1 00:00:19,372 --> 00:00:23,492 S1: All right. Welcome to episode 494. Sorry, it's been a while. 2 00:00:23,852 --> 00:00:27,772 S1: Had some, uh, config issues been working on with the 3 00:00:27,772 --> 00:00:31,612 S1: home gear. I think I got them sorted out, and 4 00:00:31,612 --> 00:00:35,172 S1: we are ready to, uh, keep going. So my stress 5 00:00:35,172 --> 00:00:45,692 S1: and excitement levels continue to rise. Feeling basically unbelievably excited 6 00:00:45,692 --> 00:00:48,531 S1: about the future and, like, what we could potentially do 7 00:00:50,052 --> 00:00:52,892 S1: and like all the different ways that I'm using AI 8 00:00:52,972 --> 00:00:55,132 S1: and I'm trying to get other people to use AI. 9 00:00:55,692 --> 00:00:59,252 S1: I'm doing probably, I don't know, five sessions a week 10 00:00:59,252 --> 00:01:03,732 S1: with various friends, showing them how I'm building my stack, 11 00:01:03,732 --> 00:01:07,932 S1: how I'm building out my dachi, and how they can 12 00:01:07,972 --> 00:01:11,691 S1: build their own for their own purposes. A lot of 13 00:01:11,692 --> 00:01:14,932 S1: the stuff that I talked about in the augmented course 14 00:01:14,972 --> 00:01:19,112 S1: really is basically starting to happen, um, instantiated inside of 15 00:01:19,112 --> 00:01:27,232 S1: cloud code. So it's like this extreme optimism and thought 16 00:01:27,232 --> 00:01:31,472 S1: about possibilities and like, everything I could possibly do and 17 00:01:31,472 --> 00:01:36,712 S1: help other people, do, you know, escaping from the drudgery of, like, 18 00:01:36,752 --> 00:01:40,472 S1: corporate work? A lot of corporate work, not all corporate work, 19 00:01:40,512 --> 00:01:45,392 S1: of course. And just like thinking about a better future 20 00:01:45,592 --> 00:01:48,352 S1: and trying to actively build that future, especially when I 21 00:01:48,352 --> 00:01:52,712 S1: start talking about some of the stuff from previous episodes, 22 00:01:54,672 --> 00:01:59,032 S1: podcast episodes of the newsletter. And when I want to 23 00:01:59,032 --> 00:02:03,192 S1: call out is, uh, Damon, which is this new service 24 00:02:03,192 --> 00:02:07,912 S1: that I've stood up. So it's damon.com. And what I'm 25 00:02:07,912 --> 00:02:12,632 S1: essentially doing is bringing back this idea that I've always wanted, 26 00:02:14,152 --> 00:02:17,092 S1: I think, even before the book stuff that I think 27 00:02:17,092 --> 00:02:20,492 S1: this is like early 2000, there was this one service 28 00:02:20,532 --> 00:02:23,971 S1: in the past called Friendfeed, and I had it kind 29 00:02:23,972 --> 00:02:29,492 S1: of like integrated in my website at the time. And 30 00:02:29,492 --> 00:02:32,492 S1: what it did was it, it was able to follow 31 00:02:32,732 --> 00:02:35,892 S1: what you were doing on Reddit, on Facebook, whatever the 32 00:02:35,892 --> 00:02:38,091 S1: current services were at the time. I know Reddit was 33 00:02:38,091 --> 00:02:42,931 S1: definitely one of them. Uh, book feeds, RSS feeds, basically 34 00:02:43,492 --> 00:02:47,052 S1: you could subscribe to or you could publish like click 35 00:02:47,091 --> 00:02:50,492 S1: the options for all these different accounts and connect them. 36 00:02:51,371 --> 00:02:54,251 S1: And then when someone comes to your Friendfeed page, they 37 00:02:54,252 --> 00:02:57,251 S1: would see like the books that you're looking at, like 38 00:02:57,292 --> 00:03:00,092 S1: the stuff. Oh, it was upvotes as well. So we 39 00:03:00,091 --> 00:03:02,652 S1: could see what you upvoted on like Hacker News and 40 00:03:02,651 --> 00:03:05,811 S1: what you upvoted on Digg and what you upvoted on Reddit. 41 00:03:06,612 --> 00:03:11,251 S1: So it was like this live dashboard thing that was 42 00:03:11,252 --> 00:03:15,632 S1: going on with that person. It was just unbelievably awesome. 43 00:03:15,712 --> 00:03:19,552 S1: It was called Friendfeed, and I have always been trying 44 00:03:19,552 --> 00:03:24,232 S1: to get back to that thing. And so Damon is 45 00:03:24,232 --> 00:03:28,352 S1: essentially just like a more pure form of that because 46 00:03:28,352 --> 00:03:31,192 S1: rather than it being a third party service, the idea 47 00:03:31,192 --> 00:03:34,512 S1: is that each of us hosts our own just using 48 00:03:34,512 --> 00:03:38,992 S1: a common protocol, and we all just know how to 49 00:03:39,032 --> 00:03:42,192 S1: call it, you know, it's a common protocol. Therefore there's clients, 50 00:03:42,192 --> 00:03:45,712 S1: there's servers, and like it's very simple. But the idea 51 00:03:45,712 --> 00:03:50,272 S1: is that world. And it wouldn't just be humans that 52 00:03:50,272 --> 00:03:53,072 S1: have this right. It's it's also the businesses and the 53 00:03:53,072 --> 00:03:56,752 S1: buildings and everything. Um, so everything gets an API, but 54 00:03:56,752 --> 00:04:00,112 S1: it's like this format. But if I'm in a coffee 55 00:04:00,112 --> 00:04:03,872 S1: shop and, you know, I share people with things around me, 56 00:04:03,872 --> 00:04:06,992 S1: they have their favorite. Their top book is also their 57 00:04:06,992 --> 00:04:08,832 S1: top fantasy book is also The Name of the wind, 58 00:04:08,832 --> 00:04:13,142 S1: which is my top fantasy book. So it would show 59 00:04:13,142 --> 00:04:15,702 S1: me that right. My digital assistant would be able to say, hey, 60 00:04:15,742 --> 00:04:18,222 S1: you know, check out this person next to you. You 61 00:04:18,222 --> 00:04:20,942 S1: should say hi. They also love name of the wind. Boom. 62 00:04:20,982 --> 00:04:24,862 S1: Human connection. So everything comes back to the human connection 63 00:04:24,902 --> 00:04:28,462 S1: facilitated by the tech. So that was one of the 64 00:04:28,462 --> 00:04:32,582 S1: things I talked about a lot in a previous part 65 00:04:32,582 --> 00:04:37,061 S1: of the newsletter. I've been blogging like, absolutely crazy. Just 66 00:04:37,101 --> 00:04:45,421 S1: absolutely crazy. Like I've been blogging higher quality stuff. Um, 67 00:04:46,222 --> 00:04:51,702 S1: more thorough stuff. More well researched stuff. I've put out 68 00:04:51,702 --> 00:04:54,662 S1: probably ten of these in like the last month. It 69 00:04:54,662 --> 00:04:58,542 S1: is unbelievable the amount of output I've been able to 70 00:04:58,541 --> 00:05:02,022 S1: do because of Chi. All because of my AI stack. 71 00:05:02,342 --> 00:05:05,822 S1: Because what I'm now doing, my workflow now is to 72 00:05:05,862 --> 00:05:10,922 S1: use Whisper Flow to record into vim or record into 73 00:05:10,962 --> 00:05:15,162 S1: Apple notes or record into whatever. And then I just 74 00:05:15,162 --> 00:05:19,282 S1: copy and paste that into Kai and I say create 75 00:05:19,282 --> 00:05:23,042 S1: blog and it knows to not change my language. It 76 00:05:23,041 --> 00:05:26,362 S1: doesn't write anything for me. It just puts my language 77 00:05:26,362 --> 00:05:29,882 S1: in there. Um, I actually do have a rewrite command, 78 00:05:30,282 --> 00:05:34,842 S1: and if I use that, it's allowed to fix grammar 79 00:05:34,842 --> 00:05:37,762 S1: and typos and like sentence structure, but it's still not 80 00:05:37,762 --> 00:05:41,642 S1: allowed to change the content. And what happens is it 81 00:05:41,642 --> 00:05:45,041 S1: still reads exactly like me because all it did is 82 00:05:45,041 --> 00:05:48,202 S1: really clean up. Like, should that have been a semicolon 83 00:05:48,202 --> 00:05:52,322 S1: or a or a dash or a period or whatever? 84 00:05:53,362 --> 00:05:57,082 S1: And then I could say, okay, enrich. Okay. You know, 85 00:05:57,122 --> 00:05:59,522 S1: in like the movies it says like enhance. Well, now 86 00:05:59,522 --> 00:06:02,362 S1: I can say enrich. And what that does is it 87 00:06:02,362 --> 00:06:05,762 S1: goes and gets links, right? Because when I'm narrating, this 88 00:06:05,762 --> 00:06:10,102 S1: is insane. When I am narrating, I can literally in 89 00:06:10,101 --> 00:06:13,622 S1: Whisper flow. I say things like, yeah, and um, go 90 00:06:13,622 --> 00:06:16,982 S1: get a quote from Viktor Frankl about this and put 91 00:06:16,981 --> 00:06:21,502 S1: it here. Right. So I'm just narrating. I'm like, okay, 92 00:06:21,502 --> 00:06:24,102 S1: we need some data to back this one up. Um, 93 00:06:24,101 --> 00:06:28,862 S1: I'm talking about, you know, tech layoffs. So find the 94 00:06:28,862 --> 00:06:33,142 S1: latest data on this from a reputable source and link 95 00:06:33,182 --> 00:06:36,981 S1: to that here. Also create a visualization using our standard 96 00:06:37,182 --> 00:06:42,061 S1: D3 visualization. And boom. So I press enter to that thing. 97 00:06:42,782 --> 00:06:49,421 S1: And this thing fires off. And like 10s later I 98 00:06:49,462 --> 00:06:55,782 S1: have a linked like graph with real data and the 99 00:06:55,782 --> 00:06:59,742 S1: data sources listed and the data sources listed inside the graph. 100 00:07:01,902 --> 00:07:06,102 S1: It's all annotated, all the notes are there, and all 101 00:07:06,101 --> 00:07:09,602 S1: I did was talk. All I did was talk. It 102 00:07:09,602 --> 00:07:14,042 S1: is unbelievable. And, you know, for the longer ones, I 103 00:07:14,042 --> 00:07:16,802 S1: end up going back in multiple phases. But I'm working 104 00:07:16,802 --> 00:07:19,762 S1: on that workflow. Ideally, I'd like to have as much 105 00:07:19,762 --> 00:07:23,122 S1: of it as done as possible. What has not worked 106 00:07:23,122 --> 00:07:25,282 S1: for me is kind of like iterating back and forth. 107 00:07:25,322 --> 00:07:29,442 S1: It's no fun to do that. I prefer to either 108 00:07:29,442 --> 00:07:33,162 S1: just capture like violently and like this giant thing and 109 00:07:33,162 --> 00:07:37,202 S1: then just work from there, or try to have the 110 00:07:37,202 --> 00:07:46,202 S1: thought fully parsed out. Done. Inside of the note over to, 111 00:07:47,242 --> 00:07:49,722 S1: you know, Claude. And he just takes it and runs 112 00:07:49,722 --> 00:07:51,962 S1: with it and just knows I've got all these different 113 00:07:51,962 --> 00:07:56,042 S1: custom commands for adding links for cleanup. I have a 114 00:07:56,042 --> 00:08:00,242 S1: separate command for publishing, which does like editor type stuff. 115 00:08:00,682 --> 00:08:03,322 S1: So it makes sure none of the links are broken. 116 00:08:03,362 --> 00:08:07,502 S1: It it, uh. It'd make sure I don't have any 117 00:08:07,542 --> 00:08:10,822 S1: unsubstantiated claims that it thinks I should add data to 118 00:08:11,422 --> 00:08:13,582 S1: and stuff like that. It checks to make sure quotes 119 00:08:13,582 --> 00:08:16,582 S1: actually came from that person. Right. So I'm checking basically 120 00:08:16,582 --> 00:08:22,102 S1: for like, hallucinations and mistakes that I've made. I've got 121 00:08:22,102 --> 00:08:24,782 S1: a piece of errata for the newsletter that just went out. 122 00:08:25,262 --> 00:08:28,862 S1: So the open source package that does the bug bounty stuff, 123 00:08:28,902 --> 00:08:32,662 S1: searching for vulnerabilities that was not released by XPO. And 124 00:08:32,662 --> 00:08:35,022 S1: I guess this is a good example of how I'm 125 00:08:35,022 --> 00:08:38,862 S1: not using AI for for a whole lot of stuff 126 00:08:39,022 --> 00:08:42,422 S1: on the newsletter. Um, I actually wrote that and it 127 00:08:42,422 --> 00:08:47,102 S1: was incorrect. Um, I had just read both articles and 128 00:08:47,102 --> 00:08:50,622 S1: somehow in my mind I must have like crossed. I 129 00:08:50,622 --> 00:08:54,062 S1: don't know, cross pollinated or something. But anyway, yeah, that'll 130 00:08:54,102 --> 00:08:56,302 S1: be in the errata in the next newsletter. But since 131 00:08:56,302 --> 00:08:59,222 S1: I'm doing a podcast and it's after it, I can 132 00:08:59,222 --> 00:09:03,322 S1: correct it now. Uh, okay. What was I talking about? Yeah, 133 00:09:03,482 --> 00:09:09,122 S1: basically just this workflow is completely insane and I'm just 134 00:09:09,122 --> 00:09:13,761 S1: ultra excited about it now. All that to say, I'm 135 00:09:13,761 --> 00:09:17,282 S1: still extremely worried. Like I talked about in that other post, 136 00:09:17,402 --> 00:09:23,002 S1: that other post was talking about the. How worried I 137 00:09:23,002 --> 00:09:28,802 S1: am about the, uh, the future and especially for a 138 00:09:28,802 --> 00:09:33,561 S1: whole lot of workers globally, basically knowledge workers. I'm really worried. 139 00:09:33,922 --> 00:09:37,242 S1: And I'm not just worried about them. I'm worried about 140 00:09:37,242 --> 00:09:41,842 S1: systemic effects of them losing so many jobs and there 141 00:09:41,842 --> 00:09:47,281 S1: being some sort of like threshold where if it crosses that, 142 00:09:47,282 --> 00:09:50,562 S1: then enough people lose their jobs, it creates enough panic, 143 00:09:50,962 --> 00:09:56,442 S1: it creates enough reduction of income into local businesses, so 144 00:09:56,482 --> 00:09:59,842 S1: enough businesses close. So it kind of turns into like 145 00:09:59,881 --> 00:10:04,622 S1: a like a mini pandemic effect, where it's like every 146 00:10:04,662 --> 00:10:07,141 S1: I mean, that one was like different because it's so 147 00:10:07,142 --> 00:10:09,862 S1: obvious why it's happening. But in this case, it would 148 00:10:09,862 --> 00:10:13,021 S1: be like, oh, we're having some sort of economic meltdown. 149 00:10:13,302 --> 00:10:15,382 S1: And then so the business is closed because no one's 150 00:10:15,381 --> 00:10:17,902 S1: coming to the businesses, because they're panicking, because they don't 151 00:10:17,902 --> 00:10:21,502 S1: have any money. And it's just like this massive cascade effect. 152 00:10:21,942 --> 00:10:24,822 S1: So I'm really, really worried about that. And I'm really 153 00:10:24,822 --> 00:10:27,822 S1: worried about I don't think a lot of these people 154 00:10:27,822 --> 00:10:30,702 S1: are going to be able to reskill. I think this 155 00:10:30,702 --> 00:10:34,262 S1: whole reskilling narrative is like something we tell ourselves to 156 00:10:34,302 --> 00:10:36,942 S1: make ourselves feel good. And I'm not sure it's like 157 00:10:36,942 --> 00:10:42,742 S1: how realistic it is. And it's it's like, really, I 158 00:10:42,742 --> 00:10:45,462 S1: don't know. It's really depressing to me, the whole thing. 159 00:10:45,822 --> 00:10:49,182 S1: So thinking about that side of it and how little 160 00:10:49,182 --> 00:10:54,262 S1: I can possibly do is, is just not good for 161 00:10:54,261 --> 00:10:56,982 S1: me to dwell on. So I literally dwell on it. 162 00:10:57,022 --> 00:11:01,932 S1: I sit inside of the the suck, you know? And 163 00:11:01,932 --> 00:11:03,772 S1: I sit inside there and I'm like, what can I do? 164 00:11:03,812 --> 00:11:07,531 S1: What can I do? Um, how bad is it going 165 00:11:07,532 --> 00:11:09,651 S1: to be? I have to, you know, share how bad 166 00:11:09,652 --> 00:11:12,012 S1: it's going to be or whatever. So then I write 167 00:11:12,011 --> 00:11:15,052 S1: a post like that which goes into all the detail, 168 00:11:15,052 --> 00:11:17,172 S1: and I get it all out, and I basically put 169 00:11:17,172 --> 00:11:21,052 S1: it there, and then I like, basically say, okay, that's it. 170 00:11:21,252 --> 00:11:24,452 S1: We're not thinking about this anymore right now that we're 171 00:11:24,452 --> 00:11:28,131 S1: setting that aside because the solution is always the same. 172 00:11:28,652 --> 00:11:34,771 S1: The solution is to expand the mind to, you know, 173 00:11:34,812 --> 00:11:37,692 S1: brush that off to to have the stoic mindset and 174 00:11:37,692 --> 00:11:44,412 S1: be like, okay, yep, that super sucks. Okay. Well. Anyway. Right. 175 00:11:44,452 --> 00:11:47,612 S1: I've been talking about this human 3.0 thing. I did 176 00:11:47,612 --> 00:11:49,771 S1: that previous post called The End of Work. I didn't 177 00:11:49,772 --> 00:11:53,651 S1: think this would be happening this fast when I wrote that, but. 178 00:11:56,772 --> 00:11:59,552 S1: In end of work, I've already talked about it in 179 00:11:59,552 --> 00:12:04,031 S1: David Graeber's book Bullshit Jobs. Right. I've always seen this 180 00:12:04,032 --> 00:12:07,232 S1: current structure of like 9 to 5, and everyone, or 181 00:12:07,272 --> 00:12:10,312 S1: a vast majority of people can't stand to go to work. 182 00:12:10,631 --> 00:12:13,192 S1: It's cutting out 9 to 5 is the most important 183 00:12:13,232 --> 00:12:16,552 S1: hours of the day. And all they have time to 184 00:12:16,552 --> 00:12:19,912 S1: do is to get ready for the next day of work, 185 00:12:19,912 --> 00:12:21,592 S1: which they don't want to go to, to have a 186 00:12:21,592 --> 00:12:25,792 S1: bunch of stupid meetings. Like it? It's a bad situation 187 00:12:25,792 --> 00:12:28,752 S1: that we're in, right? It's also bad that it's going to, 188 00:12:29,272 --> 00:12:34,072 S1: you know, catastrophically come to an end. I would say, 189 00:12:34,352 --> 00:12:37,272 S1: or at least, you know, very badly come to an end, 190 00:12:38,032 --> 00:12:41,312 S1: I would say. Disruptively. Right. It's going to be extremely 191 00:12:41,312 --> 00:12:47,672 S1: disruptive to millions upon millions of people, maybe billions. I 192 00:12:47,672 --> 00:12:50,352 S1: don't know, it depends how you count, but it's going 193 00:12:50,392 --> 00:12:53,712 S1: to be massively disruptive to the global economy. What is 194 00:12:53,752 --> 00:12:58,932 S1: what is happening but going back to the positive, I 195 00:12:58,932 --> 00:13:01,772 S1: think that needs to happen. It needs to happen that 196 00:13:01,772 --> 00:13:06,372 S1: we get rid of this corporate structure. I mean, corp okay, 197 00:13:06,412 --> 00:13:09,531 S1: this all comes from the military, the hierarchy. You work 198 00:13:09,532 --> 00:13:14,692 S1: for Mr. Johnson. Mr. Johnson works for Mrs. Williams. Right. 199 00:13:14,692 --> 00:13:19,292 S1: And Mrs. Williams is trying to get her presentation together, uh, 200 00:13:19,292 --> 00:13:22,052 S1: to give to Mrs. Clark, because she's the one who 201 00:13:22,052 --> 00:13:24,212 S1: put all this together, and we're all just happy to 202 00:13:24,212 --> 00:13:31,772 S1: work for her. It's a very submissive, very hierarchical. Very 203 00:13:31,772 --> 00:13:37,292 S1: unhealthy structure to have. Most people in any company be 204 00:13:37,292 --> 00:13:42,532 S1: in this, like. Oh, yeah, I only contribute this little piece. Oh, 205 00:13:42,572 --> 00:13:45,652 S1: they don't ask me for ideas. I just help them 206 00:13:45,652 --> 00:13:48,132 S1: implement them. I'm just happy to be a part of it. 207 00:13:48,572 --> 00:13:54,372 S1: Like that's cool for 1950s or whatever. I mean, we 208 00:13:54,372 --> 00:13:56,872 S1: have to move through stages as humans. Well, it's time 209 00:13:56,872 --> 00:14:00,551 S1: to get out of this stage. We should all be founders. 210 00:14:00,552 --> 00:14:03,432 S1: We should all be CEOs, not not CEOs in the 211 00:14:03,432 --> 00:14:08,752 S1: old style. I'm using the CEO term for what it 212 00:14:08,752 --> 00:14:11,272 S1: is in the future, which won't be called a CEO. 213 00:14:11,312 --> 00:14:16,552 S1: We are all individual contributors to society and we should 214 00:14:16,552 --> 00:14:21,392 S1: be sharing with each other. We have companies. Yes, we have, 215 00:14:22,152 --> 00:14:27,512 S1: you know, products. Yes, we have offerings. Yes. And of course, 216 00:14:27,512 --> 00:14:32,112 S1: somebody gives us something in return for us giving them 217 00:14:32,112 --> 00:14:35,472 S1: that service. Right. So there's still a currency here, but 218 00:14:35,472 --> 00:14:38,792 S1: that currency won't be won't be based on this negative 219 00:14:38,792 --> 00:14:42,472 S1: infrastructure that we currently have, where it's all based on 220 00:14:42,472 --> 00:14:46,352 S1: your labor and it's all based on your, uh, you know, 221 00:14:46,392 --> 00:14:51,472 S1: your participation in this negative hierarchical structure that creates all 222 00:14:51,472 --> 00:14:54,372 S1: these bullshit jobs like David Graeber talks about in the book. 223 00:14:55,532 --> 00:14:59,452 S1: And the way I think about this is this is 224 00:14:59,452 --> 00:15:02,332 S1: just a natural progression. And this idea, I think I 225 00:15:02,372 --> 00:15:06,572 S1: got most from Harari and I can't remember which book 226 00:15:06,572 --> 00:15:08,252 S1: it was. I think it might have been the second 227 00:15:08,252 --> 00:15:15,292 S1: one after sapiens. They use so that basically what he 228 00:15:15,292 --> 00:15:20,052 S1: talked about is that, um, governments and systems of organization 229 00:15:20,052 --> 00:15:24,932 S1: and systems of government are basically their time bound based 230 00:15:24,932 --> 00:15:27,492 S1: on what is needed for the society at that time. 231 00:15:28,212 --> 00:15:32,972 S1: So it's like, it's not that we shouldn't have had, uh, 232 00:15:33,012 --> 00:15:37,172 S1: capitalism or we shouldn't have communism or whatever. It's like 233 00:15:37,812 --> 00:15:43,732 S1: those structures are like best cases. They are the things 234 00:15:43,732 --> 00:15:48,012 S1: that fit where humanity is at the time. And it's 235 00:15:48,012 --> 00:15:50,452 S1: a good way of looking at like, okay, why didn't 236 00:15:51,272 --> 00:15:56,272 S1: Iraq suddenly become a democracy as soon as we got 237 00:15:56,312 --> 00:15:59,592 S1: rid of Saddam? Well, that's not where the population is 238 00:15:59,592 --> 00:16:04,752 S1: ready for. Right. And maybe there's an argument that, like, 239 00:16:04,992 --> 00:16:08,832 S1: we are no longer, uh, up to the task of 240 00:16:08,832 --> 00:16:16,352 S1: maintaining a democracy because our population has declined so much. Cognitively, philosophically, 241 00:16:16,992 --> 00:16:22,112 S1: education wise, or I would say knowledge wise. And so 242 00:16:22,152 --> 00:16:26,472 S1: we're losing our ticket or we're losing our ability to 243 00:16:26,912 --> 00:16:31,792 S1: be worthy of democracy. That's one argument. That's one argument. 244 00:16:31,872 --> 00:16:34,872 S1: So I like this framing. I like the structure. And 245 00:16:34,872 --> 00:16:37,352 S1: so essentially what we would be saying here is that 246 00:16:37,392 --> 00:16:42,152 S1: the capitalist structure is super useful at a certain phase 247 00:16:42,152 --> 00:16:45,872 S1: of our maturity and development. And that ideally we would 248 00:16:45,912 --> 00:16:48,632 S1: move out of it and move into something more like 249 00:16:49,112 --> 00:16:52,782 S1: not like a Stalin communism, not like a mao communism. 250 00:16:52,862 --> 00:16:55,182 S1: It wouldn't even really be communism because it wouldn't be 251 00:16:55,182 --> 00:16:58,062 S1: like state control of things. It would be more like 252 00:16:58,582 --> 00:17:03,302 S1: shared human control of things and shared human voting. It 253 00:17:03,302 --> 00:17:10,822 S1: would be actual democracy instead of democracy. Republic. Of democracy 254 00:17:10,862 --> 00:17:14,582 S1: or a republic. Because we would have the tech, presumably, 255 00:17:14,582 --> 00:17:18,182 S1: to do so. And you could use other things for 256 00:17:18,182 --> 00:17:21,302 S1: the whole federal versus state or whatever. We could basically 257 00:17:21,342 --> 00:17:25,022 S1: figure out these problems. Right. And the more advanced we 258 00:17:25,022 --> 00:17:28,581 S1: are as a population, the easier that would be to do, 259 00:17:28,582 --> 00:17:31,662 S1: because you just make a good argument and people are like, oh, yeah, 260 00:17:31,662 --> 00:17:34,262 S1: it's a pretty good argument. Yeah, let's do it that way. Right. 261 00:17:34,302 --> 00:17:40,982 S1: Which we clearly don't have today. But so the point 262 00:17:40,982 --> 00:17:44,702 S1: of all of this is to say that the only 263 00:17:44,702 --> 00:17:48,882 S1: way I can function is to take all of my 264 00:17:50,282 --> 00:17:54,442 S1: concern and worry and sort of pain around. Holy crap, 265 00:17:54,442 --> 00:17:57,722 S1: this is going to get bad and use that exact 266 00:17:57,722 --> 00:18:01,482 S1: same force and that exact same energy and just be like, no, 267 00:18:01,642 --> 00:18:05,802 S1: you know what? I am not thinking that way. I 268 00:18:05,802 --> 00:18:08,362 S1: don't know that we have a chance to get out 269 00:18:08,362 --> 00:18:12,722 S1: of this clean. We might exterminate ourselves. We might go 270 00:18:12,722 --> 00:18:15,561 S1: into massive civil war. We might have, like, a huge 271 00:18:15,561 --> 00:18:19,002 S1: amount of problems. There's a million what ifs. There is 272 00:18:19,002 --> 00:18:21,202 S1: nothing I can do about it. There's nothing you could 273 00:18:21,202 --> 00:18:23,282 S1: do about it. This is a thing that is happening 274 00:18:23,321 --> 00:18:26,401 S1: to the planet right now, and it's just kind of 275 00:18:26,442 --> 00:18:30,802 S1: playing out. And it's really weird with this whole free 276 00:18:30,802 --> 00:18:33,802 S1: will thing. It's like, I know that we don't have 277 00:18:33,802 --> 00:18:38,122 S1: the free will to fix this, but guess what? There's 278 00:18:38,162 --> 00:18:41,122 S1: a guaranteed way it doesn't get fixed is to think 279 00:18:41,122 --> 00:18:43,122 S1: that you don't have the free will to fix it. 280 00:18:43,522 --> 00:18:46,421 S1: Which means I behave as if. And this is another 281 00:18:46,422 --> 00:18:49,462 S1: essay I'm working on, but you behave as if you 282 00:18:49,462 --> 00:18:55,381 S1: had the freedom, and ironically, that ends up bringing forth 283 00:18:55,622 --> 00:18:59,542 S1: a more positive thing. Now you could say, well, that 284 00:18:59,542 --> 00:19:02,821 S1: was what was going to happen anyway. Well, cool. Whatever. 285 00:19:03,222 --> 00:19:04,942 S1: I don't have time to think about that right now. 286 00:19:04,942 --> 00:19:07,782 S1: I need to think about positivity and trying to make 287 00:19:07,782 --> 00:19:11,022 S1: it happen because we are humans. Actually, the name of 288 00:19:11,022 --> 00:19:13,382 S1: this essay, and I know I'm sort of going on 289 00:19:13,382 --> 00:19:17,061 S1: a tangent here, but hopefully it's okay. The name of 290 00:19:17,061 --> 00:19:21,742 S1: this essay is Reality is Layer Dependent, which means at 291 00:19:21,742 --> 00:19:26,502 S1: my layer right now, when I am trying to fix 292 00:19:26,502 --> 00:19:30,382 S1: the world at my layer right now as a human, 293 00:19:31,302 --> 00:19:36,022 S1: free will does exist. Because if I go outside and 294 00:19:36,022 --> 00:19:38,382 S1: someone has stolen my trash cans and I see them 295 00:19:38,382 --> 00:19:41,102 S1: across the street in front of their house and they're 296 00:19:41,102 --> 00:19:46,161 S1: full of garbage. I'm going to walk across the street 297 00:19:46,162 --> 00:19:50,602 S1: and ask them to not do that again. Please. I'm 298 00:19:50,642 --> 00:19:53,561 S1: not going to say I'm not going to walk across 299 00:19:53,561 --> 00:19:55,362 S1: the street and say, hey, I just want to let 300 00:19:55,362 --> 00:19:58,642 S1: you know, I know you don't have free will. And, um, 301 00:19:59,242 --> 00:20:03,042 S1: you there was nothing you could have possibly done to 302 00:20:03,082 --> 00:20:06,482 S1: not steal my garbage cans and fill them up full 303 00:20:06,482 --> 00:20:10,722 S1: of garbage. That is not a conversation I'm going to have. 304 00:20:11,202 --> 00:20:14,242 S1: I'm going to have a conversation about them changing their behavior, 305 00:20:14,762 --> 00:20:19,282 S1: which means at this layer of of reality, which is 306 00:20:19,282 --> 00:20:24,321 S1: human interaction and the perception of free will. These are 307 00:20:24,321 --> 00:20:28,362 S1: the kinds these are the types of conversations that we have. Right. 308 00:20:29,442 --> 00:20:33,722 S1: And layers below this, it's kind of lame and stupid. Uh, 309 00:20:33,922 --> 00:20:38,842 S1: the biological layer, the chemical layer, the physical layer. You 310 00:20:38,842 --> 00:20:42,641 S1: talk to atoms about the fact that somebody stole garbage cans. 311 00:20:42,782 --> 00:20:45,742 S1: They don't understand that. You know what I mean? So. 312 00:20:48,862 --> 00:20:54,822 S1: All this coming back to. I'm trying to focus. I 313 00:20:54,862 --> 00:20:58,302 S1: recommend other people do this as well. Take all that 314 00:20:58,942 --> 00:21:03,342 S1: hurt energy, all that negativity, all that everything, and just 315 00:21:03,342 --> 00:21:07,702 S1: move it over into this positivity category because everything could 316 00:21:07,702 --> 00:21:12,341 S1: go horribly wrong. Or this could be the origin story 317 00:21:12,742 --> 00:21:16,982 S1: for a few scrappy people got together and they planned 318 00:21:17,022 --> 00:21:21,702 S1: on building a better internet. That was human based and 319 00:21:21,942 --> 00:21:28,382 S1: they just, you know, steadfastly refused to give into the suck. 320 00:21:28,382 --> 00:21:31,341 S1: And they started building the better thing. And, oh, the 321 00:21:31,342 --> 00:21:35,262 S1: idea started catching on. And when things got bad enough, 322 00:21:35,262 --> 00:21:39,381 S1: people leaned over into the positive side that that's actually 323 00:21:39,382 --> 00:21:42,762 S1: what we ended up building. and it turns out we survived. 324 00:21:42,762 --> 00:21:44,802 S1: It was way better. We got rid of the corporate 325 00:21:44,802 --> 00:21:48,442 S1: work we're now teaching in schools that everyone is a creator. 326 00:21:48,482 --> 00:21:53,282 S1: Everyone is a builder. Everyone is a entrepreneur. Everyone has 327 00:21:53,722 --> 00:21:59,122 S1: value to give to the world, right? Not the special few. 328 00:21:59,321 --> 00:22:01,962 S1: Your job is not to get out of school and 329 00:22:01,962 --> 00:22:04,482 S1: find a really cool company, because that's a really smart 330 00:22:04,482 --> 00:22:09,161 S1: person and you're going to give your little meager skills, 331 00:22:09,321 --> 00:22:14,962 S1: you know, to, to help them succeed. Screw that. This 332 00:22:14,962 --> 00:22:18,842 S1: is new world. This is we all have that capability, right? 333 00:22:19,482 --> 00:22:23,601 S1: So if we have a tiny chance of this happening, 334 00:22:24,402 --> 00:22:26,962 S1: that chance is larger if if we all try and 335 00:22:26,962 --> 00:22:31,882 S1: push towards it. So that's that's why I'm very. Sort 336 00:22:31,922 --> 00:22:36,601 S1: of sad and very excited all at the same time. Okay. 337 00:22:36,642 --> 00:22:41,122 S1: That was the first line of the newsletter. After 22 338 00:22:41,122 --> 00:22:45,022 S1: minutes in. That was literally the first line of the newsletter. Okay, 339 00:22:45,022 --> 00:22:52,542 S1: we're scrolling down. Incredibly awesome conversation with my buddy Jason 340 00:22:52,542 --> 00:22:57,062 S1: Haddox over the weekend about automated recon pen testing type 341 00:22:57,102 --> 00:22:59,982 S1: stuff that we're building together. So mine is called Helios. 342 00:23:00,022 --> 00:23:03,141 S1: I've had it for like, whatever, 15 years, I don't know, 343 00:23:03,142 --> 00:23:06,342 S1: 12 years, something like that. And before it was just 344 00:23:06,342 --> 00:23:11,101 S1: like nasty Python and bash and stuff like that. Basic 345 00:23:11,102 --> 00:23:15,141 S1: automation stuff. Linuxi type automation stuff. Using a whole bunch 346 00:23:15,142 --> 00:23:18,862 S1: of custom tools, a whole bunch of project discovery tools 347 00:23:19,462 --> 00:23:21,581 S1: and like it does the job. But now I'm basically 348 00:23:21,582 --> 00:23:25,542 S1: doing a full AI upgrade on it, and Jason's been 349 00:23:25,542 --> 00:23:29,062 S1: working on his stack as well. And so, uh, we 350 00:23:29,061 --> 00:23:32,062 S1: talked a bunch about, uh, what I'm doing currently with 351 00:23:32,061 --> 00:23:36,302 S1: my stack with Kai, and he pings me like, I 352 00:23:36,302 --> 00:23:39,892 S1: don't know, like 15 minutes later, he's like, dude, um, 353 00:23:40,492 --> 00:23:44,812 S1: my thing just found a bug. Um, a P1 bug. 354 00:23:45,372 --> 00:23:47,892 S1: And it turns out that, um, he had this password 355 00:23:47,892 --> 00:23:52,012 S1: field for a thing that he was testing, and, uh, 356 00:23:53,172 --> 00:23:55,532 S1: it was just the password field, and it was for 357 00:23:55,532 --> 00:24:01,091 S1: some sort of admin site, and he was thinking, like, 358 00:24:01,132 --> 00:24:02,691 S1: do I? Okay, what do I want to try to 359 00:24:02,692 --> 00:24:06,732 S1: brute force this thing? It doesn't look extremely vulnerable. And 360 00:24:06,732 --> 00:24:10,572 S1: his I found something that he and I would not 361 00:24:10,571 --> 00:24:13,212 S1: have thought of. Uh, right. I mean, it's somewhere in 362 00:24:13,212 --> 00:24:16,891 S1: my methodology, but it's not part of my main methodology. Um, 363 00:24:17,372 --> 00:24:19,932 S1: which is to start messing with parameters. That's fine, but 364 00:24:19,972 --> 00:24:23,692 S1: it in one shot, it's first thing that it tried 365 00:24:23,692 --> 00:24:27,811 S1: was to add a parameter to post, which was id 366 00:24:27,852 --> 00:24:32,652 S1: equals one and instantly bypassed. So an actual live real 367 00:24:32,652 --> 00:24:37,552 S1: world P1. And he said he had to mess with 368 00:24:37,552 --> 00:24:39,952 S1: it a little bit to get up to that point. 369 00:24:40,472 --> 00:24:44,512 S1: But in terms of like doing an actual exploit, a P1, 370 00:24:45,232 --> 00:24:47,792 S1: doing something that he wasn't going to do, I wouldn't 371 00:24:47,792 --> 00:24:50,631 S1: have thought of, uh, at least in that immediately. I'm 372 00:24:50,632 --> 00:24:54,192 S1: sure somewhere deep in our methodology, we have to not 373 00:24:54,192 --> 00:24:57,191 S1: only modify parameters, but also to add parameters. I mean, 374 00:24:57,192 --> 00:25:00,992 S1: that's a pretty common thing, actually, but it didn't come 375 00:25:00,992 --> 00:25:04,072 S1: to mind, right? That's the point. It was like, that 376 00:25:04,071 --> 00:25:07,872 S1: was pretty cool. It was pretty cool. So I think 377 00:25:07,872 --> 00:25:11,072 S1: the takeaway that we have there is just like, this 378 00:25:11,071 --> 00:25:13,792 S1: stuff is not theoretical. This stuff is like getting very, 379 00:25:13,792 --> 00:25:17,552 S1: very tangible. And my point about this has always been 380 00:25:17,552 --> 00:25:23,071 S1: that we just have an orchestration problem, like the individual 381 00:25:23,071 --> 00:25:26,952 S1: steps don't require all that much intelligence. It's not super 382 00:25:26,952 --> 00:25:30,512 S1: hard to do this stuff. The problem is keeping the 383 00:25:30,512 --> 00:25:33,232 S1: plot when you're doing it and you're doing like, you know, 384 00:25:33,272 --> 00:25:37,292 S1: 175 different mini tasks, and you're gathering all this context 385 00:25:37,292 --> 00:25:40,532 S1: and there's too much context, you know, falling out of 386 00:25:40,532 --> 00:25:43,252 S1: different places. So like a big part of what I'm 387 00:25:43,252 --> 00:25:47,652 S1: doing with Kai is breaking context into separate subfolders with 388 00:25:47,652 --> 00:25:52,891 S1: their separate cloud MD files and their separate large pieces 389 00:25:52,892 --> 00:25:57,052 S1: of context, so that the subagents are consuming context and 390 00:25:57,052 --> 00:25:59,852 S1: they're not polluting the main agent with that context. Right. 391 00:25:59,892 --> 00:26:03,331 S1: Because you absolutely need this when you're, you know, parsing 392 00:26:03,372 --> 00:26:06,732 S1: like complete Doms and stuff like that. Um, there's just 393 00:26:06,732 --> 00:26:09,492 S1: so much content in there. Then you have, uh, haystack 394 00:26:09,492 --> 00:26:13,212 S1: performance issues, right? You're trying to find like endpoints inside 395 00:26:13,212 --> 00:26:16,852 S1: of a giant, you know, Dom full of JavaScript. It's 396 00:26:16,892 --> 00:26:19,972 S1: like it's pretty nasty. And it takes up a lot 397 00:26:19,972 --> 00:26:24,811 S1: of tokens, and it's traditionally not great for for AI. 398 00:26:24,972 --> 00:26:27,892 S1: And the other thing to mention about this is like, no, 399 00:26:28,012 --> 00:26:30,492 S1: when you should be using AI and no when you 400 00:26:30,492 --> 00:26:34,232 S1: shouldn't be. Right. Um, I'm going to talk about this 401 00:26:34,232 --> 00:26:37,832 S1: somewhere else. But one thing that's really cool is, is 402 00:26:37,832 --> 00:26:42,871 S1: to think about the fact that, um, you should use 403 00:26:42,872 --> 00:26:45,071 S1: as little AI as possible. I talk about this a 404 00:26:45,071 --> 00:26:48,752 S1: little bit later in the newsletter, but uses little AI 405 00:26:48,792 --> 00:26:54,672 S1: as possible. Ideally, the whole workflow would be legacy traditional 406 00:26:54,712 --> 00:27:00,831 S1: deterministic tech, just regular code, right. So like addition, subtraction, 407 00:27:00,832 --> 00:27:06,072 S1: multiplication like no reason to enter AI into this. Right. 408 00:27:06,832 --> 00:27:08,512 S1: And then there are certain types of problems that do 409 00:27:08,512 --> 00:27:12,552 S1: require that that do require intelligence. So if it requires 410 00:27:12,552 --> 00:27:15,952 S1: intelligence it's the type of thing like hey is this 411 00:27:15,952 --> 00:27:19,552 S1: a cat, for example. That's not an if this, if this, 412 00:27:19,552 --> 00:27:22,472 S1: then that statement that you can give to regular code, 413 00:27:22,752 --> 00:27:25,071 S1: which is why we needed machine learning, which is why 414 00:27:25,071 --> 00:27:29,432 S1: we use AI. Right. So just knowing when to use 415 00:27:29,432 --> 00:27:34,012 S1: which is super important. Um. All right. Scroll down. Peace. 416 00:27:34,212 --> 00:27:39,252 S1: About limitations to creativity. And I realized there's actually a 417 00:27:39,252 --> 00:27:41,612 S1: third limitation. So I'm writing another blog post that kind 418 00:27:41,612 --> 00:27:45,452 S1: of unifies them all. But the third one, the third 419 00:27:45,492 --> 00:27:48,972 S1: type of limitation to creativity, is not even thinking about 420 00:27:48,972 --> 00:27:51,452 S1: some options for creating a new solution or solving a 421 00:27:51,452 --> 00:27:55,052 S1: problem because it was previously impossible. It's like being stuck 422 00:27:55,052 --> 00:27:58,212 S1: in like old world, old mind, old tech or whatever. 423 00:27:59,092 --> 00:28:04,892 S1: And I got an example from this weekend, so I 424 00:28:04,892 --> 00:28:09,652 S1: was I'm not very happy with like my, my um. 425 00:28:12,092 --> 00:28:17,131 S1: Web analytics tech. So my web analytics stack is currently fathom, 426 00:28:17,932 --> 00:28:21,332 S1: but I would much rather be using a chartbeat. But 427 00:28:21,332 --> 00:28:23,652 S1: even Chartbeat doesn't do everything. It doesn't have a menu 428 00:28:23,652 --> 00:28:29,052 S1: bar thing. Um, it also doesn't have historical metrics, right? 429 00:28:29,112 --> 00:28:31,952 S1: I can't use it like Google Analytics. So I for 430 00:28:32,112 --> 00:28:35,152 S1: like over a decade, I use Google Analytics and Chartbeat 431 00:28:35,192 --> 00:28:38,432 S1: Chartbeat to look at Google Analytics to go and get 432 00:28:38,432 --> 00:28:44,432 S1: reports from. And that's kind of lame, but I never 433 00:28:44,432 --> 00:28:46,272 S1: questioned it. I never thought it was a problem. I 434 00:28:46,272 --> 00:28:48,352 S1: was just like the way the world is, no big deal. 435 00:28:48,392 --> 00:28:53,712 S1: Like that's just reality. Well, I was messing with, uh, fathom, 436 00:28:54,032 --> 00:28:56,232 S1: which is my current replacement for both of those, because 437 00:28:56,232 --> 00:28:59,632 S1: Chartbeat is too expensive now, and Google Analytics is garbage now. 438 00:29:00,512 --> 00:29:03,192 S1: So I use fathom, and it's like it doesn't have 439 00:29:03,192 --> 00:29:08,552 S1: the Google Analytics, like, I guess like enterprise feel. Um, 440 00:29:08,552 --> 00:29:13,512 S1: it doesn't look nearly as good as Google Analytics or Chartbeat. Um, 441 00:29:13,552 --> 00:29:16,512 S1: and it kind of has like a, uh, I found 442 00:29:16,512 --> 00:29:19,352 S1: a way to give a menu bar icon, but I realized, 443 00:29:19,352 --> 00:29:22,352 S1: hold on, I actually know how Chartbeat works. It works 444 00:29:22,352 --> 00:29:24,272 S1: by having a piece of JavaScript on the page that 445 00:29:24,272 --> 00:29:28,612 S1: sends a beacon every few seconds. And that's how it 446 00:29:28,612 --> 00:29:35,012 S1: actually sends the difference between. It can tell the difference between, um, well, 447 00:29:35,172 --> 00:29:37,772 S1: its primary functionality is that it can tell you who's 448 00:29:37,772 --> 00:29:42,092 S1: reading the website. Right? Like right now there's 165 people 449 00:29:42,092 --> 00:29:45,372 S1: reading my website. And that's that's my current count. I'm 450 00:29:45,372 --> 00:29:48,852 S1: looking at my menu bar that's 165 people with a 451 00:29:48,852 --> 00:29:53,852 S1: tab open that are reading it. Right. So that that's 452 00:29:53,852 --> 00:29:56,372 S1: what I care about. I care about who's currently looking 453 00:29:56,372 --> 00:30:01,092 S1: at what pages. Right. Google analytics doesn't have this. Chartbeat 454 00:30:01,132 --> 00:30:04,132 S1: has this. It's the only one I've found that really 455 00:30:04,132 --> 00:30:07,932 S1: had this feature. And they also had a guy that 456 00:30:07,932 --> 00:30:09,932 S1: was like super pretty and it was just like a 457 00:30:09,972 --> 00:30:12,892 S1: really cool way to visualize it. And I'm like, this 458 00:30:12,892 --> 00:30:14,652 S1: is the best thing ever. So I paid for it 459 00:30:14,652 --> 00:30:18,932 S1: forever and ever and ever. And now I just suddenly 460 00:30:18,932 --> 00:30:22,052 S1: realized on Sunday while I was working on the newsletter, hey, 461 00:30:22,052 --> 00:30:25,332 S1: I wonder if I could just make chartbeat. So I'm like, hey, 462 00:30:25,332 --> 00:30:29,282 S1: I want a piece of JavaScript called analytics. I'm going 463 00:30:29,322 --> 00:30:31,602 S1: to serve it inside my page. Here's where you're going 464 00:30:31,642 --> 00:30:35,042 S1: to put it. Here's the functionality it's going to have. Um, 465 00:30:35,082 --> 00:30:37,762 S1: here's how often it's going to beacon. Set up an 466 00:30:37,762 --> 00:30:42,562 S1: endpoint on Cloudflare to receive the beacon. You're going to 467 00:30:42,562 --> 00:30:45,962 S1: parse referrers like this, blah, blah, blah, basically. And I 468 00:30:46,282 --> 00:30:48,922 S1: gave it a whole bunch of spec sort of stuff, 469 00:30:48,962 --> 00:30:53,362 S1: you know, um, basically a full spec of what I 470 00:30:53,362 --> 00:30:59,122 S1: want to build, uh, in the Google Analytics JavaScript, also 471 00:30:59,122 --> 00:31:02,442 S1: in the receiving endpoint, also in the front end showing it. 472 00:31:02,962 --> 00:31:04,842 S1: And I give it a bunch of examples and stuff 473 00:31:04,842 --> 00:31:09,162 S1: like that. And in about 18 minutes of me just 474 00:31:09,162 --> 00:31:12,282 S1: talking to it and giving it to it in that format, 475 00:31:13,602 --> 00:31:17,482 S1: it then produced the full spec and wrote the entire thing. 476 00:31:17,682 --> 00:31:21,882 S1: So within 18 minutes I literally had a chart beat replacement. 477 00:31:22,842 --> 00:31:26,262 S1: And I then spent many hours after that trying to, 478 00:31:26,302 --> 00:31:30,102 S1: you know, tweaking and adding fields and, you know, tweaking 479 00:31:30,102 --> 00:31:32,742 S1: the color scheme slightly and display and stuff like that. 480 00:31:32,742 --> 00:31:35,662 S1: So it's not like I was done after 18 minutes, 481 00:31:35,662 --> 00:31:40,382 S1: but I had live visitors showing up and showing up 482 00:31:40,382 --> 00:31:43,462 S1: on my graph, and the site looked pretty much like 483 00:31:43,462 --> 00:31:48,102 S1: Chartbeat within 18 minutes. That is ridiculous. And the whole 484 00:31:48,102 --> 00:31:51,542 S1: point of talking about this is, yeah, it's cool. So 485 00:31:51,542 --> 00:31:53,702 S1: I want to talk about it. I think it's cool. 486 00:31:53,702 --> 00:31:58,542 S1: I love, uh, live telemetry from the world is just 487 00:31:58,582 --> 00:32:01,222 S1: a thing that, like, I'm obsessed with. You have a map. 488 00:32:01,222 --> 00:32:06,342 S1: You realize that there's some human who's reading some thought, uh, and, 489 00:32:06,382 --> 00:32:09,582 S1: you know, maybe maybe you've seen this person before. Maybe 490 00:32:09,582 --> 00:32:11,982 S1: you've walked by them in a coffee shop or something. 491 00:32:12,942 --> 00:32:15,702 S1: It's just like human connection, I think is really cool. 492 00:32:17,182 --> 00:32:21,502 S1: But the thing I want to focus on here is that. 493 00:32:23,362 --> 00:32:26,602 S1: Literally the second before I had this thought, I was 494 00:32:26,602 --> 00:32:31,682 S1: caged by this concept of like, well, that's too bad. 495 00:32:31,682 --> 00:32:35,202 S1: Short beats expensive because there's no way I could make 496 00:32:35,202 --> 00:32:39,042 S1: a heartbeat. I wasn't actually even thinking there's no way 497 00:32:39,042 --> 00:32:42,682 S1: I could make a heartbeat. That was an automatic default 498 00:32:43,522 --> 00:32:47,242 S1: barrier inside my brain. I didn't even have to think 499 00:32:47,242 --> 00:32:51,482 S1: that the barrier was there. The barrier is invisible. Now, 500 00:32:51,522 --> 00:32:54,002 S1: keep in mind, I've been able to do this, this 501 00:32:54,162 --> 00:32:57,802 S1: advanced level of like building for like the last couple 502 00:32:57,842 --> 00:33:01,282 S1: of years, I've been building tons of stuff. Why did 503 00:33:01,282 --> 00:33:04,842 S1: I never think to build a better analytics system? I've 504 00:33:04,882 --> 00:33:10,282 S1: paid for Fathom Analytics. I've paid them hundreds upon hundreds 505 00:33:10,282 --> 00:33:14,482 S1: of dollars for a thing that's worse than what I 506 00:33:14,482 --> 00:33:21,142 S1: made in 18 minutes. Let that sink in, okay? 18 507 00:33:21,142 --> 00:33:25,222 S1: minutes to be way better than my Google Analytics solution 508 00:33:25,902 --> 00:33:30,582 S1: and my Chartbeat solution and my fathom solution. The limitation, 509 00:33:30,582 --> 00:33:33,181 S1: the reason I hadn't done it, is because it hadn't 510 00:33:33,182 --> 00:33:35,902 S1: popped into my mind that I was able to do it. 511 00:33:37,062 --> 00:33:42,102 S1: And what really breaks my brain is I'm still currently 512 00:33:42,102 --> 00:33:46,782 S1: limited by an infinite number of those walls and those barriers. 513 00:33:46,862 --> 00:33:52,822 S1: So in this blog this is type three creativity limitation. 514 00:33:53,582 --> 00:33:57,942 S1: And we seek. My argument is we seek or should 515 00:33:57,982 --> 00:34:02,142 S1: seek type three freedom. In fact, all three type one 516 00:34:02,142 --> 00:34:09,181 S1: freedom is freedom from internal um, not not being able 517 00:34:09,182 --> 00:34:14,662 S1: to reach our internal child like creativity. So the freedom 518 00:34:14,662 --> 00:34:17,142 S1: is to be able to and the restraint is not 519 00:34:17,142 --> 00:34:21,082 S1: being able to. And then the second one is audience capture. 520 00:34:21,282 --> 00:34:23,442 S1: So it's like you're worried about what your parents and 521 00:34:23,442 --> 00:34:26,362 S1: your friends and your your surroundings. It's not really audience. 522 00:34:26,362 --> 00:34:32,322 S1: It's more like peer or societal, uh, capture and like limitation. 523 00:34:32,562 --> 00:34:36,922 S1: So you literally stop having good thoughts because you can 524 00:34:36,922 --> 00:34:39,562 S1: only think along certain lines of what you're expected to 525 00:34:39,602 --> 00:34:44,162 S1: produce and what is acceptable to produce. So that's layer two. 526 00:34:44,162 --> 00:34:49,042 S1: And level three is thinking in the past being limited 527 00:34:49,042 --> 00:34:54,842 S1: by the past. So it's like I grew up thinking 528 00:34:54,842 --> 00:34:58,282 S1: only certain things were possible. And I can't even know 529 00:34:58,402 --> 00:35:01,002 S1: all the ways that those limitations are still on me. 530 00:35:01,522 --> 00:35:06,522 S1: I mean, I was born in the 70s, right? So phone, 531 00:35:06,722 --> 00:35:10,242 S1: cell phones, right? I mean, all these things that we 532 00:35:10,242 --> 00:35:16,042 S1: have now, how many of them? How many of them 533 00:35:16,482 --> 00:35:19,862 S1: are like limiting me in me thinking that those things 534 00:35:19,862 --> 00:35:22,622 S1: are possible. I feel like I'm way ahead of the 535 00:35:22,622 --> 00:35:27,982 S1: game against most people in the world, honestly, including extremely 536 00:35:27,982 --> 00:35:30,142 S1: young kids who grew up with tech. I feel like 537 00:35:30,142 --> 00:35:33,382 S1: I'm more unbounded than most, but I still feel very 538 00:35:33,382 --> 00:35:38,502 S1: bound by this. I feel extremely sort of caged by this. 539 00:35:38,502 --> 00:35:41,702 S1: So I'm writing this post to kind of remind myself. 540 00:35:42,222 --> 00:35:45,582 S1: Do you have all three types of these freedoms? Oh, 541 00:35:45,622 --> 00:35:47,502 S1: and by the way, the reason I got on to 542 00:35:47,502 --> 00:35:53,622 S1: this at all is from reading, uh, Rilke and Rilke's 543 00:35:53,662 --> 00:35:56,422 S1: Letters to a Young Poet, um, which is a book 544 00:35:56,422 --> 00:35:59,302 S1: that I've been recommending. And that's where I first started 545 00:35:59,302 --> 00:36:01,142 S1: thinking about this. But then I started thinking about it 546 00:36:01,142 --> 00:36:04,262 S1: from this book, Mathematica, which I just finished. And oh 547 00:36:04,302 --> 00:36:09,502 S1: my God, it is extraordinary. So anyway, um, a bunch 548 00:36:09,502 --> 00:36:12,302 S1: of that stuff is in the previous two posts about creativity, 549 00:36:12,302 --> 00:36:14,022 S1: but I'm about to do this third one that kind 550 00:36:14,022 --> 00:36:16,372 S1: of unites all of them. Oh, and by the way, 551 00:36:16,372 --> 00:36:19,012 S1: I'm going to tell Kai to once I'm done with 552 00:36:19,012 --> 00:36:22,172 S1: the third post to go and update the other two 553 00:36:22,612 --> 00:36:25,932 S1: to point to the third one. And I can also 554 00:36:25,932 --> 00:36:29,052 S1: say in the third one, hey, I wrote these previous 555 00:36:29,052 --> 00:36:31,812 S1: two posts and it's going to Kai is going to 556 00:36:31,852 --> 00:36:34,932 S1: automatically go find those two posts and link to them. 557 00:36:34,932 --> 00:36:37,972 S1: So this is an example of a thing that you know, 558 00:36:38,012 --> 00:36:41,372 S1: in the whatever 26 years that I've been blogging, I've 559 00:36:41,372 --> 00:36:45,892 S1: had to do that manually. And it's just really, really 560 00:36:45,892 --> 00:36:48,532 S1: great to think that I could just say one thing 561 00:36:48,532 --> 00:36:53,092 S1: into Whisper Flow, and all of that gets dynamically updated 562 00:36:53,652 --> 00:36:58,532 S1: by Kai. Okay. So, uh, all right, so that's the, uh, 563 00:36:58,572 --> 00:37:07,532 S1: whole chart beat creativity thing. Um, oh. Had a really cool, 564 00:37:07,532 --> 00:37:11,372 S1: interesting conversation with Matthew Brown from Trail of Bits. So 565 00:37:11,372 --> 00:37:13,732 S1: we were talking about this AI system design thing that 566 00:37:13,732 --> 00:37:16,272 S1: I was talking about earlier, and he gave me a 567 00:37:16,312 --> 00:37:19,752 S1: couple really cool, um, ways to think about this and like, 568 00:37:19,792 --> 00:37:22,952 S1: design principles that I'm going to use for my meta 569 00:37:22,952 --> 00:37:27,112 S1: system designer. Um, and one of the things he said 570 00:37:27,112 --> 00:37:32,472 S1: that was really cool is problem design, problem understanding and 571 00:37:32,472 --> 00:37:36,992 S1: problem problem categorization is what it is really. So he's 572 00:37:36,992 --> 00:37:40,912 S1: talking about problems that could be solved or problems that 573 00:37:40,912 --> 00:37:44,272 S1: are like identifying a cat in a picture. That is 574 00:37:44,272 --> 00:37:46,912 S1: a certain type of problem that code doesn't work for. 575 00:37:47,032 --> 00:37:51,152 S1: You need machine learning, right? Or you need intelligence. Which 576 00:37:51,192 --> 00:37:53,512 S1: machine learning is like a proxy for that. And then 577 00:37:53,512 --> 00:37:55,912 S1: AI is a proxy for it as well or a 578 00:37:55,912 --> 00:37:59,592 S1: type of it. So but there's other problems where you 579 00:37:59,592 --> 00:38:02,232 S1: should not be using AI at all. Now, the reason 580 00:38:02,232 --> 00:38:05,112 S1: I was talking to him is because he's, uh, he 581 00:38:05,112 --> 00:38:08,352 S1: led the team on Trail of Bits team that won 582 00:38:08,352 --> 00:38:13,132 S1: second place in the AI competition, which is a fully 583 00:38:13,132 --> 00:38:19,932 S1: automated discovery and and patching system. Agent system. It involves 584 00:38:19,932 --> 00:38:24,132 S1: multiple agents broken into multiple components. And so my main 585 00:38:24,132 --> 00:38:26,772 S1: question for him was like, are you relying on the 586 00:38:26,772 --> 00:38:29,732 S1: model the most or are you relying on the system 587 00:38:29,732 --> 00:38:31,972 S1: the most. And he ended up saying system as well. 588 00:38:31,972 --> 00:38:34,812 S1: I've thought it was system, so I was so happy 589 00:38:34,812 --> 00:38:36,932 S1: to hear I wasn't wrong about that, at least in 590 00:38:36,932 --> 00:38:41,652 S1: his opinion. And um, yeah, he just had some really 591 00:38:41,652 --> 00:38:46,012 S1: cool ideas about like how you design the agent system, um, 592 00:38:46,132 --> 00:38:48,412 S1: to constrain it and make sure you give it, like, 593 00:38:48,452 --> 00:38:52,012 S1: only specific types of context. But, um, that episode should 594 00:38:52,012 --> 00:38:55,452 S1: come out soon. Um, that's going to be on YouTube 595 00:38:55,452 --> 00:38:59,332 S1: and also in the, in the audio and the regular podcast. 596 00:39:00,332 --> 00:39:04,092 S1: And so, uh, really cool conversation. That guy is sharp. 597 00:39:04,132 --> 00:39:06,372 S1: I mean, this guy's been doing AI forever. Like, he's 598 00:39:06,372 --> 00:39:11,792 S1: probably going to get hired by Google for $74 trillion 599 00:39:11,832 --> 00:39:16,032 S1: would not surprise me. Um, a few weeks back I 600 00:39:16,032 --> 00:39:19,232 S1: posted about feeling really guilty about eating meat, and then 601 00:39:19,232 --> 00:39:22,832 S1: I saw a Dwarkesh episode where he had this, uh, 602 00:39:22,872 --> 00:39:26,752 S1: meat guy on or animals, you know, kindness guy on, 603 00:39:27,192 --> 00:39:29,112 S1: and he's like, yeah, we've got this thing called Farm 604 00:39:29,112 --> 00:39:32,392 S1: kind and it's a charity. And like, you know, even 605 00:39:32,392 --> 00:39:36,072 S1: $10 can save a lot of animals from suffering. Um, 606 00:39:36,312 --> 00:39:39,632 S1: and just just to, like, clarify why I care about this, 607 00:39:40,232 --> 00:39:44,792 S1: it really upsets me how similar we are to some animals, 608 00:39:44,952 --> 00:39:48,872 S1: especially like pigs, even chickens. I would say, like, obviously, 609 00:39:48,872 --> 00:39:50,512 S1: I don't know what's in the mind of a chicken, 610 00:39:50,872 --> 00:39:57,312 S1: but a pig looks and feels very normal to me. 611 00:39:57,352 --> 00:40:00,392 S1: It looks and feels like a a more advanced animal. 612 00:40:01,032 --> 00:40:04,392 S1: If you hear a pig squeal, especially if it's like 613 00:40:04,392 --> 00:40:08,792 S1: in pain or something like that sounds like pain to 614 00:40:09,012 --> 00:40:13,452 S1: my brain. It sounds like pain. And, um, there are 615 00:40:13,452 --> 00:40:16,732 S1: people in, uh, I think it's groups in Africa. Or 616 00:40:16,732 --> 00:40:24,092 S1: maybe it's Australia. Um, they call humans long pig. Uh, 617 00:40:24,092 --> 00:40:28,372 S1: because the flesh is similar and in flesh means muscle. 618 00:40:29,412 --> 00:40:32,532 S1: I mean, they're also pink, and a lot of humans 619 00:40:32,532 --> 00:40:36,492 S1: are pink, right? I mean, there's so many similarities here, 620 00:40:36,492 --> 00:40:40,172 S1: and I'm just like, oh, evidently we taste the same. 621 00:40:40,172 --> 00:40:42,572 S1: That was that was the point of of being called 622 00:40:42,572 --> 00:40:46,572 S1: Long Pig because, uh, these groups eat humans. They also 623 00:40:46,572 --> 00:40:49,612 S1: eat pigs, uh, I assume like wild boar or whatever. 624 00:40:49,612 --> 00:40:51,092 S1: And they're like, yeah, they kind of taste the same. 625 00:40:51,092 --> 00:40:54,812 S1: And I'm like, okay, uh, good to know. Uh, how 626 00:40:54,812 --> 00:40:59,212 S1: do I get out of here? Um, but I just like. Oh, 627 00:40:59,252 --> 00:41:01,292 S1: and then you see the pictures of, like, this farm 628 00:41:01,292 --> 00:41:06,132 S1: kind thing and just rows and rows and rows like 629 00:41:06,132 --> 00:41:08,872 S1: matrix where you see all those, you know, human eggs 630 00:41:08,872 --> 00:41:13,552 S1: or whatever, but it's rows and rows and rows of pigs. 631 00:41:13,872 --> 00:41:16,432 S1: And this is the craziest part to me. They are 632 00:41:16,432 --> 00:41:20,112 S1: laying on their sides like kind of like rotting from 633 00:41:20,152 --> 00:41:24,272 S1: like infections or whatever, like, like bed bed sores or whatever. 634 00:41:24,552 --> 00:41:28,592 S1: So they got bugs all over them rotting. These are pigs. 635 00:41:28,632 --> 00:41:32,752 S1: They want to run around like young kids, right? They 636 00:41:32,792 --> 00:41:35,312 S1: want to run around and have fun and, like, squeal 637 00:41:35,312 --> 00:41:40,152 S1: or do whatever pigs do. They live their entire life 638 00:41:40,192 --> 00:41:45,512 S1: on their side, and they can't stand up. They can't move. 639 00:41:45,552 --> 00:41:49,792 S1: They can't run around. And they just. Okay, so I 640 00:41:49,832 --> 00:41:52,312 S1: imagine a meter, this is the way I kind of 641 00:41:52,352 --> 00:41:56,672 S1: see the thing. There's a meter for planet Earth. There's 642 00:41:56,672 --> 00:42:01,192 S1: a suffering meter. And there is a like, fulfillment and 643 00:42:01,232 --> 00:42:04,512 S1: happiness meter. Right. And we can go deeper with that 644 00:42:04,552 --> 00:42:06,732 S1: of like, is it true meaning or whatever? Let's just 645 00:42:06,732 --> 00:42:10,252 S1: say fulfillment is the far right. It's like just complete 646 00:42:10,252 --> 00:42:16,212 S1: and utter, like deep contentment with life and happiness and such. Right. 647 00:42:16,252 --> 00:42:21,972 S1: And on the far left is like a an AI 648 00:42:22,012 --> 00:42:27,172 S1: designed like torture device, which embeds directly into your brain 649 00:42:27,172 --> 00:42:31,012 S1: and produces the maximum amount of suffering. Okay, so that's 650 00:42:31,012 --> 00:42:33,812 S1: the far left. And then you got the far right 651 00:42:33,812 --> 00:42:41,092 S1: is kind of the opposite. Now, having millions of animals 652 00:42:41,092 --> 00:42:44,332 S1: that cannot move and are stuck in a cage and 653 00:42:44,332 --> 00:42:50,692 S1: are just like experiencing extraordinary hardship. This is not hundreds 654 00:42:50,692 --> 00:42:54,092 S1: of animals. This is not thousands. It is hundreds of millions. 655 00:42:54,092 --> 00:42:57,452 S1: I think it's actually billions think it's billions of animals 656 00:42:58,132 --> 00:43:01,172 S1: who that we farm to eat or eat their meat 657 00:43:02,612 --> 00:43:05,602 S1: and they are producing suffering into the world. It's not 658 00:43:05,602 --> 00:43:11,602 S1: quite AI brain implanted torture, but it's too close for 659 00:43:11,602 --> 00:43:16,522 S1: my happiness. It is pretty close. Just just imagine a 660 00:43:16,522 --> 00:43:20,322 S1: conscious creature. Okay? We're not talking about a gnat or 661 00:43:20,322 --> 00:43:23,882 S1: an insect or a caterpillar who knows what their brains 662 00:43:23,882 --> 00:43:28,602 S1: look like, but I'm sure I'm not sure they're experiencing suffering. Okay. 663 00:43:28,842 --> 00:43:32,681 S1: A pig is. Maybe a chicken is as well. So 664 00:43:32,682 --> 00:43:37,202 S1: pigs and chickens? Cows? I care about this. I care 665 00:43:37,202 --> 00:43:40,242 S1: about what that meter says on planet Earth right now. Obviously, 666 00:43:40,242 --> 00:43:43,922 S1: I care more about humans, right? Because we got billions 667 00:43:43,922 --> 00:43:46,482 S1: of humans who also need help, or at least hundreds 668 00:43:46,482 --> 00:43:49,922 S1: of millions or millions who are in a suffering category 669 00:43:49,922 --> 00:43:53,042 S1: as well. And obviously that's the highest priority. But the 670 00:43:53,042 --> 00:43:57,522 S1: irony is this we could lower the meter more effectively 671 00:43:58,602 --> 00:44:01,562 S1: with these types of things. And this gets back to 672 00:44:01,602 --> 00:44:06,022 S1: the point I was making here. This this charity is 673 00:44:06,022 --> 00:44:09,422 S1: able to move that meter. I wish they had a 674 00:44:09,462 --> 00:44:11,982 S1: I wish they had a visualization for this. Should I 675 00:44:11,982 --> 00:44:16,302 S1: should make one because I'm not limited by type three restraint. 676 00:44:19,062 --> 00:44:22,182 S1: There should be a way to visualize. And they are 677 00:44:22,182 --> 00:44:24,262 S1: able to do this with metrics. They actually have a 678 00:44:24,262 --> 00:44:29,342 S1: way to say $10 will reduce. Will seems to through 679 00:44:29,342 --> 00:44:34,422 S1: the lobbying effects and through the various programs that they implement. 680 00:44:34,422 --> 00:44:37,142 S1: And they've got dozens of of programs. It's not just 681 00:44:37,142 --> 00:44:39,862 S1: one that they put in. So there's like a cage one, 682 00:44:39,862 --> 00:44:42,862 S1: there's like a cleanup one, there's like a medicine one, 683 00:44:42,862 --> 00:44:47,142 S1: there's like a requiring that they are able to go outside, um, 684 00:44:47,182 --> 00:44:51,702 S1: the size of the cages, um, cage free. Um, the 685 00:44:51,702 --> 00:44:56,142 S1: types of medication, um, the, the number of inspections that 686 00:44:56,142 --> 00:44:59,102 S1: they have to do, like, I'm, I can't remember all 687 00:44:59,102 --> 00:45:02,362 S1: of them, but there's multiple programs that focus on particular 688 00:45:02,362 --> 00:45:06,962 S1: parts of the problem. And this farm kind thing basically 689 00:45:07,202 --> 00:45:11,642 S1: can allocate money into different ones of those. And so 690 00:45:11,642 --> 00:45:15,162 S1: they're saying they're getting extreme results from a small amount 691 00:45:15,162 --> 00:45:19,522 S1: of money. So anyway, I reached out to them and um, 692 00:45:19,922 --> 00:45:22,482 S1: so they set up a thing for unsupervised learning. So 693 00:45:22,522 --> 00:45:27,402 S1: it's farm kind. I forget the URL. It's farm kind, something. Um, 694 00:45:27,482 --> 00:45:29,362 S1: but but it'll be in the show notes. It's in 695 00:45:29,362 --> 00:45:33,002 S1: the newsletter, obviously, which is the show notes. So yeah. 696 00:45:33,042 --> 00:45:37,082 S1: Go check this thing out. Click on the link. Give $1, 697 00:45:38,082 --> 00:45:42,322 S1: give $1 billion whichever one you have. And we could 698 00:45:42,362 --> 00:45:46,322 S1: actually like put a dent in this suffering meter on 699 00:45:46,322 --> 00:45:49,722 S1: planet Earth because like my suffering okay, I'm a human, 700 00:45:49,722 --> 00:45:53,802 S1: but I'm just one, one thing like is my suffering. 701 00:45:54,442 --> 00:45:57,722 S1: How much higher does that rate? Because mine is existential 702 00:45:58,082 --> 00:46:02,262 S1: versus a pigs. Who is? I mean, it probably feels 703 00:46:02,262 --> 00:46:06,502 S1: just as bad, like just because it's not existential suffering. 704 00:46:06,502 --> 00:46:09,702 S1: I think it feels just as bad. Right? And if 705 00:46:09,702 --> 00:46:12,662 S1: there's a billion of them, they damn well damn well 706 00:46:12,702 --> 00:46:18,782 S1: outrank me. So I love having a leverage via a 707 00:46:20,142 --> 00:46:23,302 S1: donation system like Farm Kind to be able to actually 708 00:46:23,302 --> 00:46:29,422 S1: do this. So, um, I recommend I ask you to 709 00:46:29,542 --> 00:46:32,342 S1: go and actually put some money into this thing. And 710 00:46:32,342 --> 00:46:34,222 S1: I love the fact that they set up a campaign 711 00:46:34,222 --> 00:46:37,222 S1: for us because, you know, a lot of people get 712 00:46:37,222 --> 00:46:40,382 S1: their newsletter, a lot of people get the podcast, uh, 713 00:46:40,382 --> 00:46:44,462 S1: plus YouTube or whatever. Um, we should, you know, be 714 00:46:44,502 --> 00:46:47,742 S1: able to help a lot of animals is, um, what 715 00:46:47,742 --> 00:46:50,502 S1: I'm thinking. And I would say, don't even think if 716 00:46:50,542 --> 00:46:53,142 S1: you don't care about animals, don't even think about animals. 717 00:46:53,902 --> 00:46:58,242 S1: You could help a lot of earth based Consciousness, experience 718 00:46:58,282 --> 00:47:04,682 S1: less suffering and reduce that that suffering. Meter down a 719 00:47:04,682 --> 00:47:08,042 S1: couple new blogs two primary limitations on creativity. Talked about 720 00:47:08,042 --> 00:47:14,242 S1: that one are 20,000 eyes thought experiment about how AI 721 00:47:14,282 --> 00:47:19,842 S1: transcends transforms us from workers building other streams into creators 722 00:47:19,842 --> 00:47:31,882 S1: with 20,000 eyes and hands building our own. Cybersecurity Expo 723 00:47:31,882 --> 00:47:36,442 S1: raised 117 million for hackers, then open sourced the whole thing. 724 00:47:36,442 --> 00:47:39,522 S1: This is the errata. This is the wrong thing. This 725 00:47:39,522 --> 00:47:44,122 S1: Strix repo is really cool. This is it's my top 726 00:47:44,122 --> 00:47:48,562 S1: story to. This is super annoying. Um, clear evidence that 727 00:47:48,562 --> 00:47:54,042 S1: I didn't use AI. Um, because this was my mistake. Um, anyway, yeah. 728 00:47:54,082 --> 00:47:57,622 S1: Strix GitHub repo is a cool thing. It's basically an 729 00:47:57,622 --> 00:48:03,222 S1: automated vuln checking system. Um, and it wasn't Expo that 730 00:48:03,222 --> 00:48:07,342 S1: did it. Expo was someone doing kind of something similar, 731 00:48:08,302 --> 00:48:12,422 S1: and they just decided to stop doing their experiment on 732 00:48:12,422 --> 00:48:15,782 S1: hacker one. So that part of the story is correct. Um, 733 00:48:16,222 --> 00:48:18,302 S1: and Expo is doing cool stuff, but they did not 734 00:48:18,302 --> 00:48:23,102 S1: release this GitHub repo. That's that's the part that's wrong. 735 00:48:24,062 --> 00:48:28,582 S1: Here's workday lost data through social engineering targeting Salesforce. So 736 00:48:28,582 --> 00:48:32,062 S1: a whole bunch of people are getting Salesforce compromised, which 737 00:48:32,062 --> 00:48:38,422 S1: is really, um, social engineering attacks targeting Salesforce data about 738 00:48:38,422 --> 00:48:42,342 S1: that company. And that's kind of the why you keep 739 00:48:42,342 --> 00:48:45,582 S1: seeing stories that are kind of the same around these lines. 740 00:48:47,182 --> 00:48:50,982 S1: And workday appears to be the most recent victim of this. 741 00:48:51,422 --> 00:48:56,562 S1: Russia hacked a Norwegian Dam and released 1.9 million gallons 742 00:48:56,562 --> 00:49:01,802 S1: of water zoom patches, a critical privilege escalation vulnerability affecting 743 00:49:01,802 --> 00:49:07,282 S1: windows users new public exploit chains for two SAP flaws 744 00:49:07,522 --> 00:49:14,882 S1: with RC agents. Um, getting zero false positives in security 745 00:49:14,882 --> 00:49:20,122 S1: testing with deterministic validation. So that deterministic validation thing is 746 00:49:20,122 --> 00:49:25,842 S1: really interesting. This is, um, this conversation, this, uh, blackhat presentation. 747 00:49:26,282 --> 00:49:28,922 S1: There's a link to Expo here. Maybe this is how 748 00:49:28,922 --> 00:49:30,882 S1: I got confused because I was reading like 20 of 749 00:49:30,882 --> 00:49:33,202 S1: these things at the same time on Sunday, and I 750 00:49:33,202 --> 00:49:40,522 S1: just like, got cross-pollinated whatever. Uh, my mistake. Um. Basically, 751 00:49:40,522 --> 00:49:42,442 S1: the idea here is similar to what I was talking 752 00:49:42,442 --> 00:49:45,522 S1: about before and what Matthew Brown was talking about, which 753 00:49:45,522 --> 00:49:50,282 S1: is deterministic. That's code. Right. Um, and then you have 754 00:49:50,282 --> 00:49:53,192 S1: AI and like don't make don't confuse the two. You 755 00:49:53,192 --> 00:49:56,632 S1: can mix the two, but don't confuse the two. And 756 00:49:56,832 --> 00:50:01,312 S1: they're basically saying like, here's a general thing. You don't 757 00:50:01,312 --> 00:50:04,472 S1: want to ask it, hey, is this vulnerable? Because they 758 00:50:04,472 --> 00:50:06,392 S1: want to please you. They'll be like, yeah, it looks 759 00:50:06,392 --> 00:50:12,632 S1: vulnerable to me. So many false positives. So it's better 760 00:50:12,632 --> 00:50:15,992 S1: to use like a deterministic system to check if something 761 00:50:15,992 --> 00:50:20,312 S1: is vulnerable, if you can't. And then use the AI 762 00:50:20,352 --> 00:50:25,272 S1: for different parts of the system that require intelligence, critical 763 00:50:25,272 --> 00:50:29,312 S1: vulnerabilities and flow wise, AI platform 9.8 on the Richter 764 00:50:29,312 --> 00:50:32,552 S1: scale is going to happen. It's going to keep happening 765 00:50:32,552 --> 00:50:36,112 S1: because more and more systems are being built. So the 766 00:50:36,112 --> 00:50:39,432 S1: attack surface by its very nature is growing, therefore going 767 00:50:39,432 --> 00:50:42,552 S1: to be more vulnerable. Um, and then you have the 768 00:50:42,552 --> 00:50:45,152 S1: fact that AI is building so much of that code. 769 00:50:45,632 --> 00:50:49,472 S1: I'm not actually sure. Now I think about it. I'm 770 00:50:49,512 --> 00:50:55,132 S1: not actually sure if we add a 100 no. 2 771 00:50:55,132 --> 00:51:00,172 S1: million new websites to the internet that are suddenly built 772 00:51:00,172 --> 00:51:04,212 S1: by humans or suddenly built by AI. Which one is worse? 773 00:51:05,652 --> 00:51:08,172 S1: I guess it comes down to the question of what 774 00:51:08,172 --> 00:51:11,772 S1: made it be sudden. Why is there so all of 775 00:51:11,772 --> 00:51:14,732 S1: a sudden, so many 2 million more people making websites? 776 00:51:14,852 --> 00:51:18,292 S1: And who are those people? That's the question. Um, but 777 00:51:18,292 --> 00:51:23,052 S1: right now, I mean, humans aren't good at making secure code. 778 00:51:23,772 --> 00:51:28,492 S1: Really good humans are really good secure coding. Writing humans are, 779 00:51:28,532 --> 00:51:31,532 S1: but most aren't. Which is why Stack Overflow is full 780 00:51:31,532 --> 00:51:34,412 S1: of garbage. Which is why I trained on it. And 781 00:51:34,412 --> 00:51:39,412 S1: it's also making garbage. But AI is making lots of 782 00:51:39,412 --> 00:51:42,892 S1: slop on the internet, and it's shipping code very fast. 783 00:51:43,412 --> 00:51:48,872 S1: So it's bad. Um, now, over time, I think that's 784 00:51:48,872 --> 00:51:50,912 S1: going to get better and better. But in the meantime, 785 00:51:50,912 --> 00:51:53,392 S1: the slop will have already been made. And then you'll 786 00:51:53,392 --> 00:51:57,272 S1: need something like the AI automation bots to go clean 787 00:51:57,272 --> 00:52:01,592 S1: it all up. Chinese hackers breached Taiwan web servers using 788 00:52:01,592 --> 00:52:06,072 S1: customized open source tools. This is a Cisco Talos. Fine. 789 00:52:06,392 --> 00:52:10,392 S1: Lars shows us how missing MFA turn valid logins into 790 00:52:10,392 --> 00:52:17,712 S1: full compromise. Russia hackers breached US federal courts through vulnerabilities discovered. 791 00:52:18,152 --> 00:52:24,432 S1: But they were not fixed in 2020. So getting compromised 792 00:52:24,432 --> 00:52:27,272 S1: by something that you should have or you were told 793 00:52:27,272 --> 00:52:31,752 S1: about but didn't fix. Cisa releases new guidance telling companies 794 00:52:31,752 --> 00:52:36,232 S1: to inventory their OT systems. What do you know? Asset management. 795 00:52:36,272 --> 00:52:39,112 S1: This is going to be one of the biggest, coolest 796 00:52:39,112 --> 00:52:42,272 S1: things ever. Oh, by the way, I want to um, 797 00:52:42,312 --> 00:52:44,272 S1: I just thought of another idea which I didn't put 798 00:52:44,272 --> 00:52:48,212 S1: in the newsletter. Here's a cool idea and related to 799 00:52:48,252 --> 00:52:53,252 S1: my USC concept of unified entity context for enterprises. And 800 00:52:53,252 --> 00:52:56,612 S1: I got this idea, um, well, it's in the USC 801 00:52:56,612 --> 00:53:01,252 S1: idea as well, but I got this very specific idea 802 00:53:01,252 --> 00:53:07,972 S1: from a prince who's part of, um, Project Discovery. And 803 00:53:08,652 --> 00:53:12,172 S1: the idea is you send your agents out and their 804 00:53:12,172 --> 00:53:16,412 S1: job is to be like, they just sit inside of software. 805 00:53:16,412 --> 00:53:19,692 S1: They just sit in different places. They sit inside of wikis, 806 00:53:20,052 --> 00:53:23,892 S1: they sit inside of like organizations. They sit inside of software. 807 00:53:23,892 --> 00:53:28,772 S1: They sit inside of GitHub repos. And I forget how 808 00:53:28,772 --> 00:53:32,692 S1: he was talking about it. Um, but he basically said 809 00:53:32,932 --> 00:53:36,612 S1: distribute agents and have them do things and report back. 810 00:53:36,892 --> 00:53:43,212 S1: And so mine, my mind started jumping towards the USC idea. Um, 811 00:53:43,572 --> 00:53:47,072 S1: but I also jumped to the idea of security champions. 812 00:53:47,112 --> 00:53:48,792 S1: You know how like a lot of security teams, they'll 813 00:53:48,792 --> 00:53:52,232 S1: send their people out, like into the field, which is like, oh, 814 00:53:52,272 --> 00:53:55,192 S1: you live with engineering now? Oh, you live with product now. 815 00:53:55,192 --> 00:53:59,032 S1: You live with sales now or whatever. And their job 816 00:53:59,032 --> 00:54:02,672 S1: is to like sort of like understand report back but 817 00:54:02,672 --> 00:54:07,832 S1: also subtly influence them. Well, what if you didn't have 818 00:54:07,832 --> 00:54:10,912 S1: three of those people for the entire company, but instead 819 00:54:10,912 --> 00:54:14,792 S1: you had 3 million of them? Just imagine that every 820 00:54:14,792 --> 00:54:21,912 S1: piece of software, every piece of tech like your AWS accounts, your, um, 821 00:54:22,592 --> 00:54:27,872 S1: all your infrastructure, everything has agents inside of them watching 822 00:54:27,872 --> 00:54:31,472 S1: and reporting back. And some, of course, would be able 823 00:54:31,472 --> 00:54:35,112 S1: to make changes that'll come later. Um, and if you're 824 00:54:35,112 --> 00:54:38,232 S1: freaking out, that's because you work in security. Um, because 825 00:54:38,232 --> 00:54:40,872 S1: I'm freaking out. Just saying the words. So you have 826 00:54:40,872 --> 00:54:44,652 S1: millions of these agents out there They're gathering, reporting back, 827 00:54:44,652 --> 00:54:48,452 S1: blah blah blah. Who's controlling these agents? What identity do 828 00:54:48,452 --> 00:54:52,812 S1: they have? How are we logging their information? Like auditors 829 00:54:52,812 --> 00:54:55,892 S1: are going to freak out about this, but I think 830 00:54:55,892 --> 00:54:59,732 S1: this is absolutely the way that USC happens. Or one 831 00:54:59,732 --> 00:55:02,052 S1: of the ways that USC happens. There's different ways to 832 00:55:02,052 --> 00:55:05,372 S1: do this. You could have centralized agents that go, just 833 00:55:05,372 --> 00:55:08,252 S1: go and hit the stuff live and pull the stuff back. 834 00:55:08,732 --> 00:55:12,092 S1: But I think it's better to just deploy agents into 835 00:55:12,092 --> 00:55:16,972 S1: the systems themselves and have them point back to the center. Right? 836 00:55:17,012 --> 00:55:20,012 S1: Because I feel like we well, it's probably going to 837 00:55:20,012 --> 00:55:22,652 S1: be both. It's kind of like asset management, which is 838 00:55:22,652 --> 00:55:25,572 S1: how I got in the point. If you have the 839 00:55:25,572 --> 00:55:29,132 S1: agents inside of all of these systems and they're reporting back, 840 00:55:29,132 --> 00:55:33,052 S1: guess what they're doing? They are updating and breaking out 841 00:55:33,052 --> 00:55:37,852 S1: sub contexts, which then get summarized by other agents to 842 00:55:37,892 --> 00:55:42,202 S1: report up into a higher context, which which is the UFC, 843 00:55:42,762 --> 00:55:48,882 S1: and that UFC ultimately becomes this conglomeration of all these 844 00:55:48,882 --> 00:55:52,042 S1: mini contexts that got updated from all the air systems 845 00:55:52,042 --> 00:55:55,402 S1: and the project management system and the budget system and 846 00:55:55,402 --> 00:56:00,362 S1: all of those, like somebody buys, you know, a toothpaste 847 00:56:00,402 --> 00:56:04,522 S1: while they're traveling overseas on a work trip, being they 848 00:56:04,522 --> 00:56:09,402 S1: paid for the toothpaste. Okay, that hit some system somewhere. 849 00:56:10,362 --> 00:56:13,682 S1: Well guess what? In this world, which, by the way, 850 00:56:13,682 --> 00:56:15,162 S1: this is going to take a very long time to 851 00:56:15,202 --> 00:56:19,402 S1: roll out. So we're talking between two and, you know, 852 00:56:19,602 --> 00:56:23,482 S1: 15 years, right. I'm sure someone's already doing it a 853 00:56:23,482 --> 00:56:25,842 S1: little bit, but it's going to take a very long 854 00:56:25,842 --> 00:56:30,802 S1: time to move through all of enterprise it in that world. 855 00:56:31,242 --> 00:56:36,002 S1: Whenever whoever gets it, that agent lives inside of the 856 00:56:36,002 --> 00:56:39,002 S1: finance system and the accounting system, and it sees the 857 00:56:39,002 --> 00:56:42,622 S1: toothpaste hit, and it reports up a tiny little entry 858 00:56:42,622 --> 00:56:46,382 S1: into a subcontext, which goes into another subcontext, which goes 859 00:56:46,382 --> 00:56:49,742 S1: all the way up. And ultimately, that probably wouldn't be 860 00:56:49,742 --> 00:56:51,982 S1: part of a big strategic picture, but at least it 861 00:56:51,982 --> 00:56:56,502 S1: would increment values, right? Um, and maybe it didn't need 862 00:56:56,502 --> 00:56:59,862 S1: to report that because that's part of traditional tech, which 863 00:56:59,942 --> 00:57:03,102 S1: gets valued later, but maybe they weren't supposed to be 864 00:57:03,102 --> 00:57:07,582 S1: traveling and that that, uh, purchase of toothpaste means they're 865 00:57:07,622 --> 00:57:09,782 S1: not where they're supposed to be. And now we have 866 00:57:09,782 --> 00:57:13,102 S1: a traveling problem and the VPN connection is turned off. 867 00:57:13,142 --> 00:57:18,102 S1: Whatever it is, the point is, all these different agents 868 00:57:18,542 --> 00:57:22,462 S1: in the different systems can be updating the central picture 869 00:57:22,462 --> 00:57:25,902 S1: of not just USC. But guess what you get for 870 00:57:25,902 --> 00:57:28,622 S1: free when you have USC, if it's reporting on the 871 00:57:28,622 --> 00:57:33,662 S1: proper stuff. Asset management we've never been able to do 872 00:57:33,702 --> 00:57:40,082 S1: asset management. Never. It's it's hard Like I consult for 873 00:57:40,282 --> 00:57:42,882 S1: Jupiter one because I love their vision of doing this 874 00:57:42,882 --> 00:57:47,522 S1: with a graph. It is really, really hard. It is 875 00:57:47,522 --> 00:57:50,442 S1: really hard. Um, I did this for Robin Hood. I 876 00:57:50,442 --> 00:57:55,042 S1: did asset management for Robin Hood using, um, a product 877 00:57:55,042 --> 00:58:00,762 S1: like this. Right. And I'm telling you, this is like, 878 00:58:01,722 --> 00:58:08,642 S1: it's completely like shifting, like game shifting stuff to have 879 00:58:08,682 --> 00:58:12,082 S1: actual real time understanding of the systems. Right? That's what 880 00:58:12,082 --> 00:58:14,922 S1: it comes down to. Asset management is an old word. 881 00:58:14,962 --> 00:58:20,162 S1: Let's let's not use that anymore. Um, you know, uh, 882 00:58:20,922 --> 00:58:24,482 S1: real time information gathering or whatever, like, there's old words 883 00:58:24,482 --> 00:58:26,842 S1: to use, and they're kind of dead in our minds. 884 00:58:27,402 --> 00:58:30,402 S1: Here's just another way to think about it. Millions of 885 00:58:30,402 --> 00:58:34,922 S1: agents deployed across your entire organization inside of all the 886 00:58:34,922 --> 00:58:38,302 S1: different tech stacks. Stocks. That is very hard for a 887 00:58:38,302 --> 00:58:42,262 S1: centralized entity to go and audit. And by the time 888 00:58:42,262 --> 00:58:45,982 S1: you do go and audit it, it's too it's too late. 889 00:58:45,982 --> 00:58:50,862 S1: That information is rolled off like there's a million examples 890 00:58:50,862 --> 00:58:53,182 S1: of this. And if you're in it or security or whatever, 891 00:58:53,182 --> 00:58:59,382 S1: you already know this, right. So planning, finance, tracking what 892 00:58:59,422 --> 00:59:01,622 S1: you know people are doing and if they're happy or 893 00:59:01,622 --> 00:59:04,462 S1: unhappy and how we can how can we make them happier. 894 00:59:04,502 --> 00:59:09,222 S1: How can we keep people from quitting? Um, customer churn. 895 00:59:09,262 --> 00:59:14,022 S1: That's a great one. Customer management. I mean, think about that. 896 00:59:14,422 --> 00:59:17,102 S1: Look at all the different things that we know the 897 00:59:17,102 --> 00:59:20,142 S1: customer is doing, and which one of those could be 898 00:59:20,142 --> 00:59:24,342 S1: signals that they're getting ready to churn? And what can 899 00:59:24,342 --> 00:59:31,062 S1: we do as a, as a result, like a reactionary action? Um, 900 00:59:31,062 --> 00:59:34,782 S1: so they haven't come to the portal recently. Okay, cool. 901 00:59:35,042 --> 00:59:39,082 S1: They start. Um, I don't know. They start blogging about 902 00:59:39,082 --> 00:59:45,202 S1: how the competitor looks better and their team at their current, uh, offering. Doesn't, uh, 903 00:59:45,202 --> 00:59:47,762 S1: ever reach out to them? Well, that's a great one. 904 00:59:48,322 --> 00:59:53,962 S1: Are there any agents right now watching customers public blog posts, 905 00:59:55,282 --> 00:59:58,282 S1: trying to figure out if they're unhappy with the product, 906 00:59:58,442 --> 01:00:01,962 S1: or they're getting excited about another product and then sending 907 01:00:01,962 --> 01:00:05,242 S1: them a preemptive email that says, hey, haven't seen you 908 01:00:05,242 --> 01:00:09,762 S1: log in recently. Hey, here's a $5 discount code or whatever. No, 909 01:00:09,802 --> 01:00:12,322 S1: I don't think so. And if there are, there's very few. 910 01:00:12,642 --> 01:00:18,202 S1: This will become commonplace. The point here, and I'm just 911 01:00:18,202 --> 01:00:21,562 S1: saying the point over and over. So, um, I'm saying 912 01:00:21,562 --> 01:00:24,402 S1: in different ways, hopefully it's sinking in. It might have 913 01:00:24,402 --> 01:00:28,442 S1: sunk in like, uh, 38 minutes ago. If so, I apologize. 914 01:00:29,242 --> 01:00:36,582 S1: Real time updating at the edges inward, as opposed to 915 01:00:37,062 --> 01:00:40,422 S1: being the central person who is responsible for all these things, 916 01:00:40,422 --> 01:00:43,222 S1: and all the systems are opaque. You have to reach 917 01:00:43,222 --> 01:00:45,102 S1: out to that owner. You have to get a user 918 01:00:45,102 --> 01:00:49,422 S1: and a login like it doesn't work. It hasn't worked. 919 01:00:49,462 --> 01:00:53,342 S1: That's why asset management has been so difficult. Um, and 920 01:00:53,342 --> 01:00:57,502 S1: that takes us all the way back to the point 921 01:00:57,502 --> 01:01:01,582 S1: I was making with Sisa releasing new guidance, telling companies 922 01:01:01,582 --> 01:01:05,142 S1: to inventory their OT systems. It's hard to inventory your 923 01:01:05,182 --> 01:01:10,302 S1: OT system, right? It's also hard to install agents on 924 01:01:10,302 --> 01:01:14,342 S1: OT systems because they don't want to install anything and 925 01:01:14,382 --> 01:01:18,382 S1: haven't wanted to for decades. So this will be a 926 01:01:18,382 --> 01:01:23,022 S1: slow process. Um. National security UK police are getting ten 927 01:01:23,022 --> 01:01:28,102 S1: facial recognition vans to catch serious criminals. And they're saying 928 01:01:28,102 --> 01:01:31,682 S1: like sex offenders, people wanted for serious crimes. So they're 929 01:01:31,682 --> 01:01:35,362 S1: looking for, like, outstanding warrants. But you know what? It's 930 01:01:35,362 --> 01:01:39,562 S1: still the van with cameras. And, uh, it all depends 931 01:01:39,562 --> 01:01:42,122 S1: on the government you have on how those tools will 932 01:01:42,122 --> 01:01:45,202 S1: be used. Will it be the best thing ever for humanity? Yeah, maybe. 933 01:01:46,042 --> 01:01:51,602 S1: Depends who's using the tool. America's gray zone blind spot 934 01:01:51,602 --> 01:01:56,322 S1: is becoming serious national security problem. So, uh, someone at 935 01:01:56,322 --> 01:02:00,562 S1: the cipher Brief is basically saying that, like, Russia, China, 936 01:02:00,602 --> 01:02:06,242 S1: Iran are ramping up, sabotage, cyber attacks, other hybrid warfare attacks. 937 01:02:06,242 --> 01:02:09,882 S1: And basically the US is not good at these things. Now, 938 01:02:09,882 --> 01:02:14,522 S1: what I would hope is we actually are understanding these. 939 01:02:14,522 --> 01:02:18,722 S1: We're preparing to do them, uh, not not in a 940 01:02:18,722 --> 01:02:22,362 S1: terrorist way, but like we're we understand and we're learning 941 01:02:22,362 --> 01:02:25,482 S1: how to defend against them. And we could potentially use 942 01:02:25,482 --> 01:02:29,442 S1: some of these tactics ourselves. Um, but that we just 943 01:02:29,442 --> 01:02:32,352 S1: don't talk about it. I think that's more likely to 944 01:02:32,712 --> 01:02:35,792 S1: be the case, and I hope it's the case. US 945 01:02:35,792 --> 01:02:40,232 S1: military transforms Indiana training grounds into drone warfare innovation hub. 946 01:02:40,552 --> 01:02:43,672 S1: Happy to see this. We are behind on drones, especially 947 01:02:43,712 --> 01:02:47,552 S1: as it relates to China. Russia blocks signal and WhatsApp 948 01:02:47,872 --> 01:02:55,272 S1: to control communication. US Navy wants 150 unmanned ships by 2027. Yes, please. 949 01:02:56,232 --> 01:03:00,472 S1: Our ships. I remember in the early 90s, I was 950 01:03:00,472 --> 01:03:04,672 S1: in the army. I was studying assassin's mace weapons, and 951 01:03:04,672 --> 01:03:08,272 S1: there was some general talking about how our fleets are 952 01:03:08,272 --> 01:03:11,792 S1: going to be extremely vulnerable to assassin's mace weapons by 953 01:03:11,952 --> 01:03:18,112 S1: specifically China, where they could deploy something. And our giant 954 01:03:18,592 --> 01:03:24,072 S1: like projection of power through aircraft carriers and carrier fleets 955 01:03:24,352 --> 01:03:27,152 S1: could just be taken out in a matter of minutes 956 01:03:27,152 --> 01:03:32,332 S1: or hours. using one of these types of weapons, or 957 01:03:32,452 --> 01:03:35,372 S1: multiple of these types of weapons, that costs very little 958 01:03:35,412 --> 01:03:38,292 S1: to make. And it turns out the number one assassin's 959 01:03:38,292 --> 01:03:41,332 S1: mace weapon. That has started to happen. I don't remember 960 01:03:41,332 --> 01:03:43,052 S1: if he was talking about it back then, because I 961 01:03:43,052 --> 01:03:45,972 S1: just wasn't smart back then, and I just can't remember 962 01:03:45,972 --> 01:03:53,412 S1: that far back. But, um, it is drones. Absolutely. It's drones. 963 01:03:54,892 --> 01:03:58,412 S1: And I will mention kill Decision by Daniel Suarez. Go 964 01:03:58,412 --> 01:04:03,612 S1: read that Israel says Iran recruited dozens of Israeli citizens, 965 01:04:04,292 --> 01:04:08,972 S1: highlighting concern with like, yeah, it's pretty easy for foreign 966 01:04:08,972 --> 01:04:12,492 S1: Intel services to like recruit citizens. I mean, if you 967 01:04:12,492 --> 01:04:16,012 S1: have enough, if you have thousands or millions of citizens, 968 01:04:16,292 --> 01:04:19,172 S1: it's just a matter of like finding, you know, it's 969 01:04:19,172 --> 01:04:21,932 S1: a filter system to find the right ones. And it's 970 01:04:21,972 --> 01:04:27,672 S1: unfortunately pretty easy. China detained second senior diplomat in expanding probe. 971 01:04:27,872 --> 01:04:30,912 S1: So they're arresting a bunch of diplomats. Not exactly clear 972 01:04:30,912 --> 01:04:33,872 S1: what they're doing wrong. I'm guessing it might be like 973 01:04:33,912 --> 01:04:39,712 S1: not being pro-China enough. Maybe they're becoming too Western. No idea, 974 01:04:39,712 --> 01:04:46,432 S1: but I'm curious about that. I Anthropic's also Anthropic's CEO, 975 01:04:46,432 --> 01:04:49,512 S1: says I will write 90% of code in 3 to 976 01:04:49,512 --> 01:04:53,672 S1: 6 months. He said stuff like this before, and to 977 01:04:53,712 --> 01:04:55,992 S1: be clear, he's not saying there won't be people writing 978 01:04:55,992 --> 01:05:00,112 S1: code like only 10% of people now will be writing code. 979 01:05:00,832 --> 01:05:03,712 S1: He's saying that just there will be so much more 980 01:05:03,752 --> 01:05:09,912 S1: AI code that it'll be 90% of the total. OpenAI 981 01:05:09,912 --> 01:05:12,872 S1: is building chromium based web browser with AI agents that 982 01:05:12,872 --> 01:05:16,432 S1: can browse for you. My buddy Jason is like, yeah, 983 01:05:16,432 --> 01:05:21,632 S1: the next big thing is, uh, AI for AI is 984 01:05:21,632 --> 01:05:25,492 S1: basically browsers. And I think he's turning out to be correct. Like, 985 01:05:25,492 --> 01:05:28,172 S1: I keep waiting for the next step, which is the Da, 986 01:05:28,572 --> 01:05:31,132 S1: which is what I'm building. And I think that's kind 987 01:05:31,132 --> 01:05:33,172 S1: of the final step there is to have your Da 988 01:05:33,172 --> 01:05:35,532 S1: do all this for you. And a browser would just 989 01:05:35,532 --> 01:05:38,772 S1: be a tool, but it sounds like he's correct in 990 01:05:38,772 --> 01:05:41,212 S1: that this is going to be the home for a 991 01:05:41,252 --> 01:05:44,892 S1: while because we all use our browsers. We don't have 992 01:05:44,932 --> 01:05:48,652 S1: DA's yet. Da platforms aren't there yet with like Apple 993 01:05:48,652 --> 01:05:53,492 S1: and Google or OpenAI with like a separate device. So 994 01:05:53,492 --> 01:05:58,972 S1: that ecosystem like hasn't started happening yet. Um, but browsers have. 995 01:05:59,172 --> 01:06:01,692 S1: So I think he's turning out to be very correct 996 01:06:01,692 --> 01:06:04,412 S1: about this. And now OpenAI is getting in the game. 997 01:06:05,092 --> 01:06:08,772 S1: Sam Altman says we're in an AI bubble. I agree 998 01:06:08,772 --> 01:06:10,892 S1: with this. I just think it's not the kind of 999 01:06:10,932 --> 01:06:15,092 S1: bubble that people think it is, because it's not like 1000 01:06:15,132 --> 01:06:18,172 S1: AI is going away or it's going to crash. So 1001 01:06:18,172 --> 01:06:24,392 S1: when I think bubble, I think NFTs or, um, Pets.com. 1002 01:06:26,112 --> 01:06:30,792 S1: Because largely those things don't exist anymore. And it was 1003 01:06:30,832 --> 01:06:33,312 S1: it turned out to be kind of a scam. Now, 1004 01:06:33,432 --> 01:06:37,232 S1: I'm not an expert on, uh, the.com bubble because I 1005 01:06:37,272 --> 01:06:43,592 S1: kind of wasn't sentient at the time, but, um. My 1006 01:06:43,592 --> 01:06:46,032 S1: understanding was a lot of hype around, like, if you 1007 01:06:46,032 --> 01:06:49,552 S1: just have like a.com, blah, blah, blah, like you're just 1008 01:06:49,552 --> 01:06:52,032 S1: going to make tons of money. And the NFT thing 1009 01:06:52,032 --> 01:06:53,952 S1: is like, yeah, you're going to have this, you're going 1010 01:06:53,992 --> 01:06:58,072 S1: to buy it for $18.14, and you're going to be 1011 01:06:58,072 --> 01:07:00,272 S1: a millionaire if you hold on to it for a 1012 01:07:00,272 --> 01:07:04,032 S1: year and a half. Those are bubbles to me. Okay. 1013 01:07:04,312 --> 01:07:06,872 S1: The AI thing, to me, it's the most important tech 1014 01:07:06,872 --> 01:07:11,632 S1: ever invented, bar none. No questions asked. Bigger than internet. 1015 01:07:11,992 --> 01:07:16,272 S1: Bigger than mobile. Bigger than steam engine. It's the simply 1016 01:07:16,312 --> 01:07:22,092 S1: the biggest tech ever. Okay. That is not a bubble 1017 01:07:22,092 --> 01:07:28,052 S1: at all. What's a bubble about? I is thousands of 1018 01:07:28,052 --> 01:07:32,652 S1: people putting hundreds of billions of dollars. I think we 1019 01:07:32,652 --> 01:07:36,612 S1: can call it trillions of dollars now. Like invested and, 1020 01:07:36,652 --> 01:07:39,772 S1: you know, earmarked or whatever. Like, let's just call it 1021 01:07:39,812 --> 01:07:45,492 S1: hundreds of billions of dollars into new startups, new websites, 1022 01:07:45,532 --> 01:07:48,372 S1: new whatever. And everyone's jumping in there like, oh, yeah, 1023 01:07:48,412 --> 01:07:52,252 S1: you know, I do a slightly different prompt and, um, 1024 01:07:52,612 --> 01:07:54,532 S1: I've got this cool website and I'm going to raise 1025 01:07:54,532 --> 01:07:56,572 S1: a whole bunch of money and I'm going to hire 1026 01:07:56,572 --> 01:08:00,412 S1: some people, and I have a startup and it's like, no, 1027 01:08:00,412 --> 01:08:06,052 S1: not really. Not when OpenAI and anthropic make a slight 1028 01:08:06,052 --> 01:08:10,412 S1: change to their their code base, which just eliminates your 1029 01:08:10,412 --> 01:08:15,132 S1: company and 40,000 other companies just like it. It's a 1030 01:08:15,132 --> 01:08:19,052 S1: bubble because people are unsure of what it is and 1031 01:08:19,052 --> 01:08:25,041 S1: they're getting in in unsafe ways and haphazard ways and 1032 01:08:25,042 --> 01:08:28,042 S1: kind of stupid ways in a lot of cases. A 1033 01:08:28,082 --> 01:08:31,881 S1: lot of people aren't, obviously. But there is going to 1034 01:08:31,881 --> 01:08:36,082 S1: be a major correction because there is so much money invested. 1035 01:08:36,202 --> 01:08:39,962 S1: The investors don't understand AI. They're starting to a little 1036 01:08:40,002 --> 01:08:44,002 S1: bit now, but they've been investing hundreds of billions of 1037 01:08:44,002 --> 01:08:47,322 S1: dollars for like the last year or two years. I 1038 01:08:47,322 --> 01:08:51,041 S1: don't know how far back all that money was sent 1039 01:08:51,042 --> 01:08:56,282 S1: in on FOMO. It was sent in on hype. Okay, 1040 01:08:56,322 --> 01:08:58,602 S1: so this is this is the distinction. This is why 1041 01:08:58,642 --> 01:09:03,602 S1: people need to think about this super clearly. Both things 1042 01:09:03,602 --> 01:09:07,442 S1: are true at the same time. AI hype that's going 1043 01:09:07,442 --> 01:09:11,682 S1: to die down because people got in in very stupid ways. 1044 01:09:12,922 --> 01:09:14,882 S1: People are going to call that a bubble. Look what 1045 01:09:14,882 --> 01:09:19,462 S1: happened to AI. It turns out to be garbage. Very 1046 01:09:19,462 --> 01:09:25,262 S1: huge mistake. Like massive mistake. That is not a bubble. 1047 01:09:25,262 --> 01:09:29,342 S1: That is stupidity about a thing that is not understood 1048 01:09:29,902 --> 01:09:34,662 S1: and basically incautious and ignorant action taken as a result. 1049 01:09:34,902 --> 01:09:38,982 S1: And absolutely that's going to crush. Honestly, I think it's 1050 01:09:38,982 --> 01:09:42,782 S1: going to crush the majority of companies, the vast majority 1051 01:09:42,782 --> 01:09:49,182 S1: of these small little companies. Um, how about Google? How 1052 01:09:49,182 --> 01:09:53,142 S1: about meta? Are they going to have an AI hype 1053 01:09:53,142 --> 01:09:58,022 S1: and crash cycle? Uh, no, they are not. Because what 1054 01:09:58,022 --> 01:10:01,262 S1: people are doing inside of those companies is they're looking 1055 01:10:01,262 --> 01:10:05,342 S1: at all their existing processes. Another good example. Bank of America. 1056 01:10:05,462 --> 01:10:07,982 S1: Are they going to have an AI hype cycle? No 1057 01:10:07,982 --> 01:10:11,502 S1: they're not. They already know how everything works inside their company, 1058 01:10:11,742 --> 01:10:16,961 S1: and they are carefully figuring out how to apply AI 1059 01:10:17,002 --> 01:10:21,282 S1: to those existing processes. They're going to save tons of money. 1060 01:10:21,282 --> 01:10:24,442 S1: They're going to do things way better. And looking back 1061 01:10:24,482 --> 01:10:26,322 S1: ten years, they're going to be like, yeah, we wish 1062 01:10:26,322 --> 01:10:28,442 S1: we had this earlier. Like we would have saved tons 1063 01:10:28,442 --> 01:10:30,881 S1: of money. Unfortunately, they'll probably get rid of people as 1064 01:10:30,882 --> 01:10:33,961 S1: a result as well, which is a whole separate talk show. But. 1065 01:10:37,042 --> 01:10:40,602 S1: For people who are doing AI correctly and will do 1066 01:10:40,642 --> 01:10:45,922 S1: AI correctly in the future, it is laughable. Laughable to 1067 01:10:45,962 --> 01:10:50,961 S1: think of AI as a bubble or as hype. Okay, 1068 01:10:51,642 --> 01:10:55,482 S1: for all the NFT like crypto, like people who just 1069 01:10:55,482 --> 01:10:59,322 S1: thought I was a way to make money. It's absolutely 1070 01:10:59,322 --> 01:11:03,882 S1: a bubble. 100%. And they are going to get crushed. 1071 01:11:04,242 --> 01:11:07,682 S1: So just keep both of those ideas in your mind 1072 01:11:07,722 --> 01:11:11,522 S1: at the same time. Whenever you hear AI bubble AI hype. 1073 01:11:13,642 --> 01:11:17,862 S1: All right OpenAI updates GPT five to be warmer and friendlier. 1074 01:11:17,902 --> 01:11:20,702 S1: A lot of people really hated it. They hated the personality. 1075 01:11:20,942 --> 01:11:23,541 S1: I mean, there were I think there were suicides over 1076 01:11:23,582 --> 01:11:27,582 S1: using GPT four. Oh, he had to return GPT four 1077 01:11:27,782 --> 01:11:31,222 S1: back because everyone loved it so much after they complained 1078 01:11:31,222 --> 01:11:35,822 S1: about it constantly. Uh, should be noted. Slop squatting is 1079 01:11:35,822 --> 01:11:40,542 S1: when attackers register fake packages that llms hallucinate. I should 1080 01:11:40,582 --> 01:11:43,742 S1: have put this in the cybersecurity section. Yeah, this is 1081 01:11:43,742 --> 01:11:46,262 S1: really funny. So you make up a whole bunch of 1082 01:11:46,262 --> 01:11:54,222 S1: AI slop names, and then later on when I slop generates, uh, packages, 1083 01:11:54,262 --> 01:11:58,262 S1: names that are real people start using them. They will 1084 01:11:58,302 --> 01:12:02,102 S1: own the real estate. So they basically just like man 1085 01:12:02,102 --> 01:12:05,422 S1: in the middle, your, uh, your stupid AI named library 1086 01:12:07,302 --> 01:12:10,702 S1: shadow AI is like having rogue interns secretly running parts 1087 01:12:10,702 --> 01:12:14,242 S1: of your business. Yeah, especially given what I just talked about, 1088 01:12:14,242 --> 01:12:18,322 S1: about millions of agents deployed. You imagine an auditor coming 1089 01:12:18,322 --> 01:12:20,802 S1: into a place and they're just like, yeah, I just 1090 01:12:20,802 --> 01:12:23,642 S1: need to see, you know, who has access to change things. 1091 01:12:24,682 --> 01:12:27,362 S1: And it's like, yeah, we've got, you know, so and 1092 01:12:27,362 --> 01:12:32,022 S1: so AI platform it um, it's running on average 2 1093 01:12:32,022 --> 01:12:35,602 S1: million active agents, but they're, they're swapping in and out 1094 01:12:35,602 --> 01:12:39,672 S1: all the time with like a variance of like 2 1095 01:12:39,672 --> 01:12:44,322 S1: to 400,000 agents active at any one time. And it's like, okay, cool. 1096 01:12:44,362 --> 01:12:46,282 S1: Can you print me out a spreadsheet? I just want 1097 01:12:46,322 --> 01:12:49,602 S1: to review those line by line. Like that's going to 1098 01:12:49,602 --> 01:12:54,002 S1: be a nightmare. An absolute nightmare. Of course they'll be 1099 01:12:54,002 --> 01:12:59,442 S1: using AI to do that, but whatever. It is weird 1100 01:12:59,442 --> 01:13:04,242 S1: to think about millions of things deployed that have agency. Um, 1101 01:13:04,242 --> 01:13:06,762 S1: and they could see things and they could report things. 1102 01:13:07,082 --> 01:13:12,102 S1: I mean, think about central AI system compromise in this world. 1103 01:13:13,142 --> 01:13:16,142 S1: I mean, are you kidding me? I mean, a single 1104 01:13:16,142 --> 01:13:19,342 S1: kill command. Because ideally, you're supposed to be able to 1105 01:13:19,342 --> 01:13:21,742 S1: talk to all these agents, right? You obviously need to 1106 01:13:21,742 --> 01:13:23,902 S1: be able to give them commands. You need to be 1107 01:13:23,902 --> 01:13:26,342 S1: able to update their instructions. What if you could just 1108 01:13:26,342 --> 01:13:28,822 S1: tell them, wipe everything? What if you could tell them 1109 01:13:28,982 --> 01:13:33,342 S1: inject this tiny little like cuckoo's egg, steal half of 1110 01:13:33,342 --> 01:13:36,541 S1: a cent or whatever and send it to this Bitcoin account? Like, 1111 01:13:37,222 --> 01:13:40,982 S1: I mean, this is just wild world we're about to 1112 01:13:40,982 --> 01:13:45,222 S1: move into. Now, ideally you'd really, really defend this thing, 1113 01:13:45,222 --> 01:13:48,421 S1: but oh my goodness. You know mistakes will be made. 1114 01:13:49,822 --> 01:13:55,381 S1: DeFi startup replaces 45,000 in content staff with 23 agent 1115 01:13:55,462 --> 01:14:01,381 S1: AI systems for $23 per month. No. $20 per month 1116 01:14:01,782 --> 01:14:05,782 S1: 23 agent AI systems. This is a type of thing 1117 01:14:05,782 --> 01:14:08,742 S1: I'm hearing about this all over the place. They're like, yeah, 1118 01:14:08,782 --> 01:14:11,602 S1: I was spending, you know, 400 grand on this thing. 1119 01:14:11,882 --> 01:14:17,522 S1: Now I'm spending $284 and getting better results. Oh, best 1120 01:14:17,522 --> 01:14:22,242 S1: example of this is like, big giant reports. Big giant. 1121 01:14:22,642 --> 01:14:27,002 S1: So two names that I'm super like, I just think 1122 01:14:27,002 --> 01:14:31,882 S1: they're about to get destroyed. Gartner and McKinsey. And like 1123 01:14:31,882 --> 01:14:35,682 S1: everyone who's like Gartner and McKinsey. So the more expensive 1124 01:14:35,842 --> 01:14:41,522 S1: it is for, the nicer the looking report it is there, 1125 01:14:41,562 --> 01:14:46,122 S1: the more the most screwed. Like there is expertise inside McKinsey. 1126 01:14:46,122 --> 01:14:50,522 S1: There is expertise inside Gartner. But they're going to have 1127 01:14:50,522 --> 01:14:56,562 S1: to become like influencers. They're not influencers, but like content creators, 1128 01:14:56,602 --> 01:14:58,322 S1: like basically what I'm doing, they're going to have to 1129 01:14:58,322 --> 01:15:02,562 S1: go independent essentially, and have their own broadcast of their 1130 01:15:02,562 --> 01:15:07,162 S1: talent and their skill and their expertise, because it's going 1131 01:15:07,162 --> 01:15:12,112 S1: to be hard to differentiate because most, I would say 1132 01:15:12,112 --> 01:15:16,672 S1: most high quality reports like that. First of all, they 1133 01:15:16,672 --> 01:15:19,672 S1: show up with the coolest people like me who've been 1134 01:15:19,672 --> 01:15:22,712 S1: in the industry for 30 years, and I go do 1135 01:15:22,712 --> 01:15:26,112 S1: the sales call and dazzle them, and then I leave. 1136 01:15:27,232 --> 01:15:31,232 S1: And then, you know, 14, you know, smiling 22 year 1137 01:15:31,232 --> 01:15:35,232 S1: olds show up who just basically learned what a command 1138 01:15:35,232 --> 01:15:38,272 S1: line is and basically learned what security is. And those 1139 01:15:38,272 --> 01:15:41,112 S1: are going to be the consultants writing your report. And 1140 01:15:41,112 --> 01:15:44,432 S1: really they're using the expertise from all the previous reports. 1141 01:15:45,392 --> 01:15:49,672 S1: And like how does that match. Oh, and by the way, 1142 01:15:49,672 --> 01:15:53,592 S1: it's going to be $180,000 for this report, which takes 1143 01:15:53,592 --> 01:15:59,112 S1: nine weeks to make. Okay. And it's a giant opaque thing. 1144 01:15:59,152 --> 01:16:01,792 S1: It takes time to parse it and everything or whatever, 1145 01:16:02,312 --> 01:16:06,372 S1: as opposed to all the same context that those smiling 1146 01:16:06,412 --> 01:16:09,732 S1: 22 year olds had to get from you by all 1147 01:16:09,732 --> 01:16:12,171 S1: the interviews, you could just give that to your eye. 1148 01:16:12,572 --> 01:16:15,932 S1: Your eye is actually way smarter than the collective knowledge 1149 01:16:15,932 --> 01:16:19,612 S1: of all of McKinsey. And so you make that same 1150 01:16:19,612 --> 01:16:28,372 S1: report in four minutes for $1.17, or let's just say 1151 01:16:28,372 --> 01:16:31,052 S1: it's actually way more expensive. We're actually going to spend 1152 01:16:31,052 --> 01:16:34,012 S1: way more time. We're going to use the most expensive 1153 01:16:34,012 --> 01:16:43,852 S1: AI ever invented, you know, you know, uh, Claude Coad fucking, uh, seven, right? 1154 01:16:44,252 --> 01:16:49,012 S1: So it's actually $14. It's the most expensive prompt ever 1155 01:16:49,012 --> 01:16:54,052 S1: run in the history of mankind. It's a $14 report, 1156 01:16:55,212 --> 01:17:01,532 S1: and it took, uh, nine minutes to make compared to 1157 01:17:01,572 --> 01:17:04,172 S1: whatever the cost was of the other one. That took 1158 01:17:04,312 --> 01:17:12,032 S1: nine weeks. These companies are in dire, dire trouble. Technology. 1159 01:17:12,032 --> 01:17:15,592 S1: Robin hood CEO says remote work was a mistake. Orders 1160 01:17:15,592 --> 01:17:23,872 S1: executives back five days a week. Yeah, honestly, I think 1161 01:17:23,872 --> 01:17:28,512 S1: on site work is better. I really do. I love 1162 01:17:28,512 --> 01:17:33,912 S1: working remotely. I think certain people are as good or 1163 01:17:33,912 --> 01:17:38,631 S1: better working remotely, but the vibe of a team is 1164 01:17:38,672 --> 01:17:44,272 S1: a hundred times better on premise. I've seen it multiple times, 1165 01:17:44,272 --> 01:17:51,112 S1: and I've seen CEOs learn this the hard way multiple times. 1166 01:17:51,152 --> 01:17:53,832 S1: And I know lots of people who've done both and 1167 01:17:53,832 --> 01:17:57,712 S1: tried both. And this is my current wisdom level, is 1168 01:17:57,712 --> 01:18:05,332 S1: that in general, on site work is better. So cool. Uh, 1169 01:18:05,332 --> 01:18:09,532 S1: what I do like about the announcement was for executives, 1170 01:18:09,532 --> 01:18:14,332 S1: it's mandatory five days on site. For managers, it's four 1171 01:18:14,332 --> 01:18:17,732 S1: days on site, and for regular workers, it's three days 1172 01:18:17,732 --> 01:18:25,612 S1: on site. And his his quote here is, um. Your 1173 01:18:25,612 --> 01:18:31,251 S1: boss should be feeling more pain than you. I love that. 1174 01:18:31,772 --> 01:18:34,652 S1: I hate the fact that it's pain. Uh, which is 1175 01:18:34,652 --> 01:18:37,052 S1: why I think we need to move to human 3.0. 1176 01:18:37,092 --> 01:18:40,452 S1: Because this is ridiculous. We should all be working remote 1177 01:18:41,172 --> 01:18:45,172 S1: and doing, like, live meetups to work on our mutual projects. 1178 01:18:45,852 --> 01:18:50,052 S1: And if we have companies together or whatever. But this 1179 01:18:50,052 --> 01:18:53,331 S1: whole thing of you must come in. Uh, I just 1180 01:18:53,812 --> 01:18:57,252 S1: I think it's very old world. Uh, unfortunately, it seems 1181 01:18:57,252 --> 01:19:01,432 S1: to be more effective in the current model. China mandates 1182 01:19:01,432 --> 01:19:05,792 S1: domestic firms source 50% of chips from Chinese producers should 1183 01:19:05,792 --> 01:19:10,152 S1: have put that in Natsec. Text only websites are faster, cleaner, 1184 01:19:10,152 --> 01:19:15,432 S1: more accessible than modern web bloat. I love text only websites. 1185 01:19:15,432 --> 01:19:19,952 S1: I have very few images on mine. Researchers create micro 1186 01:19:19,992 --> 01:19:26,232 S1: microfliers that levitate using only sunlight. I need many of these, um, 1187 01:19:26,392 --> 01:19:28,592 S1: although I want to give them lots of capabilities. Which 1188 01:19:28,592 --> 01:19:32,392 S1: means they'll be too heavy, which means they won't float. Um, 1189 01:19:32,992 --> 01:19:34,711 S1: but this is a project I want to work on 1190 01:19:34,712 --> 01:19:40,072 S1: humans more. Most Americans think AI will permanently eliminate jobs. 1191 01:19:41,312 --> 01:19:47,552 S1: This is from Reuters Ipsos. Multiple studies show transfers to 1192 01:19:47,592 --> 01:19:51,032 S1: poor Americans basically don't help. This is like UBI studies. 1193 01:19:51,072 --> 01:19:54,871 S1: Looks like UBI studies are not looking good. The hope, 1194 01:19:55,232 --> 01:19:59,072 S1: including my hope, was that you give them this money 1195 01:19:59,252 --> 01:20:01,612 S1: and they're just going to focus on growing themselves and 1196 01:20:01,612 --> 01:20:04,492 S1: like learning and blah, blah, blah. The more I think 1197 01:20:04,492 --> 01:20:07,092 S1: about this, the more I kind of always knew this 1198 01:20:07,092 --> 01:20:10,612 S1: would not happen. Most people simply don't want to learn. 1199 01:20:10,652 --> 01:20:13,612 S1: Most people do not want to improve themselves. Most people 1200 01:20:13,612 --> 01:20:19,052 S1: are not like, curious and ambitious and like they're looking 1201 01:20:19,052 --> 01:20:22,732 S1: for their next Netflix show. The vast majority of people 1202 01:20:22,732 --> 01:20:25,852 S1: I would say, I don't know the numbers, but I 1203 01:20:25,852 --> 01:20:28,092 S1: think this is a thing that can be helped. I 1204 01:20:28,092 --> 01:20:30,492 S1: think this could be an education thing. I think some 1205 01:20:30,492 --> 01:20:32,612 S1: of this could be trauma, it could be bad education, 1206 01:20:32,612 --> 01:20:36,251 S1: it could be bad training, it could be bad culture. 1207 01:20:36,292 --> 01:20:38,812 S1: It could be lots of different things that make this happen. 1208 01:20:39,972 --> 01:20:46,452 S1: But for example, um, most libraries like, don't have people 1209 01:20:46,452 --> 01:20:50,532 S1: like knocking down the doors. It's free. Those are free books. 1210 01:20:50,532 --> 01:20:56,052 S1: Nobody's reading them. Okay. Okay. Free books. Nobody's reading them. Okay. 1211 01:20:56,132 --> 01:21:00,512 S1: The internet is full of free books. Nobody. Nobody's reading them. 1212 01:21:00,552 --> 01:21:02,792 S1: If you ask the average person, like what books are 1213 01:21:02,792 --> 01:21:08,632 S1: you reading? They're like, are you stupid? Like, I graduated 1214 01:21:08,792 --> 01:21:12,192 S1: high school a long time ago. I barely read those books. 1215 01:21:12,592 --> 01:21:15,592 S1: Why would you make me read a book? Now, some 1216 01:21:15,592 --> 01:21:17,752 S1: people read a lot of romance books, a lot of, like, 1217 01:21:17,752 --> 01:21:20,872 S1: comics or whatever I'm talking about, like. And I would 1218 01:21:20,872 --> 01:21:25,272 S1: say that's already just brilliant and amazing, just that by itself. 1219 01:21:25,672 --> 01:21:30,992 S1: But I'm talking about actually, like mostly non-fiction or really, 1220 01:21:30,992 --> 01:21:35,552 S1: really good fiction, difficult books, books that grow us. That's 1221 01:21:35,552 --> 01:21:39,032 S1: what I'm talking about. Very few people like, I'm in 1222 01:21:39,072 --> 01:21:42,912 S1: the San Francisco Bay area, okay. And most people here 1223 01:21:42,952 --> 01:21:48,472 S1: aren't reading. Most people I know in San Francisco Bay area, 1224 01:21:48,512 --> 01:21:51,671 S1: I don't want to make like, broad statistical things. Um, 1225 01:21:51,672 --> 01:21:56,381 S1: because I think, you know, first of all, that's impossible. But, Um, 1226 01:21:56,502 --> 01:21:58,342 S1: and I think a lot of the stats are wrong. 1227 01:21:58,342 --> 01:22:00,462 S1: I think when you report, how many books do you 1228 01:22:00,462 --> 01:22:02,742 S1: read a year? I bet you most of those stats 1229 01:22:02,742 --> 01:22:05,462 S1: are complete garbage. Who wants to say I haven't read 1230 01:22:05,462 --> 01:22:09,062 S1: a book since high school? Not very many people. My 1231 01:22:09,062 --> 01:22:14,902 S1: point is, I know lots of very smart people who 1232 01:22:14,942 --> 01:22:20,942 S1: make decent money, and I know all their friends as well. 1233 01:22:21,382 --> 01:22:24,262 S1: And I mean, I know hundreds or thousands of people. 1234 01:22:24,262 --> 01:22:28,022 S1: So this is my anecdotal data set. Most people don't 1235 01:22:28,022 --> 01:22:35,982 S1: read books, right. So. I don't know why I went 1236 01:22:35,982 --> 01:22:39,142 S1: so heavy into the book thing, but my point is, 1237 01:22:39,142 --> 01:22:43,182 S1: in general, most people don't care about self-improvement. They're not 1238 01:22:43,182 --> 01:22:47,302 S1: obsessed with it. Um, so when UBI money comes in, 1239 01:22:47,822 --> 01:22:51,942 S1: they're not thinking, wow, I can learn a new career. Wow. 1240 01:22:51,982 --> 01:22:54,642 S1: I could, I could buy even more books with this 1241 01:22:55,442 --> 01:23:01,202 S1: so long way of saying. I think this is why 1242 01:23:01,202 --> 01:23:04,802 S1: we're seeing the results from these UBI studies. Like, they'll 1243 01:23:04,802 --> 01:23:08,402 S1: just eat out more. They'll just, you know, improve their 1244 01:23:08,402 --> 01:23:11,522 S1: lives in other ways. They'll, you know, buy more subscriptions, 1245 01:23:11,522 --> 01:23:14,882 S1: buy clothes. And what's wrong with that? There's nothing wrong 1246 01:23:14,882 --> 01:23:18,322 S1: with that. I'm just saying, like, we should stop, like 1247 01:23:18,362 --> 01:23:23,202 S1: deluding ourselves that everyone is trying to be in this 1248 01:23:23,202 --> 01:23:27,122 S1: category that they think they are. All right. Europe faces 1249 01:23:27,122 --> 01:23:32,722 S1: an emergency as American markets completely dominate global investing. China's 1250 01:23:32,722 --> 01:23:37,242 S1: economy slowed in July despite exports staying strong. I'm about 1251 01:23:37,242 --> 01:23:43,042 S1: to do a major substrate project here to gather economic data. 1252 01:23:43,162 --> 01:23:46,122 S1: A whole bunch of data, actually. But economic data. I 1253 01:23:46,122 --> 01:23:51,562 S1: want to know where we're getting these numbers from because 1254 01:23:51,762 --> 01:23:54,382 S1: we know China's numbers are bad. Like, what are we 1255 01:23:54,422 --> 01:23:56,542 S1: judging this based on? And I want to kind of 1256 01:23:56,582 --> 01:24:00,461 S1: establish some ground truth there or at least triangulate onto it. 1257 01:24:01,542 --> 01:24:05,382 S1: Nobody's buying homes or switching jobs as American mobility stalls. 1258 01:24:05,582 --> 01:24:09,582 S1: Americans are drinking less alcohol than they have in 90 years. 1259 01:24:09,622 --> 01:24:14,302 S1: This is from a Gallup poll. Williams syndrome makes people 1260 01:24:14,302 --> 01:24:18,182 S1: hyper social and trusting of everyone. It's basically the opposite of. 1261 01:24:21,742 --> 01:24:27,661 S1: Being autistic. I almost said autistic. It's way different. UK 1262 01:24:27,702 --> 01:24:32,302 S1: drought group tells citizens to delete emails to save water. 1263 01:24:35,502 --> 01:24:39,262 S1: That's why the UK cannot have nice things. They're telling me. 1264 01:24:41,382 --> 01:24:45,342 S1: It's not the UK, it's some drought group. Okay, it's 1265 01:24:45,422 --> 01:24:49,342 S1: a country didn't do this, but whatever. It rhymes with 1266 01:24:49,342 --> 01:24:51,082 S1: a lot of things that the UK is trying to 1267 01:24:51,082 --> 01:24:56,682 S1: do to stop progress. The story behind Timothy Leary's turn on, 1268 01:24:56,722 --> 01:24:58,562 S1: tune in, drop out. You got to go check this 1269 01:24:58,562 --> 01:25:02,001 S1: thing out. Tune in. No. Turn on, tune in, drop out. 1270 01:25:02,282 --> 01:25:06,042 S1: Definitely something to check out. Ideas. Happy about this section? 1271 01:25:06,562 --> 01:25:08,482 S1: I feel like I is going to have a profound 1272 01:25:08,482 --> 01:25:12,602 S1: impact on globalism, especially for knowledge work. So the first 1273 01:25:12,602 --> 01:25:15,242 S1: jobs to go away are like the Fiverr jobs, the 1274 01:25:15,282 --> 01:25:22,282 S1: Upwork jobs, um, a lot of creative work, a lot 1275 01:25:22,282 --> 01:25:25,722 S1: of build me a basic website. And that's the first 1276 01:25:25,722 --> 01:25:29,882 S1: stuff to go with I and I'm really worried about 1277 01:25:30,162 --> 01:25:34,762 S1: millions of people because, like, we're always so us focused. 1278 01:25:34,882 --> 01:25:37,322 S1: Obviously I live in the US. I'm very US focused, 1279 01:25:37,882 --> 01:25:39,961 S1: but it's like, what about the rest of the world? 1280 01:25:40,682 --> 01:25:44,562 S1: What about all these really smart, ambitious knowledge workers who 1281 01:25:44,562 --> 01:25:50,662 S1: learned how to make websites and they're getting crazy income 1282 01:25:50,662 --> 01:25:54,501 S1: and helping their families and helping their local economies from 1283 01:25:54,502 --> 01:25:57,942 S1: all over the world. You know, Vietnam, Poland, like all 1284 01:25:57,942 --> 01:26:04,381 S1: over the place. And now suddenly that faucet gets turned 1285 01:26:04,382 --> 01:26:09,541 S1: off because smaller groups of people can use more AI 1286 01:26:09,542 --> 01:26:14,822 S1: and take more of that work. One of the primary 1287 01:26:14,822 --> 01:26:18,381 S1: directives of building AI systems should be to use as 1288 01:26:18,382 --> 01:26:21,502 S1: little AI as possible. Cool. Talked about that one. Thought 1289 01:26:21,502 --> 01:26:24,462 S1: I forgot it. It's in there. It's number two. If 1290 01:26:24,462 --> 01:26:27,342 S1: most people aren't confused about what I'm writing and sharing, 1291 01:26:27,342 --> 01:26:31,102 S1: that means I'm not properly exercising my type one freedom 1292 01:26:31,222 --> 01:26:35,262 S1: or my type two freedom. Actually, now that I think 1293 01:26:35,262 --> 01:26:39,142 S1: about it. But yeah, this is a whole thing and 1294 01:26:39,142 --> 01:26:41,862 S1: this is already a 17 hour podcast. So I'm going 1295 01:26:41,862 --> 01:26:43,622 S1: to I'm going to pass on this one for now. 1296 01:26:43,742 --> 01:26:48,962 S1: But basically if you are speaking from your true authentic self. 1297 01:26:49,162 --> 01:26:51,962 S1: You should be surprising yourself and you should be surprising 1298 01:26:51,962 --> 01:26:55,482 S1: everyone around you. If you only say things that people 1299 01:26:55,522 --> 01:26:59,921 S1: are like, yeah, that's that's perfectly correct. And they're not like, hmm, 1300 01:27:00,282 --> 01:27:03,402 S1: that guy's a little bit weird. Like, yeah, what? Why 1301 01:27:03,442 --> 01:27:05,522 S1: is he talking about that? That's kind of weird. Like, 1302 01:27:05,682 --> 01:27:09,682 S1: it doesn't match any of his other content. Um, so 1303 01:27:09,682 --> 01:27:11,562 S1: this is why I like Tyler Cowan. This is why 1304 01:27:11,562 --> 01:27:18,602 S1: I like Dwarkesh is they just explore things. Okay? And, like, 1305 01:27:18,602 --> 01:27:22,842 S1: I don't think Dwarkesh is sitting around wondering, like, oh, gee, 1306 01:27:22,842 --> 01:27:24,682 S1: I can't put out this video because no one will 1307 01:27:24,682 --> 01:27:27,842 S1: like it because I'm supposed to talk about AI. He 1308 01:27:27,842 --> 01:27:31,442 S1: literally just goes on rants about China and he just 1309 01:27:31,442 --> 01:27:35,802 S1: did the animal one. He's literally just chasing his his, uh, 1310 01:27:35,962 --> 01:27:38,882 S1: his interest. Right? And that's I feel like that's what 1311 01:27:38,882 --> 01:27:41,762 S1: I do as well. It's massively hurt me. It's massively 1312 01:27:41,762 --> 01:27:44,642 S1: hurt my socials because I'll talk about whatever and they'll 1313 01:27:44,642 --> 01:27:47,222 S1: be like, don't talk about politics. Don't beat up on Trump. 1314 01:27:47,222 --> 01:27:52,102 S1: He's a great guy. And it blunts my stuff there. 1315 01:27:52,102 --> 01:27:55,102 S1: But I think it's just a better way to live, 1316 01:27:55,142 --> 01:27:59,222 S1: to not be restricted in this way. Number four, a 1317 01:27:59,222 --> 01:28:02,342 S1: lot of what comes out in your words and your 1318 01:28:02,342 --> 01:28:05,102 S1: writing comes not from your thoughts or what you wanted 1319 01:28:05,102 --> 01:28:08,022 S1: to say, but from your current emotional state. So the 1320 01:28:08,022 --> 01:28:10,582 S1: way I think about this is there's a thing you 1321 01:28:10,582 --> 01:28:13,822 S1: think you're saying, like, for example, in this whole podcast, 1322 01:28:14,102 --> 01:28:18,062 S1: there's a think thing that I think I'm saying, right? 1323 01:28:18,102 --> 01:28:22,622 S1: I think I'm sounding smart. I think I'm sharing information 1324 01:28:22,622 --> 01:28:26,902 S1: with people. I think I'm like being helpful. I think 1325 01:28:26,902 --> 01:28:31,541 S1: I'm being excited. But people might be hearing something else. 1326 01:28:31,542 --> 01:28:33,942 S1: They might be hearing, oh, this guy's actually trying to 1327 01:28:33,942 --> 01:28:37,822 S1: promote his products. Like, let's say I was actually trying 1328 01:28:37,822 --> 01:28:40,142 S1: to promote a product, which I'm not right now, but 1329 01:28:40,182 --> 01:28:45,251 S1: maybe I will be in the next podcast. Who knows? Um, 1330 01:28:45,372 --> 01:28:48,052 S1: let's say I was actually trying to promote a product, 1331 01:28:48,052 --> 01:28:51,172 S1: but I was trying to talk in a way in 1332 01:28:51,172 --> 01:28:54,131 S1: which it seemed like I wasn't. I was like, oh, yeah, well, 1333 01:28:54,172 --> 01:28:58,492 S1: you know, everyone all use threshold, for example. I'll be like, yeah, 1334 01:28:58,532 --> 01:29:00,572 S1: everyone has a problem. You know, I just think it's 1335 01:29:00,572 --> 01:29:03,932 S1: really weird. People, you know, can't find whatever, they can't 1336 01:29:03,932 --> 01:29:07,251 S1: find the right stories and like, they're not rated high enough. And, 1337 01:29:07,492 --> 01:29:11,291 S1: you know, there's there's, uh, small creators around the world 1338 01:29:11,292 --> 01:29:14,812 S1: and they can't get their stuff found or whatever. And 1339 01:29:14,852 --> 01:29:19,812 S1: the receiver is like, I feel a pitch coming. And 1340 01:29:19,852 --> 01:29:23,252 S1: in my mind, I don't think I'm sending that, but 1341 01:29:23,252 --> 01:29:26,452 S1: they can receive it. So I'm obsessed with this idea of, like, 1342 01:29:27,012 --> 01:29:32,452 S1: receivers can hear things beyond the senses. They have an, 1343 01:29:32,852 --> 01:29:37,212 S1: you know, an extra sensory way to sense truth in 1344 01:29:37,212 --> 01:29:41,052 S1: what's being sent. So it's almost like what I'm sending 1345 01:29:41,052 --> 01:29:45,992 S1: is beyond words and meaning, and what they're receiving is 1346 01:29:45,992 --> 01:29:48,912 S1: beyond words and meaning. So the words I'm saying and 1347 01:29:48,912 --> 01:29:52,272 S1: the words they're hearing are at that surface level, but 1348 01:29:52,272 --> 01:29:55,432 S1: what they're actually understanding, what I'm actually sending is different 1349 01:29:55,432 --> 01:29:58,752 S1: than what I think. And the only thing that I 1350 01:29:58,752 --> 01:30:03,672 S1: can interpret it is, is a receiver. And they're going 1351 01:30:03,672 --> 01:30:05,992 S1: to receive it emotionally, and I'm going to send it 1352 01:30:05,992 --> 01:30:10,192 S1: emotionally at another layer than my words. So I'm like 1353 01:30:10,232 --> 01:30:12,872 S1: obsessed with this. I'm like, that's how I could read 1354 01:30:12,872 --> 01:30:15,872 S1: a whole bunch of tweets, including from my own, and 1355 01:30:15,872 --> 01:30:20,352 S1: just be like, um, well, I'll just use someone else, 1356 01:30:20,352 --> 01:30:22,992 S1: for example. They're like, oh, blah blah, I'm such a 1357 01:30:23,032 --> 01:30:25,232 S1: hero and blah blah blah. And I did this and 1358 01:30:25,232 --> 01:30:29,112 S1: I didn't even want any appreciation from it at all. And, 1359 01:30:29,152 --> 01:30:30,952 S1: you know, I just put a lot of effort in 1360 01:30:30,952 --> 01:30:34,472 S1: and blah, blah, blah. And the thing that they're trying 1361 01:30:34,472 --> 01:30:44,052 S1: to send with their words is. Um, well, they're trying 1362 01:30:44,052 --> 01:30:48,372 S1: to create the impression that they're just a selfless person, 1363 01:30:48,652 --> 01:30:51,212 S1: and they just do it for the community or whatever. 1364 01:30:52,332 --> 01:30:57,372 S1: But what a tuned receiver hears is I'm a giant narcissist, 1365 01:30:57,372 --> 01:30:59,492 S1: and I want everyone to love me and think I'm 1366 01:30:59,492 --> 01:31:04,612 S1: the best person ever. And I am obsessed with the 1367 01:31:04,612 --> 01:31:08,732 S1: difference between those signals and how the second one is 1368 01:31:08,732 --> 01:31:13,812 S1: often invisible in the text that they said, but also 1369 01:31:14,292 --> 01:31:16,812 S1: to the to the sender, to the person who said it. 1370 01:31:16,812 --> 01:31:18,612 S1: They're like, what are you talking about? I'm just like, 1371 01:31:18,692 --> 01:31:21,332 S1: just sharing some of the things I've done. Like I 1372 01:31:21,372 --> 01:31:25,572 S1: donated blood nine times yesterday. Like I'm just sharing that information. 1373 01:31:25,572 --> 01:31:27,852 S1: I'm not trying to say that I'm a hero. Now, 1374 01:31:27,852 --> 01:31:30,372 S1: if you want to call me a hero, you, you're 1375 01:31:30,372 --> 01:31:34,852 S1: free to do so. Um, anyway, that's kind of the 1376 01:31:34,852 --> 01:31:38,532 S1: point there. All right. Discovery I apps are becoming like 1377 01:31:38,672 --> 01:31:47,992 S1: music personal, contextual and infinite. Really cool little idea. So 1378 01:31:47,992 --> 01:31:53,392 S1: it's not like there's not like the music. Everyone has 1379 01:31:53,392 --> 01:31:57,032 S1: their own world of music. Isn't that cool? That's a 1380 01:31:57,032 --> 01:32:01,832 S1: cool idea. Claudia is a desktop companion for cloud code. 1381 01:32:01,872 --> 01:32:07,272 S1: Haven't messed with this command line person, as everyone knows. Uh, which, 1382 01:32:07,272 --> 01:32:09,312 S1: by the way, I was trying to convey there that 1383 01:32:09,312 --> 01:32:11,992 S1: I'm awesome. Even though I just said I'm a command 1384 01:32:11,992 --> 01:32:15,272 S1: line person, I was actually trying to convey that I'm awesome. 1385 01:32:15,272 --> 01:32:18,272 S1: And you should be awesome too. And use the command 1386 01:32:18,272 --> 01:32:22,992 S1: line context seven brings always fresh documentation to AI coding 1387 01:32:22,992 --> 01:32:27,232 S1: assistance via MCP. This is cool. Okay, so this is 1388 01:32:27,232 --> 01:32:32,592 S1: an MCP you put in your AI system and what 1389 01:32:32,592 --> 01:32:35,712 S1: it does is it will go get the current documentation. 1390 01:32:35,712 --> 01:32:39,092 S1: So if you're like hey, build me a new website 1391 01:32:39,092 --> 01:32:44,572 S1: or build me a website. It will go and get 1392 01:32:45,012 --> 01:32:51,652 S1: just without even asking. Go and get the latest Shadchan documentation, um, 1393 01:32:51,692 --> 01:32:55,092 S1: before it starts doing the design phase using your specs. 1394 01:32:55,892 --> 01:32:59,212 S1: So it won't just start building using its current model knowledge. 1395 01:32:59,372 --> 01:33:03,292 S1: It keeps it updated based on what you mentioned. So 1396 01:33:03,292 --> 01:33:06,412 S1: if you mention MVP, it'll go read the latest MVP stuff. 1397 01:33:06,452 --> 01:33:08,292 S1: If you mention cloud code it'll go read all the 1398 01:33:08,292 --> 01:33:14,932 S1: cloud code docs. Really really cool. Amsterdam's Ritman Library puts 1399 01:33:15,132 --> 01:33:21,331 S1: 2178 rare occult books online for free agent auto updates 1400 01:33:21,332 --> 01:33:26,012 S1: to jobs or auto applies to jobs for for free. Um, 1401 01:33:26,012 --> 01:33:29,852 S1: I haven't used one of these, but, um, I'd like 1402 01:33:29,852 --> 01:33:32,131 S1: to make one and give it to my friends. That's 1403 01:33:32,132 --> 01:33:34,692 S1: what I would like to do. Holy crap. That's a 1404 01:33:34,692 --> 01:33:38,832 S1: project I need to do. Why have I not done that? Okay. 1405 01:33:38,872 --> 01:33:46,592 S1: Hold on. Writing this down. Oh, then I'm going to 1406 01:33:46,592 --> 01:33:50,272 S1: put a stripe page on it and sell it. Um, 1407 01:33:50,272 --> 01:33:57,432 S1: but not for my friends. Okay. Make, um, automated. Sorry. 1408 01:33:57,632 --> 01:34:09,792 S1: Doing this live. Make automated job agent or. Oh. See that? See? 1409 01:34:09,952 --> 01:34:14,192 S1: Watch this. What what what did I actually say? What 1410 01:34:14,192 --> 01:34:18,392 S1: I said was I was making an agent for friends. 1411 01:34:18,512 --> 01:34:22,192 S1: What am I actually conveying? Um. Oh, this guy makes 1412 01:34:22,192 --> 01:34:24,272 S1: stuff for his friends and gives it to him for 1413 01:34:24,272 --> 01:34:27,552 S1: free because he's a nice guy. I am absolutely sure 1414 01:34:27,672 --> 01:34:32,112 S1: I was subconsciously sending that. Um, I'm also consciously sending 1415 01:34:32,112 --> 01:34:34,302 S1: that all the time, so I don't mind that it's 1416 01:34:34,302 --> 01:34:39,062 S1: unconsciously being sent, but there are cases where I'm unconsciously 1417 01:34:39,062 --> 01:34:43,501 S1: sending something that I don't want to be consciously sending. Uh, 1418 01:34:43,542 --> 01:34:47,782 S1: let's see here. Oh, whisper. Oh, whisper makes local text 1419 01:34:47,782 --> 01:34:50,182 S1: to speech as simple as. Oh, llama. This is a 1420 01:34:50,182 --> 01:34:54,302 S1: pretty cool little project. Uh, generated EDM is getting really good, 1421 01:34:54,302 --> 01:35:00,062 S1: so I went and made some EDM. I'm telling you, 1422 01:35:00,982 --> 01:35:03,421 S1: you can make fun of EDM for this, but, like, 1423 01:35:03,462 --> 01:35:07,382 S1: it's starting to sound pretty good. Same with rap songs. Um. Oh, 1424 01:35:07,422 --> 01:35:10,022 S1: metal songs too. Oh my goodness. I've heard some metal 1425 01:35:10,022 --> 01:35:14,222 S1: songs actually. Chad. My buddy Chad made one for my 1426 01:35:14,222 --> 01:35:16,702 S1: character that I just made in this one game. It's 1427 01:35:16,702 --> 01:35:24,142 S1: one D&D game we play on Fridays, and, uh. It's, 1428 01:35:24,182 --> 01:35:26,942 S1: I mean, it was themed to my character and the 1429 01:35:26,942 --> 01:35:30,742 S1: character concepts. I think he used Suno to make it, 1430 01:35:31,102 --> 01:35:34,362 S1: and it was a song. What I sent back to 1431 01:35:34,402 --> 01:35:36,322 S1: him in the text was I would go see these 1432 01:35:36,322 --> 01:35:41,402 S1: people live. I would seriously go and see these people live. 1433 01:35:41,842 --> 01:35:43,802 S1: Of course, there is no these people because he made 1434 01:35:43,802 --> 01:35:48,562 S1: the song in like, you know, 14 seconds using Suno. Um, 1435 01:35:49,362 --> 01:35:54,162 S1: insane insane world. I tools spawn equal and opposite I tools. 1436 01:35:54,162 --> 01:35:58,922 S1: This is Joan Westerberg. She is just killing it. Absolutely 1437 01:35:58,922 --> 01:36:01,642 S1: killing it with the essays, like every single one, is good. 1438 01:36:02,202 --> 01:36:05,522 S1: Shadow AI agents are creating the same security chaos as 1439 01:36:05,522 --> 01:36:10,002 S1: early Wi-Fi adoption. That's another cool analogy I really like. 1440 01:36:10,122 --> 01:36:13,802 S1: We've replaced anxiety with apathy as our defense mechanism. This 1441 01:36:13,802 --> 01:36:18,762 S1: is another one from Westerberg. 70 kids jumped bikes over 1442 01:36:18,762 --> 01:36:22,122 S1: each other constantly. That was me. Um, and there's pictures 1443 01:36:22,122 --> 01:36:24,482 S1: in there and they look very familiar. Actually, a lot 1444 01:36:24,482 --> 01:36:30,742 S1: of the kids look exactly like me. Uh, I Automation 1445 01:36:30,742 --> 01:36:35,382 S1: specialist post job search on Reddit. That was a cool 1446 01:36:35,382 --> 01:36:38,782 S1: one to check out. Recommendation of the week. Think about 1447 01:36:38,782 --> 01:36:42,862 S1: the distance between your thinking, speaking and writing versus your feeling. 1448 01:36:42,862 --> 01:36:47,421 S1: Speaking and writing. Have someone read. Basically, have someone read 1449 01:36:47,462 --> 01:36:49,822 S1: some of your stuff where you think you're going to 1450 01:36:49,822 --> 01:36:53,222 S1: get an unexpected reaction and see what they hear or 1451 01:36:53,422 --> 01:36:56,421 S1: see when they read it. So what were you saying 1452 01:36:56,422 --> 01:36:58,822 S1: without you knowing you were saying it? And you'll have 1453 01:36:58,822 --> 01:37:00,742 S1: to do this with like a very smart friend who's 1454 01:37:00,742 --> 01:37:04,622 S1: also very honest. And then if you find a big gap, 1455 01:37:04,742 --> 01:37:08,302 S1: try to work on making sure that your verbal words 1456 01:37:08,302 --> 01:37:11,782 S1: are the same as your emotional words in the receiver. 1457 01:37:14,182 --> 01:37:17,342 S1: ISM of the week. The first principle is that you 1458 01:37:17,342 --> 01:37:21,102 S1: must not fool yourself and you are the easiest person 1459 01:37:21,102 --> 01:37:24,422 S1: to fool. First principle is that you must not fool 1460 01:37:24,422 --> 01:37:28,622 S1: yourself and you are the easiest person to fool. Richard Feynman.