,000 trying to sort of nerd out here other than just saying that like the layers are gonna slowly emerge where basically 764 00:43:28,030 --> 00:43:35,770 LLMs and related reasoning technologies has become the kind of baseline technology that everything's based built 765 00:43:35,845 --> 00:43:36,135 Alex: yeah. 766 00:43:36,155 --> 00:43:39,415 But I, I, I agree and I think we we're gonna see a lot of rapid growth. 767 00:43:39,515 --> 00:43:40,815 All, all, all I'm saying is like. 768 00:43:41,470 --> 00:43:48,460 The, the, these types of technology can, I don't know, but can and often show the fact that like, you make 769 00:43:48,460 --> 00:43:52,330 a ton of progress in the beginning, you know, as humans we got faster and 770 00:43:52,330 --> 00:43:56,560 we started riding horses and we made faster cars and then we built rockets. 771 00:43:56,610 --> 00:43:59,760 And if you, if you, if you looked at that trajectory, we would 772 00:43:59,760 --> 00:44:02,790 say, well, in a hundred years we'll be going faster than light. 773 00:44:02,850 --> 00:44:03,870 That doesn't happen. 774 00:44:04,215 --> 00:44:11,175 Troy: Well, I think the lighting, the, the, the approaching light, which is sort of insight abstraction, reasoning, 775 00:44:11,325 --> 00:44:15,795 asking right questions, not being prompted, those kinds of human-like 776 00:44:15,795 --> 00:44:22,005 connections that are born of us being, you know, long standing sensory creatures. 777 00:44:22,455 --> 00:44:22,785 Right? 778 00:44:22,785 --> 00:44:24,975 Like that is not coming immediately. 779 00:44:25,245 --> 00:44:26,385 I totally agree with you. 780 00:44:26,385 --> 00:44:27,795 I think it's a great example. 781 00:44:28,215 --> 00:44:29,955 I think it's a, or analogy rather. 782 00:44:30,255 --> 00:44:39,855 So I had two items, Brian, and one was a, a, a sort of just slight reflection on the newsletter and the other one was trying, 783 00:44:39,855 --> 00:44:48,246 I, Alex sort of shows up in my dreams sometimes and it, it was really trying to envision, I think it's really interesting. 784 00:44:48,246 --> 00:44:48,846 Let's start here. 785 00:44:48,996 --> 00:44:58,236 It's really interesting right now to try to envision what the new normal is or the new model or the new system that replaces. 786 00:44:58,700 --> 00:45:01,610 What we know as of, of the system of the open web. 787 00:45:02,015 --> 00:45:02,465 Okay. 788 00:45:02,705 --> 00:45:12,005 Which is, you know, Google is center, you know, referrals via links, web pages, affiliate revenue banners, 789 00:45:12,185 --> 00:45:19,145 YouTube, you know, the pressure of social media, challenging kind of, you know, old, old legacy media conventions. 790 00:45:19,355 --> 00:45:23,015 All of those things are what we understand to be the web happening for a long time. 791 00:45:23,015 --> 00:45:23,285 Right? 792 00:45:23,495 --> 00:45:33,185 And now we've got this new thing and where knowledge is abstracted in real time from, you know, all of human 793 00:45:33,185 --> 00:45:37,415 knowledge where everything starting with, you know, evergreen content 794 00:45:37,415 --> 00:45:41,405 and service content can be sort of infinitely personalized for you. 795 00:45:41,795 --> 00:45:45,575 And it's super cool and everybody I talk to from like. 796 00:45:46,060 --> 00:45:52,780 You know, the people in my circle, my wife, my wife's friends, stuff like are shifting quicker than 797 00:45:52,780 --> 00:46:00,370 I would've thought to using, you know, chat GPT as as an effective or related tools as effective tools. 798 00:46:00,640 --> 00:46:08,470 And so like what it's, it's interesting for me to think about what that new model looks like and how it sustains itself. 799 00:46:08,560 --> 00:46:15,940 And I think we get really caught up in the fact that, well, we'll have the snake eating its tail problem where, you 800 00:46:15,940 --> 00:46:19,630 know, there will be no content 'cause there's no banners to run on webpages 801 00:46:19,630 --> 00:46:23,530 and people can't, aren't incented to make content and get traffic from Google. 802 00:46:23,980 --> 00:46:28,390 And, and I actually don't think, I think that there is a new ecosystem 803 00:46:28,390 --> 00:46:33,910 and it won't, and, and we will find ways obviously to, to make it pay. 804 00:46:34,415 --> 00:46:39,551 and, and that, that like slowly, kind of like Alex's analogy. 805 00:46:39,551 --> 00:46:47,141 First we're gonna see the quick, you know, slurping of the most fundamental tier of knowledge. 806 00:46:47,411 --> 00:46:51,131 And then we're gonna move into news and more real time stuff. 807 00:46:51,281 --> 00:46:54,191 And there'll be new pressures on, you know, whose content is that? 808 00:46:54,191 --> 00:46:55,811 How am I getting paid in all of that. 809 00:46:56,221 --> 00:46:59,791 And other stuff will become more conversational, as you've pointed out, Brian. 810 00:47:00,091 --> 00:47:03,991 So we're gonna see more media move to, you know, audio, video. 811 00:47:04,441 --> 00:47:07,351 And yeah, there'll still be newsletters and there'll still be the odd 812 00:47:07,351 --> 00:47:10,171 website and people will still like to read humans and all of that. 813 00:47:10,507 --> 00:47:17,107 But the shape of the web, I, I'm really interested in, in how we start to think about the new shape. 814 00:47:17,578 --> 00:47:18,388 Does that make sense? 815 00:47:18,817 --> 00:47:25,297 Like what it actually, what is the new normal that we all sort of see as this ecosystem that's replaced the open web? 816 00:47:25,867 --> 00:47:30,847 And while we can, you know, and it's top of mind right now because. 817 00:47:31,684 --> 00:47:35,389 Like open AI is going out, the government's doing this, this, 818 00:47:35,389 --> 00:47:40,799 this, this process led by, what's his dingle from all in 819 00:47:41,249 --> 00:47:41,669 David 820 00:47:41,669 --> 00:47:42,449 Sachs. 821 00:47:43,094 --> 00:47:43,904 Brian: Jason isn't in 822 00:47:43,919 --> 00:47:46,499 Troy: they're asking for comments around the new AI 823 00:47:46,559 --> 00:47:46,769 Alex: Yeah. 824 00:47:46,769 --> 00:47:48,059 Jason's the dingle 825 00:47:48,299 --> 00:47:48,659 Troy: Right? 826 00:47:48,664 --> 00:47:48,734 Okay. 827 00:47:48,929 --> 00:47:50,489 So, so they're asking for comments. 828 00:47:50,489 --> 00:47:54,299 What OpenAI is saying is you can't restrict us from sucking up knowledge 829 00:47:54,299 --> 00:47:57,509 that should be considered, you know, open and available to us. 830 00:47:57,509 --> 00:47:57,869 Right? 831 00:47:58,439 --> 00:48:05,499 And what Meta is saying is you gotta encourage the growth of open of, of open source models. 832 00:48:06,129 --> 00:48:10,749 And what Anthropic is saying is, oh, please make sure that we're safe. 833 00:48:12,249 --> 00:48:15,489 Create a mechanism so government can review and shut down, you know, models 834 00:48:15,489 --> 00:48:18,639 that become too powerful and everybody's sort of talking in their book, right? 835 00:48:19,143 --> 00:48:24,903 and, and oh yeah, Google's saying, don't sue us if someone uses our model to make a bomb. 836 00:48:25,783 --> 00:48:26,743 Like that's their line. 837 00:48:26,743 --> 00:48:32,353 So all of these are things are coming from the big lobbying efforts of these big, you know, organizations. 838 00:48:32,803 --> 00:48:40,463 And we're, we're, we're just in the middle of working through kind of what this new world's gonna look like and who gets what, 839 00:48:40,944 --> 00:48:45,774 like who becomes the subsistence farmer and who's gonna have all the power much 840 00:48:45,774 --> 00:48:49,734 like we, you know, have today, and what the rest of the ecosystem looks like. 841 00:48:49,944 --> 00:48:53,634 And I think that, like, what I'd like to get to between us or in 842 00:48:53,634 --> 00:48:58,284 my mind is a, a very simple way of describing this new world. 843 00:48:58,854 --> 00:49:05,994 What it looks like, and it's, and it all starts with y your kind of like view, Alex, that started, I would say a year or 844 00:49:05,994 --> 00:49:09,924 two ago, or a year and a half ago on the podcast, is like, everything's changing. 845 00:49:10,411 --> 00:49:17,041 the spaceship's over the White House, and you know, media as you know, it is dead and it's all good. 846 00:49:17,534 --> 00:49:20,054 It's all gonna be okay because I 847 00:49:20,174 --> 00:49:21,704 Alex: I don't know if I, I don't know if I said that. 848 00:49:22,355 --> 00:49:23,045 Troy: uh, Because I can 849 00:49:23,250 --> 00:49:25,595 Brian: Is that where step two is a question mark? 850 00:49:25,955 --> 00:49:27,335 It's all good as step three. 851 00:49:29,045 --> 00:49:30,005 Troy: What does it look like? 852 00:49:30,035 --> 00:49:31,295 Is that a, I mean, that's me 853 00:49:31,327 --> 00:49:32,045 doing this. 854 00:49:32,555 --> 00:49:33,125 I'm sorry. 855 00:49:33,125 --> 00:49:37,385 I'm sorry I laid a lot out there, but what does that new world look like to you, Brian? 856 00:49:37,430 --> 00:49:39,200 Brian: isn't that what this podcast is about? 857 00:49:39,365 --> 00:49:39,905 Troy: Right. 858 00:49:40,355 --> 00:49:42,305 Answer the que You just asked me a question. 859 00:49:42,680 --> 00:49:45,110 Brian: Well, you don't wanna answer the question about what the podcast is about. 860 00:49:45,140 --> 00:49:46,370 I don't know what that world is like. 861 00:49:46,370 --> 00:49:48,171 I think we're just still, we're trying to figure it out. 862 00:49:48,355 --> 00:49:50,030 And does anyone know what it, 863 00:49:50,030 --> 00:49:50,570 it, 864 00:49:50,915 --> 00:49:51,170 Alex: yeah, 865 00:49:51,275 --> 00:49:53,135 I mean, no, I mean, I don't, 866 00:49:53,330 --> 00:49:54,890 Troy: You can you feel me at least? 867 00:49:55,220 --> 00:49:56,390 Alex: Yeah, I can feel you. 868 00:49:56,450 --> 00:50:01,736 I mean, it's, feels like a trailer for this podcast, what you just said, because that's essentially all we talk about. 869 00:50:01,916 --> 00:50:02,246 But 870 00:50:02,406 --> 00:50:03,425 Brian: thought that was what it about. 871 00:50:03,725 --> 00:50:06,245 I mean, other than the midlife crises, I thought that was what this is 872 00:50:06,350 --> 00:50:06,645 Alex: Yeah. 873 00:50:07,095 --> 00:50:07,697 Part of that. 874 00:50:07,747 --> 00:50:09,547 no, I, I think, I think you're right, though. 875 00:50:09,641 --> 00:50:16,091 the thing is like, it feels like in some ways that you can kind of look at the consumer proposition pretty clearly, 876 00:50:16,121 --> 00:50:22,191 which is, you know, I'm gonna talk to my computer and my computer's gonna give me stuff, and that, that stuff is going to 877 00:50:22,191 --> 00:50:30,511 either be regurgitated you know, in any format that I want audio, video, text, or, you know, it might be able to surface 878 00:50:30,511 --> 00:50:34,201 a specific piece of content from YouTube, et cetera, that I can consume like that. 879 00:50:34,231 --> 00:50:39,601 But, you know, e everybody, the, the most valuable space in, in technology, 880 00:50:39,601 --> 00:50:43,861 what everybody realized is, is that it's, it's, you want to be the interface, right? 881 00:50:43,861 --> 00:50:45,121 Google started showing flights. 882 00:50:45,151 --> 00:50:48,841 Google started showing weather Google, you know, like, because they don't technically 883 00:50:48,901 --> 00:50:50,971 Troy: The Europeans don't want Google doing that 884 00:50:51,061 --> 00:50:53,191 Alex: Right, but I mean, good for them. 885 00:50:53,191 --> 00:50:53,461 Right? 886 00:50:53,461 --> 00:50:54,061 I, I agree. 887 00:50:54,061 --> 00:50:56,281 But like everybody wants to own the interface. 888 00:50:56,281 --> 00:50:58,891 Apple wants you to stay on their Apple News product. 889 00:50:58,921 --> 00:51:01,021 Every, nobody wants you to go to the web. 890 00:51:01,321 --> 00:51:02,671 Nobody wants you to go to the web. 891 00:51:02,671 --> 00:51:11,701 So that, that, the tension there now is that these systems require people on the web, you know, which is this kind of great 892 00:51:11,701 --> 00:51:16,561 distribution mechanism to make things so that they can feed it to their consumers. 893 00:51:16,561 --> 00:51:16,891 Right? 894 00:51:17,101 --> 00:51:23,731 And if, and, and, and the trade used to be like, you know, we'll put ads on that and, and you'll get a sense on, on the click. 895 00:51:24,041 --> 00:51:30,311 I don't think that any mechanism right now has been figured out to, to generate that transaction. 896 00:51:30,311 --> 00:51:32,741 And in part because they've just stolen all that stuff. 897 00:51:32,741 --> 00:51:38,261 Like, I mean, let's be fair, they, they, you know, they're, they're using fair use, but they've just gobbled it all up. 898 00:51:38,261 --> 00:51:42,501 And, and that's fine for now, but a lot of these sites are gonna be running on fumes. 899 00:51:42,501 --> 00:51:43,641 And when they shut down. 900 00:51:44,106 --> 00:51:48,346 They're just gonna run out of data or they're gonna be ingesting data that that 901 00:51:48,421 --> 00:51:52,291 Troy: Or, or they make you a subsistence farmer, which is really what will happen. 902 00:51:52,611 --> 00:51:59,001 Alex: I mean, yes, but I think like the sub, you know, it, it feels a little bit like in the Mediterranean 903 00:51:59,001 --> 00:52:04,041 at some point they were kind of scraping the ocean with those nets to just capture all the food there. 904 00:52:04,041 --> 00:52:10,191 And, and they decimated escaping, escaping the sea bottom, and they decimated parts of that, that ocean floor. 905 00:52:10,191 --> 00:52:11,451 And there's nothing there anymore. 906 00:52:11,691 --> 00:52:13,551 I, I, I think that that's the risk 907 00:52:13,711 --> 00:52:15,816 Troy: It's still a, still a great place to visit. 908 00:52:15,946 --> 00:52:19,276 Brian: well, yeah, I was on Corsica and there's no fish like fresh fish from 909 00:52:19,276 --> 00:52:19,846 Corsica. 910 00:52:20,392 --> 00:52:24,440 Alex: The subsist I think the subsistence farming era was Google. 911 00:52:24,944 --> 00:52:26,114 Right now. 912 00:52:26,144 --> 00:52:32,174 Now it's the kind of like scorched earth era, because I don't see how anybody makes money. 913 00:52:32,324 --> 00:52:35,174 I see all the value for the consumer a hundred percent. 914 00:52:35,234 --> 00:52:38,444 I, I, I keep saying that this is the interface that people want. 915 00:52:38,834 --> 00:52:43,574 But there is, there is very little brand building in that 916 00:52:43,769 --> 00:52:47,849 Troy: Hey, I would just ask you, dude, when the robots are making 917 00:52:47,849 --> 00:52:51,719 everything, which is gonna happen, and it's not gonna take that long, right? 918 00:52:51,719 --> 00:52:58,049 When they're doing the assembly lines and they're fixing my you know, my sink and all that stuff we need something to do. 919 00:52:58,505 --> 00:52:59,345 We make media. 920 00:52:59,405 --> 00:53:00,425 That's all we got to do. 921 00:53:00,815 --> 00:53:02,435 We make and we consume media. 922 00:53:02,881 --> 00:53:03,451 Alex: it's true. 923 00:53:03,706 --> 00:53:07,126 They'll just be, I mean, are you say so, so your hypothesis is, I think 924 00:53:07,126 --> 00:53:10,238 I, we had talked about that before, but like, eventually, like people 925 00:53:10,306 --> 00:53:13,426 will always, yeah, people will always create media, right? 926 00:53:13,426 --> 00:53:14,386 People create media. 927 00:53:14,386 --> 00:53:17,976 They won't be peeling carrots or cleaning toilets for fun. 928 00:53:17,976 --> 00:53:19,806 But, but, but they will always 929 00:53:19,903 --> 00:53:20,916 create media for fun. 930 00:53:20,916 --> 00:53:21,156 And, 931 00:53:21,486 --> 00:53:22,866 and, and with the right amount of 932 00:53:22,896 --> 00:53:27,936 Troy: And the rest of them will be paid a little bit and then they'll be the craftspeople, the pucks, the people like 933 00:53:28,266 --> 00:53:29,016 Alex: yeah, look at us. 934 00:53:29,016 --> 00:53:32,376 Look at, look, look at the amount of value we generate for free. 935 00:53:32,781 --> 00:53:33,471 Sorry, somebody's 936 00:53:33,471 --> 00:53:34,194 at the door. 937 00:53:34,194 --> 00:53:34,350 I, 938 00:53:34,395 --> 00:53:36,227 I'm gonna have to, it's my heart Stop. 939 00:53:36,227 --> 00:53:36,527 It's my 940 00:53:36,535 --> 00:53:36,767 heart. 941 00:53:36,767 --> 00:53:37,087 Stop. 942 00:53:37,087 --> 00:53:37,214 Brian: Yeah. 943 00:53:37,214 --> 00:53:38,954 I know this is, Alex has a hard stop. 944 00:53:38,954 --> 00:53:39,382 Troy: Alex, I 945 00:53:39,382 --> 00:53:39,832 love you. 946 00:53:39,862 --> 00:53:40,252 Thank you 947 00:53:40,357 --> 00:53:40,887 Alex: Love you too. 948 00:53:40,947 --> 00:53:41,167 Bye. 949 00:53:41,578 --> 00:53:41,998 Troy: Okay, 950 00:53:42,103 --> 00:53:42,793 Brian: Um, 951 00:53:42,883 --> 00:53:53,428 Troy: before we bring on a ab anonymous banker I also had a thought about emotion and how sometimes I feel 952 00:53:53,428 --> 00:53:59,158 like our newsletter has like too much substance and not enough emotion. 953 00:53:59,648 --> 00:54:05,796 Like we should just be kinda lighter or we should talk about things that make people feel things like productivity. 954 00:54:05,796 --> 00:54:10,632 I. People like that productivity newsletter was shared and read by 955 00:54:10,632 --> 00:54:13,962 more people than any of the other stuff that seemed smarter to me. 956 00:54:14,270 --> 00:54:19,241 Brian: What, Troy, why do you think everyone who creates content on the internet becomes a life coach? 957 00:54:19,732 --> 00:54:24,832 It's the inevitable arc. You can start wherever you want, but if you create internet, if you create 958 00:54:24,832 --> 00:54:27,592 content on the internet long enough, you become a life coach. 959 00:54:27,592 --> 00:54:28,172 That's my theory. 960 00:54:28,612 --> 00:54:28,822 Why? 961 00:54:28,942 --> 00:54:32,362 Like Scott Galloway is now like, he's like trying to save young men. 962 00:54:32,422 --> 00:54:34,402 He was like a marketing professor at NYU. 963 00:54:34,402 --> 00:54:39,253 Wasn't he like with, with, I mean, I, I admire it. 964 00:54:39,253 --> 00:54:39,433 It's 965 00:54:39,463 --> 00:54:40,873 Troy: Will you do me a favor? 966 00:54:40,873 --> 00:54:43,963 Will you write a little bit about that notion in my question 967 00:54:44,023 --> 00:54:44,263 Brian: this 968 00:54:44,713 --> 00:54:48,463 Yeah, no, I mean if like this ad tech thing doesn't work out, I mean, I'm 969 00:54:48,463 --> 00:54:53,127 happy to go into, if anyone wants any life advice, I'm open for business. 970 00:54:53,589 --> 00:54:54,939 no, I think people do like that. 971 00:54:55,029 --> 00:54:55,509 I agree. 972 00:54:55,976 --> 00:55:02,915 Troy: I was inspired with that thought by listening to God Help me, a Semaphore podcast where they were interviewing 973 00:55:02,915 --> 00:55:08,377 this guy Frank Cooper, who's now the CMO of Visa, who used to work at Def Jam 974 00:55:08,867 --> 00:55:09,047 Brian: Yeah. 975 00:55:09,047 --> 00:55:10,247 He wasn't he at Pepsi. 976 00:55:10,592 --> 00:55:11,462 Troy: yeah, he was at Pepsi. 977 00:55:11,462 --> 00:55:14,762 And, and he, his point was like, what makes good hip hop? 978 00:55:15,242 --> 00:55:22,634 And his answer was, it's like, it's not about the best guys or the best rappers or the best lines. 979 00:55:22,634 --> 00:55:27,861 It's like, finding something that's within people, making them feel something 980 00:55:28,269 --> 00:55:28,529 Brian: All right. 981 00:55:28,629 --> 00:55:29,409 AB is here. 982 00:55:30,019 --> 00:55:30,804 AB: Hey, how's it going? 983 00:55:31,263 --> 00:55:31,553 Brian: Good. 984 00:55:31,870 --> 00:55:34,050 Can we go back to talk about the, the skim? 985 00:55:34,616 --> 00:55:35,006 Troy: No. 986 00:55:35,454 --> 00:55:42,804 the, the ab thesis for this week was that, you know, there's the cleanup acts in media that are going on right now. 987 00:55:42,804 --> 00:55:42,864 I 988 00:55:42,984 --> 00:55:44,484 Brian: Yeah, that's, that's the skim. 989 00:55:44,574 --> 00:55:44,754 That 990 00:55:44,799 --> 00:55:45,594 is the skim thing. 991 00:55:45,594 --> 00:55:45,684 The 992 00:55:45,914 --> 00:55:46,031 AB: And 993 00:55:46,139 --> 00:55:47,409 taste Taste made. 994 00:55:47,409 --> 00:55:49,299 to, you know, that's another, yeah. 995 00:55:49,670 --> 00:55:50,630 Brian: So these are just like. 996 00:55:51,118 --> 00:55:52,258 Capitulation deals. 997 00:55:52,258 --> 00:55:54,898 I mean, this is like going to the, the scrapyard. 998 00:55:55,367 --> 00:56:01,937 AB: I think people make a decision that, you know, the growth ahead is, there's a big question mark, and so 999 00:56:01,937 --> 00:56:07,547 there's a point in time now where you can potentially get out, there's a ton of these names, media names, that people 1000 00:56:07,547 --> 00:56:12,767 would recognize that are either for sale by bankers or informally you can acquire. 1001 00:56:12,767 --> 00:56:13,097 So. 1002 00:56:13,668 --> 00:56:18,438 Troy: you do They say for sale by owner in the, in the capital markets. 1003 00:56:20,782 --> 00:56:21,802 AB: I think it's just discu. 1004 00:56:21,832 --> 00:56:24,652 I mean, people just know where, where the for sale signs are. 1005 00:56:24,682 --> 00:56:29,762 I mean, one interesting thing someone asked me earlier this week is like, where's the wiz in media? 1006 00:56:29,817 --> 00:56:31,562 I, I don't think it can ever exist. 1007 00:56:31,767 --> 00:56:32,342 Brian: What you mean? 1008 00:56:32,342 --> 00:56:33,512 Nobody beats the wiz. 1009 00:56:33,812 --> 00:56:34,442 Troy: No, no, no. 1010 00:56:34,442 --> 00:56:38,282 The, the, the cyber, the, the cybersecurity company that sold 1011 00:56:38,317 --> 00:56:40,054 for $32 1012 00:56:40,057 --> 00:56:43,082 Brian: I, I see my, see, no, I, my, my mind was 1013 00:56:43,082 --> 00:56:44,072 in a totally different place. 1014 00:56:44,072 --> 00:56:44,290 I'm like, 1015 00:56:44,342 --> 00:56:45,797 AB: You're watching YouTube Too much. 1016 00:56:46,027 --> 00:56:46,317 Yeah. 1017 00:56:46,590 --> 00:56:48,690 Brian: Well, no discounts, discounting. 1018 00:56:48,690 --> 00:56:50,040 I mean, nobody beats The Wiz. 1019 00:56:50,070 --> 00:56:50,520 The Wiz. 1020 00:56:50,520 --> 00:56:54,840 This whole thing was that like, you know, he's got, he gets, you know, he is the lowest prices. 1021 00:56:54,840 --> 00:56:55,320 So I was just 1022 00:56:55,425 --> 00:56:55,845 Troy: four. 1023 00:56:55,845 --> 00:57:00,705 Israeli dudes just sold their company for $32 billion to Google. 1024 00:57:01,202 --> 00:57:01,412 AB: Yeah. 1025 00:57:01,412 --> 00:57:02,762 And under five years, right? 1026 00:57:02,762 --> 00:57:04,592 They created in, in 2020. 1027 00:57:05,342 --> 00:57:11,102 And it, it's, it's funny because in the press release, it's, it's an all cash, there's no earnout and it says subject 1028 00:57:11,102 --> 00:57:14,312 to adjustments, but the adjustments are pretty dim, minimis, probably. 1029 00:57:14,462 --> 00:57:14,852 So 1030 00:57:14,866 --> 00:57:18,076 Troy: Like for coffee and like other sundry 1031 00:57:18,122 --> 00:57:18,872 AB: working capital. 1032 00:57:19,292 --> 00:57:19,592 Yeah. 1033 00:57:19,758 --> 00:57:20,208 But I, yeah. 1034 00:57:20,208 --> 00:57:27,166 I, it is an, it's a, it's an interesting thought exercise of where some value can be created at that speed and scale. 1035 00:57:27,216 --> 00:57:30,666 I think a more easy thing to replicate is like the poppy example, Right. 1036 00:57:30,666 --> 00:57:31,266 I don't know if. 1037 00:57:31,536 --> 00:57:35,398 If you guys have, it's really interesting to watch their Shark Tank episode. 1038 00:57:35,518 --> 00:57:37,678 'cause it was a completely different idea back then. 1039 00:57:37,678 --> 00:57:41,188 And then they turned it, you know, they got a 25% investor. 1040 00:57:41,518 --> 00:57:43,768 One of the guests on Shark Tank invested in it. 1041 00:57:43,768 --> 00:57:45,868 He changed the branding. 1042 00:57:46,298 --> 00:57:48,278 He basically figured out that they had a great product. 1043 00:57:48,278 --> 00:57:52,028 They just needed to fix the branding and their go-to market strategy and created something that 1044 00:57:52,463 --> 00:57:59,853 Troy: But, but you, you can just look for those characteristics in different markets ab and those are the ability 1045 00:57:59,853 --> 00:58:06,523 to leverage business against a bigger distribution system and particularly something that's high margin, right? 1046 00:58:06,763 --> 00:58:09,215 So in the case of this the wiz. 1047 00:58:09,646 --> 00:58:14,176 Basically the hope would be that their product supercharges, Google's cloud 1048 00:58:14,176 --> 00:58:17,986 offering, which is very high margin and very important competitively. 1049 00:58:18,196 --> 00:58:20,626 In the case of Poppy, they go to Pepsi. 1050 00:58:20,626 --> 00:58:27,226 Pepsi has distributions in every distribution into every corner store on the planet, and they could, you 1051 00:58:27,226 --> 00:58:31,216 know, take you into, you know, any facility basically that they're in. 1052 00:58:31,276 --> 00:58:31,546 Right? 1053 00:58:31,546 --> 00:58:33,166 So the leverage on that brand is great. 1054 00:58:33,166 --> 00:58:40,756 It's the same thing when you see the eye rolling multiples at a revenue level with like someone who sells a tequila company 1055 00:58:40,996 --> 00:58:47,296 to one of the big, the two or three big, you know, hard liquor companies where they get the distribution advantage. 1056 00:58:47,506 --> 00:58:49,216 It happens in packaged goods too. 1057 00:58:49,306 --> 00:58:49,666 So, 1058 00:58:49,793 --> 00:58:51,225 AB: Well, they actually pick up a a ton. 1059 00:58:51,225 --> 00:58:54,045 'cause right now Poppy is distributed through the Anheuser-Busch network. 1060 00:58:54,045 --> 00:59:01,935 So you automatically actually pick up 20 to 30% of margin just by changing to the Pepsi distribution network. 1061 00:59:02,550 --> 00:59:02,551 Troy: Mm-hmm. 1062 00:59:03,020 --> 00:59:04,485 Brian: So what does that look like in media? 1063 00:59:04,945 --> 00:59:11,515 Troy: Well, the only place it looks like that in media, I think is where you have super valuable IP that's not 1064 00:59:11,705 --> 00:59:17,685 whose monetization's not being realized because of either some, you know, 1065 00:59:17,805 --> 00:59:21,555 subscription ad selling or distribution mechanism that's underutilized. 1066 00:59:22,113 --> 00:59:28,486 So if you owned before it was a big thing like Pixar going to Disney, right? 1067 00:59:28,486 --> 00:59:30,916 Like Disney could make a lot out of that asset. 1068 00:59:31,379 --> 00:59:33,269 So that would be the example that I would give. 1069 00:59:33,794 --> 00:59:39,484 Or on the small side I don't know who's got great IP that sells it, you know, in a limited way. 1070 00:59:39,484 --> 00:59:40,984 Bars still selling to Penn. 1071 00:59:41,475 --> 00:59:48,119 AB: Yeah, you see some of this, it's, it's an interesting way to gauge ip, but I bumped into a company last week 1072 00:59:48,119 --> 00:59:55,079 that is gonna do, it's like an agency with college creators and they're, they did a couple million of revenue 1073 00:59:55,079 --> 00:59:58,589 last year and they're on track to do 50 million of revenue this year. 1074 00:59:58,859 --> 01:00:04,882 Basically because there's so much brand dollars flowing into the creator space and there's not amazing places suspend it. 1075 01:00:04,882 --> 01:00:06,862 So this operating team. 1076 01:00:07,331 --> 01:00:11,231 Has basically become a beacon of a lot of brand money. 1077 01:00:11,381 --> 01:00:14,111 And it's profitable, it's growing the other place. 1078 01:00:14,111 --> 01:00:14,591 I see. 1079 01:00:14,951 --> 01:00:21,236 'cause I think there's like a, a, a deal news that the Boston Celtics just sold for what six or 7 billion is 1080 01:00:21,236 --> 01:00:26,666 in this need around sports rights to continue to monetize the media side. 1081 01:00:26,886 --> 01:00:32,046 Because as the linear deals go down in value, they're gonna have to figure out ways to monetize the YouTube and 1082 01:00:32,046 --> 01:00:35,346 other digital rights, because that's the only thing underpinning a lot of the. 1083 01:00:35,770 --> 01:00:37,210 Value of the sports teams. 1084 01:00:37,270 --> 01:00:43,180 So I, I think there will be continued new company creation and values growing in companies around sports 1085 01:00:43,180 --> 01:00:46,750 teams and athletes and creators to better monetize that content. 1086 01:00:47,095 --> 01:00:50,950 Brian: Yeah, I did you see like Unilever wants to spend like 50% 1087 01:00:51,130 --> 01:00:53,920 of like their marketing on like creators, something like that. 1088 01:00:53,980 --> 01:00:55,945 And I just wonder where is that gonna go? 1089 01:00:56,410 --> 01:01:00,400 AB: I think what there's the, the consum, what it is like the consumers, I think we wrote about this, like 1090 01:01:00,400 --> 01:01:03,670 30 to 50% of their time is on, are on these different social platforms. 1091 01:01:03,670 --> 01:01:06,910 So it's more about chasing the eyeballs, but it's tough, right? 1092 01:01:06,910 --> 01:01:11,770 It's like it's gonna go either to the platforms directly or some of these different. 1093 01:01:12,270 --> 01:01:16,987 You know, there's a, a business that's about to be sold that layers on top of 1094 01:01:16,987 --> 01:01:21,937 YouTube that helps to better organize the inventory for brands to spend. 1095 01:01:21,937 --> 01:01:23,347 It's, it's a big business. 1096 01:01:23,347 --> 01:01:29,297 It's 30 million of ebitda illustrated a really good multiple, and it's just like a layer layered on top of the YouTube 1097 01:01:29,687 --> 01:01:33,017 advertising ecosystem, and it helps brands better target their consumers. 1098 01:01:33,456 --> 01:01:39,069 Troy: And on the ad side, I wonder if we don't see those multiples in, what's the 1099 01:01:39,069 --> 01:01:44,599 name of that ad network that's trading at bonkers multiples the mobile game app. 1100 01:01:44,599 --> 01:01:44,839 Love. 1101 01:01:44,839 --> 01:01:51,769 And I wonder if that one isn't driven, partly because it would be very useful to someone like Apple, 1102 01:01:52,379 --> 01:01:53,789 Brian: It's like an alternative to Apple, isn't it? 1103 01:01:54,179 --> 01:01:54,599 Troy: right? 1104 01:01:54,599 --> 01:01:56,899 But someone sees an opportunity. 1105 01:01:57,169 --> 01:02:00,199 I mean, it's, it's, it's beyond multiple comprehension, isn't it, 1106 01:02:00,247 --> 01:02:00,937 AB: I mean, it's trading. 1107 01:02:01,027 --> 01:02:01,327 yeah. 1108 01:02:01,717 --> 01:02:07,567 And then, I mean, the whole thing is like they've cornered the market in terms of driving app installs, and there's a 1109 01:02:07,567 --> 01:02:12,067 couple ecosystems that they play into for example, like casual gaming, it, it. 1110 01:02:12,503 --> 01:02:17,873 It exists because it's basically farming a user for three to six months in terms of showing 'em ads, 1111 01:02:17,873 --> 01:02:20,603 and then as soon as they get tired of that game, moving into the next. 1112 01:02:20,603 --> 01:02:26,483 So you need these ad networks that can do app installs and other things to drive consumers to the next app. 1113 01:02:26,954 --> 01:02:30,019 Brian: It's basically most of mobile gaming is arbitrage. 1114 01:02:30,739 --> 01:02:31,029 Yeah. 1115 01:02:31,534 --> 01:02:31,894 It's great. 1116 01:02:31,894 --> 01:02:32,854 Arbitrage is everything. 1117 01:02:33,169 --> 01:02:39,707 AB: It's like plugging people into this matrix of just go, taking their attention for an hour or two a day, getting them 1118 01:02:39,707 --> 01:02:43,302 highly addicted to a game for three to six months, and then moving them to the next. 1119 01:02:43,517 --> 01:02:52,007 Troy: You know what's amazing ab is that the contrast between market reception to something like app loving, which is, 1120 01:02:52,037 --> 01:02:58,367 you know, an ad network that focuses on a certain, you know, inventory type and, and, and consumer behavior 1121 01:02:58,817 --> 01:03:06,915 to Tabula that focuses on a different inventory type that has incredibly broad distribution penetration, but 1122 01:03:06,915 --> 01:03:10,965 can't seem to get out of the, like doldrums from a valuation perspective. 1123 01:03:11,437 --> 01:03:16,464 AB: Yeah, I mean, I think the ad product, I mean, tabula continues to try to innovate its different ad products and 1124 01:03:16,464 --> 01:03:19,704 they mentioned they're getting into performance with Microsoft and MSN. 1125 01:03:20,169 --> 01:03:24,189 I think that the app love and ad product actually works at a pretty high. 1126 01:03:24,549 --> 01:03:27,369 Like fidelity, and they're getting paid significantly for those 1127 01:03:27,369 --> 01:03:31,809 app installs, whereas everyone's encountered the tabula ads. 1128 01:03:31,839 --> 01:03:35,019 You land on pages that you're like, what is this? 1129 01:03:35,049 --> 01:03:35,319 Right? 1130 01:03:35,319 --> 01:03:37,089 It's like very weird. 1131 01:03:37,099 --> 01:03:38,124 Troy: Before and after. 1132 01:03:38,124 --> 01:03:39,564 It's before and after, man. 1133 01:03:39,952 --> 01:03:42,622 AB: It's, tricking a, it is tricking a subset of consumers 1134 01:03:42,622 --> 01:03:46,522 to buy stuff, but the majority of people literally exit out in two. 1135 01:03:46,642 --> 01:03:49,702 They're like, where, how did I accidentally land on this page? 1136 01:03:49,987 --> 01:03:52,205 Troy: toning skin, toning, dental 1137 01:03:52,550 --> 01:03:53,780 Brian: Yeah, just to put like numbers. 1138 01:03:53,780 --> 01:04:00,650 So App Loving stock is up 333% in the last year and Tablos is down 31%. 1139 01:04:00,980 --> 01:04:04,248 Hey, do you know what, what is going on with the Trade Desk? 1140 01:04:04,308 --> 01:04:12,463 It's funny 'cause they were the, the sort of standout of the Ad Tech publicly traded stocks and, and now 1141 01:04:12,968 --> 01:04:16,693 they're going through this this period where everyone's down on Trade Desk. 1142 01:04:17,130 --> 01:04:18,030 Do you follow that at all? 1143 01:04:18,150 --> 01:04:18,420 AB. 1144 01:04:18,715 --> 01:04:21,590 AB: I mean, I just Googled it so they didn't meet the revenue expectations, 1145 01:04:22,055 --> 01:04:22,275 Troy: For 1146 01:04:22,580 --> 01:04:24,830 one outta the last 20 quarters. 1147 01:04:24,830 --> 01:04:25,160 Yeah. 1148 01:04:26,000 --> 01:04:26,330 AB: yeah. 1149 01:04:26,750 --> 01:04:29,250 Brian: they're down 52% year to date. 1150 01:04:29,732 --> 01:04:32,552 AB: Yeah, I don't, I don't follow close enough to have a good perspective. 1151 01:04:33,031 --> 01:04:33,721 Troy: my take. 1152 01:04:33,901 --> 01:04:41,841 They're, the market is seeing that they're too reliant on, they have a lot of revenue in the page-based ecosystem. 1153 01:04:42,291 --> 01:04:43,281 They 1154 01:04:43,444 --> 01:04:49,952 didn't defy gravity, And that they're not penetrating you know, video is, or, or what do you call it? 1155 01:04:50,002 --> 01:04:52,192 CTV as well as people maybe hoped. 1156 01:04:52,540 --> 01:04:52,830 Brian: Yeah, 1157 01:04:52,866 --> 01:04:58,322 AB: If you look at like the, the Critio stock, you know, so much of, of when it was, it's, it's back to a, a relatively 1158 01:04:58,322 --> 01:05:03,748 good price, but so much of what was priced into it is their expectations of retail media and the growth. 1159 01:05:03,808 --> 01:05:04,798 And so a lot of these. 1160 01:05:05,143 --> 01:05:05,833 Stocks. 1161 01:05:05,863 --> 01:05:10,273 The reason why they're they trade up or down is because they come up with a thesis. 1162 01:05:10,273 --> 01:05:13,633 They say, we're gonna be able to grow to this much revenue in three years 1163 01:05:13,783 --> 01:05:16,873 because we believe the ad market is going to shift in this direction. 1164 01:05:17,338 --> 01:05:21,778 We know that agents, there's a lot of blockers for change in the ad world. 1165 01:05:21,778 --> 01:05:25,258 And so when that doesn't come to fruition as fast as people think, that's 1166 01:05:25,258 --> 01:05:28,948 what happened to Criteo is like they basically this was two Decembers ago. 1167 01:05:28,948 --> 01:05:31,918 They turned off their, they said, we're not gonna be able to hit our projections. 1168 01:05:31,918 --> 01:05:34,588 You know, this isn't coming to fruition as quickly as we thought. 1169 01:05:34,588 --> 01:05:40,048 And then the stock dropped 50% overnight and it was literally the last question on an earnings call. 1170 01:05:40,048 --> 01:05:41,878 Someone pushed in and, and figure this out. 1171 01:05:42,248 --> 01:05:44,318 And so I think that's what a lot of these companies are based on is. 1172 01:05:44,908 --> 01:05:48,238 Market forces, they, they don't, they're not completely in control of themselves. 1173 01:05:48,298 --> 01:05:51,568 They're hoping the buyers shift in a certain direction. 1174 01:05:51,958 --> 01:05:55,438 They can command more of the ad dollars and then take a higher margin. 1175 01:05:55,885 --> 01:05:56,095 Brian: Should we 1176 01:05:56,215 --> 01:05:56,875 Troy: other questions 1177 01:05:56,875 --> 01:05:59,635 I can give you a little, a little good product taste 1178 01:05:59,725 --> 01:06:00,535 if you want. 1179 01:06:03,877 --> 01:06:07,147 I'll get back to, to, you know, grocery items soon. 1180 01:06:07,147 --> 01:06:08,707 And then maybe electronic products. 1181 01:06:08,707 --> 01:06:12,967 Like, nobody wants to know that Dyson is a, you know, good cordless vacuum. 1182 01:06:12,967 --> 01:06:13,207 Right. 1183 01:06:13,207 --> 01:06:20,096 Uh, you know, clearly comedy's having a moment, and now comedy and politics are seemingly inseparable. 1184 01:06:20,516 --> 01:06:22,486 But there's a show I tuned on Lasette. 1185 01:06:22,726 --> 01:06:26,086 I'm not gonna put it up as good product, but it's maybe at a little bit of a lead in. 1186 01:06:26,566 --> 01:06:29,716 And it's called, last one, laughing. 1187 01:06:30,209 --> 01:06:30,869 Do you know the show? 1188 01:06:30,869 --> 01:06:34,229 It's being franchised into every, there's one in Germany, one in Canada, 1189 01:06:34,705 --> 01:06:41,067 and basically they put 10, 10 comedians in a room, and if you laugh, you lose. 1190 01:06:41,559 --> 01:06:43,989 And so then they set up a bunch of pranks to that. 1191 01:06:43,989 --> 01:06:50,259 They can all do, like, they put one of them on stage and he or she tries to get the room to laugh or they have, I don't 1192 01:06:50,259 --> 01:06:57,309 know, like just different kind of gags that, that are like, there's one thing where you put the person on a stool and 1193 01:06:57,309 --> 01:07:02,793 then all the other comedians get to come up and whisper something in their ear and to see if they can make them laugh. 1194 01:07:03,303 --> 01:07:05,463 And it's like not great. 1195 01:07:05,940 --> 01:07:07,440 Six hours of entertainment. 1196 01:07:07,440 --> 01:07:12,270 But it's a really interesting new format and it's on Amazon Prime, the UK one. 1197 01:07:12,270 --> 01:07:14,340 'cause the British are the funniest people. 1198 01:07:14,610 --> 01:07:19,680 I mean, if you loaded it up with really funny people in America, you might be able to make it work in the, you know, 1199 01:07:20,010 --> 01:07:24,090 people in the UK are, I mean, generally speaking, the British are funny. 1200 01:07:24,490 --> 01:07:25,885 I don't know about the German one. 1201 01:07:25,885 --> 01:07:27,535 That may be just ironically funny. 1202 01:07:27,535 --> 01:07:29,394 But anyway, last one. 1203 01:07:29,394 --> 01:07:29,754 Laughing. 1204 01:07:29,784 --> 01:07:32,334 Not quite a good product, but interesting experiment. 1205 01:07:32,814 --> 01:07:35,694 There's a good new Mo Black bag is a good movie, by the way. 1206 01:07:35,694 --> 01:07:44,991 It's a se Soderberg movie starring Kate Blanche and Fastbender Marissa Ella from Industry Tom Burke. 1207 01:07:45,411 --> 01:07:47,001 And it's perfect. 1208 01:07:47,001 --> 01:07:48,291 90 Minutes of Entertainment. 1209 01:07:48,861 --> 01:07:49,941 It's like. 1210 01:07:50,395 --> 01:07:52,195 A stylish spy thriller. 1211 01:07:52,195 --> 01:07:53,575 Everybody needs those. 1212 01:07:54,015 --> 01:07:56,535 And so I, I re But that's a good product for sure. 1213 01:07:56,655 --> 01:08:05,715 And the last one I would say is your friend Alex Kitz interviews Juan Koon on YouTube, where they talk about this 1214 01:08:05,715 --> 01:08:13,599 sort of existential question that we were talking about with Alex, which is when will AI make its own discoveries? 1215 01:08:13,899 --> 01:08:15,489 When will it show insight? 1216 01:08:15,849 --> 01:08:17,109 When will it ask? 1217 01:08:17,608 --> 01:08:20,613 Not answer questions, but maybe ask them, and 1218 01:08:20,703 --> 01:08:22,983 Brian: Koon is like a, he's a dor, isn't he? 1219 01:08:23,426 --> 01:08:23,846 Troy: I don't know. 1220 01:08:23,906 --> 01:08:25,646 I don't, I don't, no, I don't, I don't think so. 1221 01:08:25,646 --> 01:08:27,986 I think he's more of a kind of realist. 1222 01:08:28,448 --> 01:08:28,898 he's great. 1223 01:08:28,898 --> 01:08:30,248 We'll put the link in the notes. 1224 01:08:30,302 --> 01:08:33,062 I think Alex is a really informed, good interviewer. 1225 01:08:33,062 --> 01:08:33,962 I, I like watching 1226 01:08:34,040 --> 01:08:34,412 his stuff. 1227 01:08:34,437 --> 01:08:34,727 Brian: Good. 1228 01:08:34,927 --> 01:08:35,407 I like Alex. 1229 01:08:35,912 --> 01:08:36,212 All right. 1230 01:08:36,352 --> 01:08:37,977 You have a good product ab. 1231 01:08:38,454 --> 01:08:39,924 AB: Well, I have two, two comments. 1232 01:08:39,924 --> 01:08:47,739 One interesting thing in this world of content creation, comedians seem to be brought up more and more around like, 1233 01:08:47,739 --> 01:08:53,379 there's a business called Donut Media that sold to recurrent a few years ago, all in the auto space, and they 1234 01:08:53,379 --> 01:08:58,119 were basically able to arb the, the va, the cost of content creators by going 1235 01:08:58,119 --> 01:09:02,449 to these like second tier comedians and getting them to do YouTube shows. 1236 01:09:02,779 --> 01:09:03,349 So. 1237 01:09:03,709 --> 01:09:09,902 It's, it's an interesting thesis that people are using to basically find cheap content creators that are good, 1238 01:09:09,902 --> 01:09:16,342 that can do shows, be funny on the fly and they're not worried about them necessarily taking over a YouTube 1239 01:09:16,342 --> 01:09:19,702 channel or a brand where they become like the, the focus of attention. 1240 01:09:19,852 --> 01:09:24,322 So, I, I feel like being a, there's never been a better time to be a second tier comedian. 1241 01:09:24,531 --> 01:09:27,921 Troy: in other words, there's good multiples on second tier comedians right now. 1242 01:09:28,026 --> 01:09:28,574 Brian: you can ar, 1243 01:09:28,656 --> 01:09:29,286 you can arb. 1244 01:09:29,286 --> 01:09:30,361 Second tier comedians 1245 01:09:30,412 --> 01:09:35,032 AB: Most of them, you know, can't make, they're just happy to pay their rent and get health insurance. 1246 01:09:35,132 --> 01:09:38,402 And their desire is to be a comedian, not to be, not to be a media. 1247 01:09:38,672 --> 01:09:39,452 The other thing is 1248 01:09:39,812 --> 01:09:40,652 I ask people, 1249 01:09:40,861 --> 01:09:41,521 Brian: things don't change. 1250 01:09:41,521 --> 01:09:42,781 This is how media got built. 1251 01:09:42,841 --> 01:09:43,981 I mean, right. 1252 01:09:44,372 --> 01:09:44,732 AB: Yeah. 1253 01:09:45,109 --> 01:09:49,414 The other thing is it feels like I. So I ask people all the time, like, are you using ai? 1254 01:09:49,414 --> 01:09:53,884 And it feel, it, it finally feels like it's turning more into a tool versus a toy. 1255 01:09:54,094 --> 01:09:58,744 And even across age ranges, everyone seems to be using it now. 1256 01:09:58,774 --> 01:10:02,374 Like every call, even people that are older that I would never 1257 01:10:02,374 --> 01:10:05,374 think would use AI are like, oh yeah, I'm using it every day now. 1258 01:10:05,374 --> 01:10:09,034 So I think that's, this happened in the last few weeks and I've just 1259 01:10:09,034 --> 01:10:13,444 been surprised the the broad group of people that say they're using it. 1260 01:10:13,789 --> 01:10:20,373 On a daily basis, and actually big investors, other bankers people in corporate development. 1261 01:10:20,482 --> 01:10:21,347 Troy: Yeah, it's it. 1262 01:10:21,347 --> 01:10:23,267 It's the moment like when grandpa got on 1263 01:10:24,520 --> 01:10:25,000 AB: a hundred percent. 1264 01:10:25,501 --> 01:10:29,479 Brian: How is it used in like in your field, like how do you use it? 1265 01:10:29,890 --> 01:10:34,560 AB: I mean, so the, the simple example is you're going to a meeting with someone you didn't have time to prep. 1266 01:10:34,650 --> 01:10:39,630 You put in their name, you put in their company, and you tell deep research to tell you the things that have happened 1267 01:10:39,630 --> 01:10:42,570 in the last year, like what you should talk about, like simple things like that. 1268 01:10:42,984 --> 01:10:44,964 Say if we're taking a company to market in space. 1269 01:10:44,979 --> 01:10:47,829 Troy: That model you sent me the other day, did it do that? 1270 01:10:48,161 --> 01:10:49,301 AB: No, no. 1271 01:10:49,681 --> 01:10:55,531 There's a, there's a couple companies that we're testing out right now that are supposed to do this stuff, but I think 1272 01:10:55,531 --> 01:11:01,765 what's interesting is the, the underlying foundational models are actually getting better than the wrappers, right? 1273 01:11:01,765 --> 01:11:07,901 So there's a company called Rogo that's at a bunch of the banks helping people do presentations, but. 1274 01:11:08,469 --> 01:11:08,679 Chat. 1275 01:11:08,799 --> 01:11:11,439 BT has actually gotten better than that, so than that, that? 1276 01:11:11,529 --> 01:11:13,989 program at, at doing the, the work. 1277 01:11:14,139 --> 01:11:18,999 So it, there's nothing good in Excel modeling right now for buyer lists. 1278 01:11:19,029 --> 01:11:22,839 I mean, it's all the basics of, of a first or or second year analyst. 1279 01:11:23,049 --> 01:11:24,459 The models can do now. 1280 01:11:24,459 --> 01:11:28,269 And I think, I think where the junior level staff is gonna move as 1281 01:11:28,269 --> 01:11:31,684 more of a manager of these AI tools to just produce a lot more work. 1282 01:11:31,981 --> 01:11:33,871 Troy: will it buy me lunch this afternoon? 1283 01:11:34,346 --> 01:11:36,386 Will it send me a bottle of good tequila? 1284 01:11:36,814 --> 01:11:37,466 AB: Exactly. 1285 01:11:37,556 --> 01:11:37,946 Yeah. 1286 01:11:38,096 --> 01:11:44,936 I mean, that's, that's the pa, that's the future, and that's what I push A couple of these folks on is like the kinetic, 1287 01:11:45,206 --> 01:11:50,338 basically, where it's sitting on top of your CRM and saying, Hey, you should reach out to this person, da da, da. 1288 01:11:50,366 --> 01:11:51,236 Like that hasn't happened 1289 01:11:51,920 --> 01:11:55,520 Troy: That's it for this episode of people versus algorithms where each 1290 01:11:55,520 --> 01:12:00,104 week we uncover patterns shaping media culture and technology. 1291 01:12:00,508 --> 01:12:03,948 Big thanks as always to our producer, Vanja Arsenov. 1292 01:12:04,458 --> 01:12:09,138 She always makes us a little clearer and more understandable and we appreciate her very, very much. 1293 01:12:09,638 --> 01:12:13,088 If you're enjoying these conversations, we'd love for you to leave us a review. 1294 01:12:13,524 --> 01:12:16,184 It helps us get the word out and keeps our community growing. 1295 01:12:16,660 --> 01:12:18,350 Remember, you can find People vs. 1296 01:12:18,380 --> 01:12:22,820 Algorithms on Apple Podcasts, on Spotify, and now on YouTube. 1297 01:12:23,302 --> 01:12:25,592 Thanks for listening and we'll see you again next week. 1298 01:12:25,942 --> 01:12:26,282 Brian: All right. 1299 01:12:26,798 --> 01:12:28,573 This is a little bit of an uneven episode. 1300 01:12:28,908 --> 01:12:29,316 Troy: Alright. 1301 01:12:29,316 --> 01:12:30,006 Brian: be honest with you. 1302 01:12:30,006 --> 01:12:31,121 I gotta do my next