1 00:00:19,212 --> 00:00:27,852 S1: Hey. What's up? All right, episode 497. Yeah. Hope things 2 00:00:27,852 --> 00:00:31,052 S1: are starting off well this week. Um, got some lab 3 00:00:31,052 --> 00:00:35,772 S1: results back. This is definitely too much information, but, uh, 4 00:00:37,531 --> 00:00:42,052 S1: c metabolic is pristine. Liver is great. Kidneys not so good. 5 00:00:43,692 --> 00:00:46,812 S1: Got to improve kidney function. Uh, turns out too much 6 00:00:46,812 --> 00:00:51,132 S1: creatine is a bad thing. I was actually getting dizziness 7 00:00:51,732 --> 00:00:55,972 S1: from ten grams of creatine, so I think I'm going 8 00:00:56,012 --> 00:01:01,012 S1: to have to go back down to five, maybe even lower. Uh, 9 00:01:01,012 --> 00:01:05,972 S1: because it turns out creatine is not great for the kidneys. And, um, 10 00:01:06,732 --> 00:01:09,732 S1: it's not like real bad, but it's just like, not optimal. 11 00:01:09,732 --> 00:01:15,172 S1: So I need to optimize that, uh, HDL a little 12 00:01:15,172 --> 00:01:18,222 S1: bit too low, LDL a little bit too high. So 13 00:01:19,222 --> 00:01:22,742 S1: I've basically been super sedentary for like the last 4 14 00:01:22,742 --> 00:01:27,022 S1: or 5 months because of working on Kai and all the, uh, 15 00:01:28,062 --> 00:01:30,941 S1: all the crazy stuff going on with AI and projects and, 16 00:01:31,102 --> 00:01:36,182 S1: you know, all the typical stuff, all the crazy world stuff. So, um, 17 00:01:36,222 --> 00:01:39,822 S1: starting to try to adjust to this, uh, stand up 18 00:01:39,822 --> 00:01:46,022 S1: alarms for standing up with my standing desk, um, foam 19 00:01:46,021 --> 00:01:50,302 S1: seating pad with, like, a cutout. So I'm not, like, sitting, um, 20 00:01:52,302 --> 00:01:57,582 S1: in an uncomfortable position all day. Mandatory cardio twice a week. Uh, 21 00:01:57,582 --> 00:02:04,702 S1: table tennis or rucking weights at least twice a week. Uh, 22 00:02:04,702 --> 00:02:06,902 S1: more coffee to balance the Celsius. So that was the 23 00:02:06,902 --> 00:02:11,422 S1: other problem. Wasn't just creatine. I'm drinking like two Celsius 24 00:02:11,462 --> 00:02:17,162 S1: a day, sometimes more, but usually only 1 to two, 25 00:02:18,002 --> 00:02:22,962 S1: and energy drinks and creatine are two of the things 26 00:02:22,962 --> 00:02:28,082 S1: on the list for um. Things to avoid. Uh, if 27 00:02:28,121 --> 00:02:35,242 S1: you have kidney function that's, uh, not optimal. And exercise. Yeah. 28 00:02:35,282 --> 00:02:38,162 S1: Raises HDL. So let me know if you're on a 29 00:02:38,162 --> 00:02:41,562 S1: similar journey. That's kind of where I'm at. Oh sugar 30 00:02:41,562 --> 00:02:45,642 S1: was great. So my metabolic health was ideal. It was 31 00:02:45,642 --> 00:02:48,642 S1: like perfect. So that was that was a great story. 32 00:02:51,042 --> 00:02:56,642 S1: Okay Kai. Update massive context loading. Breakthrough. So I am 33 00:02:56,642 --> 00:03:01,922 S1: now doing a really cool thing where I'm basically I 34 00:03:01,962 --> 00:03:06,762 S1: changed the hook to point to load dynamic context, and 35 00:03:06,802 --> 00:03:10,482 S1: I move that to point two load dynamic context. So 36 00:03:10,482 --> 00:03:14,402 S1: now my routing is actually in the MD file, which 37 00:03:14,401 --> 00:03:19,772 S1: means I can actually navigate that whole thing contextually instead 38 00:03:19,772 --> 00:03:23,612 S1: of having to edit TypeScript code. I am now able 39 00:03:23,612 --> 00:03:28,651 S1: to write it out in text in markdown, basically describing. Yeah. 40 00:03:28,692 --> 00:03:33,052 S1: If you see this type of question, that means I 41 00:03:33,052 --> 00:03:34,932 S1: want you to use the researcher. If you see this 42 00:03:34,932 --> 00:03:38,212 S1: type of thing, that means dynamically load this piece of context. 43 00:03:38,492 --> 00:03:40,532 S1: If you see me talk about this project, that means 44 00:03:40,572 --> 00:03:44,892 S1: go load this piece of context, which means my primary 45 00:03:44,892 --> 00:03:49,892 S1: boot load just gets my core context right. So this 46 00:03:49,892 --> 00:03:54,812 S1: whole UFC system that I talked about in the video is, um, 47 00:03:55,612 --> 00:03:57,892 S1: it's all based on only loading what you need to 48 00:03:57,932 --> 00:04:04,652 S1: load at that particular moment and keeping the context extremely clean. So, uh, 49 00:04:04,652 --> 00:04:07,932 S1: this is just it's really powerful and it's working perfectly. 50 00:04:07,932 --> 00:04:11,252 S1: Like I'm not having any misses. It's actually dynamically loading 51 00:04:11,252 --> 00:04:14,292 S1: exactly what I need. And it's not just the context files, 52 00:04:14,292 --> 00:04:19,952 S1: but it actually loads the correct researcher as well. I'm sorry, 53 00:04:19,952 --> 00:04:26,192 S1: the correct agent, which could be researcher, engineer, designer? Um, pentester. 54 00:04:26,392 --> 00:04:30,072 S1: It can load all those different agents according to the 55 00:04:30,072 --> 00:04:33,432 S1: type of s that, um, that I give it. Right. 56 00:04:33,472 --> 00:04:38,592 S1: So pretty. Pretty cool. And, um, speaking of Chi Pi, 57 00:04:38,632 --> 00:04:44,552 S1: speaking of the whole Pi system, I am open sourcing it. 58 00:04:44,592 --> 00:04:46,991 S1: In fact, I already have. In fact, it's already live. 59 00:04:47,552 --> 00:04:49,592 S1: And I was just going to put the framework up 60 00:04:49,592 --> 00:04:51,712 S1: there and say, hey, look, I'm an add stuff later. 61 00:04:51,712 --> 00:04:56,592 S1: But then I just started adding stuff. Um, and now 62 00:04:56,592 --> 00:04:58,792 S1: I've added a whole bunch of stuff. It's kind of 63 00:04:58,791 --> 00:05:01,272 S1: like the basic structure. It doesn't have the voice stuff 64 00:05:01,272 --> 00:05:05,632 S1: in there yet, but I do have my basic outline 65 00:05:05,632 --> 00:05:08,912 S1: for the main context file and the main tools file, 66 00:05:10,152 --> 00:05:13,952 S1: and then the pointers to where like it's pretty obvious 67 00:05:13,952 --> 00:05:16,682 S1: where to go. Put the other context for the other pieces. 68 00:05:16,682 --> 00:05:20,522 S1: So that is a lot of infrastructure there. I said 69 00:05:20,562 --> 00:05:24,002 S1: in one of the git commits, I'm probably definitely going 70 00:05:24,041 --> 00:05:27,722 S1: to leak something because I'm putting so much of like 71 00:05:27,722 --> 00:05:31,442 S1: my actual stuff out there and it's like, no secrets. 72 00:05:31,481 --> 00:05:35,482 S1: Like I'm literally sharing the actual files. A couple of 73 00:05:35,481 --> 00:05:39,322 S1: things are like redacted for like, keys and stuff like that. 74 00:05:39,322 --> 00:05:42,042 S1: But other than that, like, this is seriously the exact 75 00:05:42,122 --> 00:05:45,242 S1: infrastructure that Cai is using, and you're going to have 76 00:05:45,242 --> 00:05:47,642 S1: to tweak it for that reason. Right. Because I still 77 00:05:47,642 --> 00:05:50,562 S1: have Cai's name in there. I still have like exactly 78 00:05:50,562 --> 00:05:53,922 S1: what I'm saying to him, exactly what what his personality 79 00:05:53,922 --> 00:05:56,642 S1: is and stuff like that. So you'll have to customize 80 00:05:56,642 --> 00:06:00,682 S1: some stuff. But the whole purpose of this is going forward. 81 00:06:00,682 --> 00:06:04,162 S1: When you're watching videos on YouTube that I'm talking about, 82 00:06:05,202 --> 00:06:07,241 S1: I'm not going to say, oh, here's like a gist 83 00:06:07,242 --> 00:06:11,361 S1: file or like, here's some code in the YouTube description. 84 00:06:11,682 --> 00:06:14,212 S1: It's going to be like, hey, go check the Pi 85 00:06:14,252 --> 00:06:17,851 S1: repository and you will see it. And the Pi repository 86 00:06:17,851 --> 00:06:21,972 S1: is set up with a very clear mission. It's like, look, 87 00:06:22,012 --> 00:06:25,972 S1: enable humans to have this functionality. It's the same as fabric, 88 00:06:26,412 --> 00:06:30,092 S1: the same mission as fabric. And now fabric basically falls 89 00:06:30,092 --> 00:06:33,772 S1: under this, right? It falls under pi because fabric is 90 00:06:33,772 --> 00:06:38,452 S1: just one of the sets of tools that I have available. Um, 91 00:06:38,452 --> 00:06:41,452 S1: so she has full access to fabric, has full access 92 00:06:41,452 --> 00:06:45,252 S1: to my foundry stuff, which is the fobs and the 93 00:06:45,252 --> 00:06:49,652 S1: custom commands, the custom cloud commands, like all the different stuff, 94 00:06:49,652 --> 00:06:53,731 S1: it's all in the commands directory and in MCC and 95 00:06:53,731 --> 00:06:56,532 S1: she can use all of it. And that is the 96 00:06:56,532 --> 00:06:59,812 S1: whole purpose of this entire project. And it is now 97 00:06:59,812 --> 00:07:03,972 S1: open source. So it's capital Pi is the name of 98 00:07:03,972 --> 00:07:13,152 S1: the project on GitHub. Okay. Oh yeah. Just thought of 99 00:07:13,152 --> 00:07:15,472 S1: a cool, um. I was sitting here trying to write 100 00:07:15,472 --> 00:07:19,832 S1: the newsletter, uh, and just kept adding more stuff. So 101 00:07:19,832 --> 00:07:22,392 S1: I've got this one. I just added it. So sick. 102 00:07:22,432 --> 00:07:26,992 S1: It's called capture learning. It's a command. And so the 103 00:07:26,992 --> 00:07:31,512 S1: idea is, if I have a I'm working on something 104 00:07:31,512 --> 00:07:35,512 S1: with Kai. We make something new or we're troubleshooting something 105 00:07:35,512 --> 00:07:37,312 S1: and we finally get it to work. I'm just going 106 00:07:37,352 --> 00:07:41,472 S1: to say, hey, write this down or document this, or 107 00:07:41,912 --> 00:07:45,312 S1: capture learning or whatever. And that same thing that I 108 00:07:45,312 --> 00:07:50,072 S1: told you about before, um, that dynamically loads context. Well, 109 00:07:50,072 --> 00:07:55,032 S1: it could also listen because it's being triggered on the prompt, 110 00:07:55,392 --> 00:07:59,512 S1: the user prompt submit that hook is what's actually triggering this. 111 00:07:59,792 --> 00:08:04,472 S1: So if Kai hears anything like that, Kai now knows 112 00:08:04,472 --> 00:08:08,072 S1: to go and execute capture learning. What does that do? 113 00:08:08,272 --> 00:08:13,402 S1: That drops it into the learning context directory. The Learning 114 00:08:13,402 --> 00:08:19,962 S1: Context directory includes a full report of the lesson, the 115 00:08:20,002 --> 00:08:25,082 S1: false assumption that we had, the mistake that we were making, 116 00:08:25,082 --> 00:08:28,402 S1: or whatever talks through the problem, talks through the process 117 00:08:28,402 --> 00:08:31,282 S1: because it has the whole log of our conversation. The 118 00:08:31,282 --> 00:08:34,202 S1: process of how we got there and then what the 119 00:08:34,202 --> 00:08:39,122 S1: solution was and then what the takeaway is. So that's 120 00:08:39,122 --> 00:08:41,642 S1: documented for each one. I'm going to have that going 121 00:08:41,642 --> 00:08:44,442 S1: forward now. And guess what you could do. You could 122 00:08:44,442 --> 00:08:51,882 S1: now say something like Harvest Learnings and then have that 123 00:08:51,881 --> 00:08:55,122 S1: go and compare your current documentation, your current workflows, your 124 00:08:55,122 --> 00:09:00,122 S1: current pipelines, your current context and instructions and everything, and 125 00:09:00,122 --> 00:09:02,882 S1: compare it with the lessons learned and say, is there 126 00:09:02,881 --> 00:09:05,722 S1: anything here that we should update based on the lessons 127 00:09:05,761 --> 00:09:08,441 S1: learned over the last week or the last year or whatever? 128 00:09:09,082 --> 00:09:11,372 S1: So I just think this is a really cool sort 129 00:09:11,372 --> 00:09:18,492 S1: of meta improvement concept. All right. Cybersecurity Npm's most used 130 00:09:18,492 --> 00:09:23,852 S1: UI packages got backdoored to hijack crypto. Yeah. This, uh, 131 00:09:24,452 --> 00:09:28,132 S1: aikido company evidently found this, and, um, put out a 132 00:09:28,172 --> 00:09:35,252 S1: report about it. It's, uh, 18 different packages and, uh. Yeah, 133 00:09:35,292 --> 00:09:40,652 S1: rewritten to steal crypto. Uh, lots of supply chain stuff 134 00:09:40,652 --> 00:09:44,732 S1: going on. Uh, I really like the idea of using. 135 00:09:46,972 --> 00:09:49,852 S1: AI for many eyes. I feel like many eyes is 136 00:09:49,852 --> 00:09:53,891 S1: like my my big, uh, thing I keep coming back 137 00:09:53,892 --> 00:09:57,372 S1: to with with AI. And I think I talked about 138 00:09:57,372 --> 00:10:01,252 S1: this maybe last week or the week before, but SSL, 139 00:10:01,412 --> 00:10:05,332 S1: you remember the giant SSL vulnerability? I think we still 140 00:10:05,332 --> 00:10:08,772 S1: called it SSL back then. Maybe it was already TLS, 141 00:10:08,772 --> 00:10:12,032 S1: but anyway, Why? That was a huge vuln and everyone 142 00:10:12,032 --> 00:10:14,152 S1: was like, hey, how could this possibly happen? This is 143 00:10:14,152 --> 00:10:17,632 S1: open source. And it's like, well, turns out open source 144 00:10:17,631 --> 00:10:20,552 S1: is just a guy. I heard someone say that recently. 145 00:10:20,552 --> 00:10:23,672 S1: Open source is just a guy. You know, it's just 146 00:10:23,872 --> 00:10:28,112 S1: Chris Richards or whatever who lives in Idaho. Turns out 147 00:10:28,352 --> 00:10:31,151 S1: that whole open source, many eyes things. Turns out it's 148 00:10:31,152 --> 00:10:34,511 S1: just Chris and Chris hurt his ankle, and he hasn't 149 00:10:34,511 --> 00:10:36,072 S1: been online in a while. You know what I mean? 150 00:10:36,072 --> 00:10:40,832 S1: So it's like Many Eyes didn't turn out to be 151 00:10:40,872 --> 00:10:43,792 S1: what we thought it was going to be. It's because 152 00:10:43,792 --> 00:10:46,791 S1: what it means, what many eyes, what we thought many 153 00:10:46,792 --> 00:10:50,432 S1: eyes was going to be was many eyes are looking 154 00:10:50,432 --> 00:10:52,752 S1: at the project, but what it turned out to be 155 00:10:52,792 --> 00:10:56,911 S1: was many eyes could look at the project, but they 156 00:10:56,912 --> 00:11:00,672 S1: weren't actually. And so this is why I love the 157 00:11:00,672 --> 00:11:07,952 S1: idea of AI. Many eyes, millions of eyes. Right? Cheap 158 00:11:07,992 --> 00:11:11,002 S1: eyes that don't get tired, don't get sick or whatever, 159 00:11:11,962 --> 00:11:17,722 S1: and you just stick them on the internet. You're just like, hey, 160 00:11:17,722 --> 00:11:23,002 S1: go watch Chris's project. You know, watch the code, you know, 161 00:11:23,042 --> 00:11:26,482 S1: see if anything hasn't been updated, like maybe reach out 162 00:11:26,482 --> 00:11:27,802 S1: and ping them and say, hey, do you want to 163 00:11:27,802 --> 00:11:32,602 S1: update something? Maybe offer to help, uh, you know, maintain 164 00:11:32,602 --> 00:11:37,362 S1: the project or something? Or more importantly, if something nasty 165 00:11:37,442 --> 00:11:40,922 S1: is in there, you can actually find it, go and 166 00:11:40,922 --> 00:11:45,522 S1: report it to him or whatever. Or at the very least, 167 00:11:45,522 --> 00:11:48,522 S1: maybe submit an issue and say there's a vulnerability here, right? 168 00:11:48,962 --> 00:11:52,082 S1: It's like these are the eyes that we need. And 169 00:11:53,682 --> 00:11:57,202 S1: I guess the naive assumption was, well, we'll just train 170 00:11:57,202 --> 00:11:59,762 S1: people up in the school or in the trade schools, 171 00:11:59,802 --> 00:12:04,202 S1: and eventually we'll have millions of developers, millions and millions, 172 00:12:04,202 --> 00:12:08,482 S1: and they'll all be security trained. And guess what? It 173 00:12:08,542 --> 00:12:13,742 S1: didn't happen because one, there's not that many of them. 174 00:12:14,222 --> 00:12:19,142 S1: And two, I mean, who's got time for that? Who's 175 00:12:19,142 --> 00:12:22,582 S1: got time for going and watching all the internets, you know, 176 00:12:22,622 --> 00:12:26,182 S1: open source projects and making sure there's nothing nasty in 177 00:12:26,222 --> 00:12:29,502 S1: them or nothing nasty is being done to them. The 178 00:12:29,502 --> 00:12:35,222 S1: answer is nobody. And it's likely to be nobody forever. Um, 179 00:12:35,222 --> 00:12:40,102 S1: so I think this AI agents thing is a really 180 00:12:40,102 --> 00:12:43,661 S1: good way to achieve this whole mini AIS thing. My 181 00:12:43,662 --> 00:12:46,342 S1: buddy Clint Gibler and team found tons of vulns with 182 00:12:46,342 --> 00:12:48,901 S1: a ten line cloud code prompt, so I think found 183 00:12:48,942 --> 00:12:51,622 S1: like 400 vulns. I think he said it was something 184 00:12:51,622 --> 00:12:57,381 S1: like 20 something Vulns were real, and it's actually fairly easy. 185 00:12:57,422 --> 00:13:02,742 S1: I think, um, to whittle that down and get rid 186 00:13:02,742 --> 00:13:05,302 S1: of a lot of those false positives. But the important 187 00:13:05,302 --> 00:13:08,911 S1: point to me is that ten lines of, you know, 188 00:13:08,952 --> 00:13:14,791 S1: a prompt in cloud code. And it actually found real vulns. 189 00:13:14,872 --> 00:13:17,992 S1: These are real projects that are sitting online. Who knows 190 00:13:17,992 --> 00:13:20,872 S1: if they've been assessed before, but either way, it found 191 00:13:20,872 --> 00:13:24,352 S1: real violence. Now it was noisy. But again, I think 192 00:13:24,352 --> 00:13:30,752 S1: that's a filter. Um, that is likely to, uh, be 193 00:13:30,752 --> 00:13:33,511 S1: pretty easy to build to just, um, you know, take 194 00:13:33,511 --> 00:13:37,391 S1: that in stages and clean those up. Um, yeah. And 195 00:13:37,392 --> 00:13:41,112 S1: there might be a blog post about that. Uh, maybe 196 00:13:41,112 --> 00:13:43,992 S1: a follow up would be nice, um, to maybe talk 197 00:13:43,992 --> 00:13:47,952 S1: about that whole cleanup process, but, uh, very cool work. 198 00:13:49,631 --> 00:13:58,552 S1: Hiring fraud flips zero. Trust from network to identity. So, yeah, 199 00:13:58,592 --> 00:14:04,592 S1: somebody's talking about here hiring fake people. Like they don't 200 00:14:04,592 --> 00:14:07,162 S1: have to break in and they don't have to fish 201 00:14:07,162 --> 00:14:11,401 S1: you if they can just get onboarded as regular employees 202 00:14:11,922 --> 00:14:15,562 S1: with full credentials, right? So this whole fake hiring thing 203 00:14:15,562 --> 00:14:19,242 S1: is becoming a serious issue. It's funny that it's happening 204 00:14:19,242 --> 00:14:23,322 S1: at the same time that people can't get hired. So 205 00:14:23,362 --> 00:14:26,962 S1: it's like, okay, well, if nobody's getting hired and obviously 206 00:14:26,962 --> 00:14:29,362 S1: it's not nobody. But if it's hard to get hired 207 00:14:29,362 --> 00:14:35,442 S1: right now, why are we hiring all these North Koreans anyway? Yeah. 208 00:14:35,482 --> 00:14:41,602 S1: Identity becoming more important than zero trust. Or like the 209 00:14:41,602 --> 00:14:46,402 S1: headline said, zero trust moves to identity instead of, you know, 210 00:14:47,202 --> 00:14:53,522 S1: perimeter or whatever. Critical fixes for Chrome. Definitely go update 211 00:14:53,522 --> 00:15:00,602 S1: their scattered spider now targets browsers as enterprises move operations there. Yeah. 212 00:15:00,602 --> 00:15:04,602 S1: So my buddy Jason Haddox has been talking about AI 213 00:15:04,642 --> 00:15:09,382 S1: moving to the browser as the next phase. And he's right, 214 00:15:09,702 --> 00:15:12,222 S1: he's right. I didn't think it would go this heavy, 215 00:15:12,222 --> 00:15:15,942 S1: but it's going heavy like tons of browsers coming out 216 00:15:15,942 --> 00:15:20,742 S1: with AI built directly in. And, uh, yeah. And now 217 00:15:21,062 --> 00:15:24,542 S1: attackers are going after it as well because and this 218 00:15:24,542 --> 00:15:27,742 S1: was Jason, this is what Jason was explaining to me 219 00:15:27,742 --> 00:15:29,582 S1: why he thought this was going to happen. It's just 220 00:15:29,582 --> 00:15:31,942 S1: like it is the focal point. Like we are usually 221 00:15:31,942 --> 00:15:35,102 S1: in the browser. We need to log into things with 222 00:15:35,102 --> 00:15:37,782 S1: the browser. So we've got like our passkeys set up, 223 00:15:37,782 --> 00:15:40,022 S1: we've got like our password set up. And it's just 224 00:15:40,022 --> 00:15:42,742 S1: like it's a focal point of so much that we do. 225 00:15:43,782 --> 00:15:49,902 S1: So it's a good attack point. Attackers can serve poison 226 00:15:49,902 --> 00:15:53,662 S1: websites only to agents. Yeah, I love this. This is 227 00:15:53,702 --> 00:15:59,222 S1: a really cool one. So you can actually. Yeah. Have 228 00:15:59,222 --> 00:16:01,942 S1: a site that looks fine and acts fine if it's 229 00:16:01,942 --> 00:16:04,382 S1: a human browsing it and using it. But if it's 230 00:16:04,382 --> 00:16:09,632 S1: an AI, they basically get fed prompt stuff that takes 231 00:16:09,632 --> 00:16:16,032 S1: them astray. Kind of like steganography. Actually, if you think 232 00:16:16,032 --> 00:16:20,952 S1: about it, US puts $10 million bounties on three Russian 233 00:16:20,952 --> 00:16:25,152 S1: FSB hackers. Yeah, this administration Trump is a little bit 234 00:16:25,152 --> 00:16:28,232 S1: going after Putin a little bit in a way that 235 00:16:28,232 --> 00:16:33,472 S1: I quite like. Seems like the relationship is fraying and 236 00:16:33,472 --> 00:16:36,872 S1: I'm very happy with that. And it looks like he's 237 00:16:36,872 --> 00:16:41,632 S1: going after some of their hacker groups. Yeah. Good news. 238 00:16:41,752 --> 00:16:46,792 S1: CISOs face growing pressure to hide breaches Cisa pushes universal 239 00:16:46,792 --> 00:16:52,272 S1: Software ingredients lists. Yeah, this is great. This is all 240 00:16:52,272 --> 00:16:54,672 S1: part of the whole supply chain stuff. My buddy, uh, 241 00:16:54,672 --> 00:17:00,192 S1: Sasha's dealer is, uh, over at Crosspoint, and he talks 242 00:17:00,192 --> 00:17:06,092 S1: tons about software supply chain stuff. Uh, and definitely in 243 00:17:06,092 --> 00:17:09,331 S1: relation to, uh, reversing labs, which, as far as I 244 00:17:09,332 --> 00:17:12,092 S1: could tell, is the best company doing this stuff. I'm 245 00:17:12,092 --> 00:17:15,972 S1: not affiliated with them, but they are, uh, really cool 246 00:17:15,972 --> 00:17:20,452 S1: at this stuff. And, um, yeah, probably should get, uh, 247 00:17:20,452 --> 00:17:27,331 S1: more affiliated with them. Um, but yeah. She says, talking 248 00:17:27,332 --> 00:17:31,131 S1: about this, uh, we got the NPM story. Lots of 249 00:17:31,132 --> 00:17:33,412 S1: people have been working on this. It goes back to 250 00:17:33,452 --> 00:17:36,932 S1: what I was just saying about Many Eyes. It reminds 251 00:17:36,932 --> 00:17:39,811 S1: me of also vendor lists, like I used to, uh, 252 00:17:40,132 --> 00:17:43,252 S1: work a lot with vendor lists when I was at Apple, and. 253 00:17:43,252 --> 00:17:46,972 S1: Holy crap, you you think you got a lot of vendors? 254 00:17:46,972 --> 00:17:49,772 S1: You should see Apple. Uh, they got a lot of vendors. Um, 255 00:17:50,012 --> 00:17:54,732 S1: but how many eyes do you need to watch? All 256 00:17:54,732 --> 00:17:56,851 S1: the vendors that you have? Let's say you're a small startup. 257 00:17:56,852 --> 00:17:59,412 S1: Let's say you're a medium or medium sized company. Whatever. 258 00:17:59,612 --> 00:18:02,452 S1: You don't have to be Apple or Google, right? How 259 00:18:02,452 --> 00:18:05,141 S1: many eyes do you need to watch all the different 260 00:18:05,142 --> 00:18:15,422 S1: contracts to watch? Conduct, request. Read, parse, make sense of 261 00:18:15,422 --> 00:18:18,102 S1: and do something with all the different assessments that have 262 00:18:18,102 --> 00:18:23,462 S1: to be happening continuously. Then how about determining where that 263 00:18:23,462 --> 00:18:26,742 S1: stuff is installed on your network and what impact that 264 00:18:26,742 --> 00:18:30,381 S1: might have to the business? How many people do you 265 00:18:30,382 --> 00:18:32,622 S1: need for that? Do you need to hire three extra people? 266 00:18:33,302 --> 00:18:35,262 S1: Because that's going to be a hard ask. Like we're 267 00:18:35,262 --> 00:18:37,902 S1: trying to reduce headcount right now. We can maybe get 268 00:18:37,902 --> 00:18:42,142 S1: you one. How much is that going to help? Right. 269 00:18:42,662 --> 00:18:46,342 S1: I mean, it's just ridiculous. It's a ridiculous question. So. 270 00:18:48,982 --> 00:18:54,342 S1: We need millions of extra eyes who can watch continuously 271 00:18:54,582 --> 00:18:59,542 S1: and constantly, like, it's just like, you know, the solution 272 00:18:59,542 --> 00:19:03,552 S1: is not, you know, an extra person. So I love 273 00:19:03,552 --> 00:19:07,152 S1: this combination of many eyes with the supply chain problem. 274 00:19:10,071 --> 00:19:14,631 S1: You can find bugs by reading code. Yeah. Really cool. Um. 275 00:19:14,632 --> 00:19:20,712 S1: Article here by Alex. Over 1100 exposed Olama servers found 276 00:19:20,712 --> 00:19:24,472 S1: via Shodan. And that's messed up because the question is, 277 00:19:24,472 --> 00:19:29,192 S1: what models are they running? What models are they pointing to? 278 00:19:29,672 --> 00:19:33,712 S1: Are we using up their GPUs. Like yeah what infrastructure 279 00:19:33,752 --> 00:19:37,312 S1: is that on. You can start asking questions like are 280 00:19:37,311 --> 00:19:40,432 S1: they vulnerable? Can you pivot. But you can also ask 281 00:19:40,432 --> 00:19:47,071 S1: resource exhaustion questions. National security US launches a Department of 282 00:19:47,071 --> 00:19:51,992 S1: War site. So our guy was supposed to be like, 283 00:19:51,992 --> 00:19:56,311 S1: the isolationist guy, uh, getting us out of this stuff. 284 00:19:56,592 --> 00:20:00,952 S1: I'm not going to go political here, but. Yeah. Department 285 00:20:00,952 --> 00:20:06,412 S1: of War. Cool. America steps back from the information fight. 286 00:20:06,612 --> 00:20:11,332 S1: This one is disturbing to me. Anne Applebaum says the, um, 287 00:20:11,452 --> 00:20:16,652 S1: current team is gutting US overseas media and Anti-propaganda systems, 288 00:20:17,332 --> 00:20:20,172 S1: which in my opinion, is basically handing that over to 289 00:20:20,212 --> 00:20:24,492 S1: China and Russia to have like full control over the 290 00:20:24,492 --> 00:20:28,572 S1: narrative and story about the West, West versus East, you know, 291 00:20:28,612 --> 00:20:35,252 S1: China versus US, Russia versus the West, whatever. I mean, 292 00:20:35,292 --> 00:20:38,132 S1: this work is nasty regardless. It's nasty. If the US 293 00:20:38,172 --> 00:20:40,412 S1: is doing it and of course we have done it 294 00:20:40,652 --> 00:20:44,572 S1: and we continue to do it, I'm sure. So it's 295 00:20:44,571 --> 00:20:50,371 S1: kind of gross no matter who's doing it. But. I 296 00:20:50,372 --> 00:20:54,692 S1: don't know. That's a longer conversation and definitely, uh, somewhat political. 297 00:20:54,692 --> 00:20:58,652 S1: So I'm going to skip it. But I would say 298 00:21:00,652 --> 00:21:03,742 S1: if you don't want China and Russia to win, maybe 299 00:21:03,782 --> 00:21:07,862 S1: don't allow them to control the narrative in every other 300 00:21:07,862 --> 00:21:14,222 S1: country other than the US. F-35's head to Puerto Rico 301 00:21:14,422 --> 00:21:22,982 S1: as US Venezuela standoff heats up. Mm, yeah. Sending ten 302 00:21:23,022 --> 00:21:30,702 S1: F-35s to Puerto Rico after Venezuelan F-16s buzzed a Navy destroyer. 303 00:21:32,702 --> 00:21:35,902 S1: And yeah. And then that's when that, uh, cartel boat 304 00:21:35,942 --> 00:21:43,982 S1: got hit. Strange times. Uh, State Department says non-immigrant visa 305 00:21:44,022 --> 00:21:48,542 S1: applicants now need to interview from their actual country or 306 00:21:50,142 --> 00:21:55,061 S1: their actual residence, not inside the US. Sudan closes oil 307 00:21:55,061 --> 00:21:59,542 S1: facilities after drone strikes. DHS wants $100 million for counter 308 00:21:59,582 --> 00:22:03,872 S1: drone Counter-drone systems to protect America. I'm on board. I'm 309 00:22:03,872 --> 00:22:06,192 S1: on board. I think we need to stop spending money 310 00:22:06,192 --> 00:22:13,352 S1: on F-35s or whatever modern fighters. I think we need 311 00:22:13,352 --> 00:22:17,752 S1: to move to the next phase. And China is using 312 00:22:17,752 --> 00:22:24,232 S1: its private sector to advance military capabilities. Uh, yes. Yes. 313 00:22:24,552 --> 00:22:27,792 S1: And it's explicit and it's like direct. And it's kind 314 00:22:27,792 --> 00:22:32,632 S1: of super gross and nasty, but also not really. It's nationalistic. 315 00:22:32,672 --> 00:22:36,792 S1: It's like, I mean, doesn't super bother me. What bothers 316 00:22:36,792 --> 00:22:40,432 S1: me is when they claim it's not happening and they're 317 00:22:40,432 --> 00:22:45,912 S1: trying to, you know, spread across the world and basically 318 00:22:46,512 --> 00:22:50,992 S1: get control of everything. And they're hiding this and people 319 00:22:50,992 --> 00:22:54,712 S1: are accepting them in like with Huawei, for example. Like 320 00:22:54,912 --> 00:22:58,632 S1: that's the part that bothers me. Them being nationalistic and 321 00:22:58,672 --> 00:23:02,612 S1: having unity between their private sector and the goals of 322 00:23:02,612 --> 00:23:09,611 S1: the country, it doesn't really bother me. AI OpenAI launches 323 00:23:09,852 --> 00:23:15,132 S1: an Academy and jobs board to reskill displaced workers. I mean, 324 00:23:15,172 --> 00:23:18,372 S1: to give credit to Sam Altman here, he's been saying 325 00:23:18,372 --> 00:23:21,932 S1: for like the whole time, starting in like 22, probably 326 00:23:21,932 --> 00:23:25,732 S1: way before that. But I started paying attention mostly in 22. 327 00:23:26,532 --> 00:23:29,372 S1: And he's like, look, there's going to be tremendous job 328 00:23:29,372 --> 00:23:33,292 S1: loss from AGI or AI in general or whatever. But 329 00:23:33,292 --> 00:23:39,652 S1: definitely after AGI, depending how you define it. But he's like, yeah, 330 00:23:39,652 --> 00:23:42,052 S1: we're going to have to figure out things for people 331 00:23:42,052 --> 00:23:44,411 S1: to do. He's been saying this over and over in 332 00:23:44,412 --> 00:23:48,252 S1: interviews for years and years and years. Um, so if 333 00:23:48,292 --> 00:23:50,091 S1: you didn't know that, then this is going to look 334 00:23:50,132 --> 00:23:52,732 S1: kind of crazy. Like all the reports come out saying 335 00:23:52,892 --> 00:23:56,012 S1: everyone's getting laid off. And then he's like, hey, you know, 336 00:23:56,532 --> 00:23:59,982 S1: we launched a job board. It's a bulletin board. And 337 00:23:59,982 --> 00:24:01,462 S1: you can come and you can pin a piece of 338 00:24:01,462 --> 00:24:03,662 S1: paper to it, and someone can come by and offer 339 00:24:03,662 --> 00:24:10,222 S1: you a job. Thanks, Sam. Super helpful. That's one way 340 00:24:10,222 --> 00:24:11,822 S1: to look at it. Another way to look at it 341 00:24:11,821 --> 00:24:15,702 S1: is obviously you would want to do this to help people. 342 00:24:17,382 --> 00:24:20,302 S1: I'm not sure if this is the same article as 343 00:24:20,302 --> 00:24:24,662 S1: the one competing with LinkedIn. Did I include that one 344 00:24:24,662 --> 00:24:28,902 S1: or not? That was something else I read. I think 345 00:24:28,902 --> 00:24:30,702 S1: it is. I think this is the one that people 346 00:24:30,702 --> 00:24:34,702 S1: are saying is competing with LinkedIn. It's probably how could 347 00:24:34,742 --> 00:24:38,821 S1: they possibly launch two? Anyway, there's another thing where they 348 00:24:38,982 --> 00:24:43,462 S1: they're trying to compete directly with LinkedIn and basically help 349 00:24:43,462 --> 00:24:46,462 S1: people find jobs by matching skills, which is exactly what 350 00:24:46,502 --> 00:24:50,782 S1: LinkedIn Microsoft is doing. A lot of people forget that 351 00:24:50,782 --> 00:24:56,581 S1: Microsoft owns LinkedIn. I forget sometimes, which is why I 352 00:24:56,582 --> 00:25:04,442 S1: just said a lot of people. But really, it's just me. 353 00:25:05,962 --> 00:25:10,841 S1: Anthropic agrees to pay authors at least $1.5 billion in settlement. 354 00:25:12,402 --> 00:25:15,242 S1: So they're doing this to try to avoid a much 355 00:25:15,242 --> 00:25:19,242 S1: bigger one. This is for authors of books. So roughly 356 00:25:19,242 --> 00:25:29,762 S1: $3,000 per book. Huh? Can I get $3,000? How do 357 00:25:29,762 --> 00:25:33,362 S1: I find out if my data is in here? Anthropic 358 00:25:33,362 --> 00:25:39,282 S1: valued at 183 billion after $13 billion. Raise anthropic blocks 359 00:25:39,282 --> 00:25:42,042 S1: Chinese owned firms from Claude. This is because of that 360 00:25:42,042 --> 00:25:45,042 S1: threat research that came out that basically showed a whole 361 00:25:45,042 --> 00:25:49,402 S1: bunch of Chinese companies are actually using it to do, 362 00:25:49,482 --> 00:25:52,482 S1: you know, military oriented stuff and then handing it directly 363 00:25:52,482 --> 00:25:59,252 S1: to the Chinese government. So they Uh, just allow listed 364 00:25:59,252 --> 00:26:04,091 S1: a bunch of them. DeepMind's AI cuts gravitational wave detector 365 00:26:04,092 --> 00:26:11,732 S1: noise by 100,000. I'm telling you, DeepMind, Google stuff, they 366 00:26:11,772 --> 00:26:17,652 S1: are quiet and they just make these massive jumps. And 367 00:26:18,052 --> 00:26:22,972 S1: I I'm very long on Google, very long on Google, 368 00:26:23,212 --> 00:26:26,772 S1: especially as it relates to AI. I think they're just 369 00:26:27,372 --> 00:26:33,132 S1: they're business mind is there, especially with Sundar. Like he's 370 00:26:33,132 --> 00:26:36,571 S1: like the real deal. And they woke up on AI 371 00:26:36,612 --> 00:26:40,172 S1: like they're just they're just crushing it. AI agents could 372 00:26:40,172 --> 00:26:44,532 S1: reshape entire economies within the next decade. This is an 373 00:26:44,732 --> 00:26:50,292 S1: archive paper. Agents on MD emerges as the universal standard 374 00:26:50,292 --> 00:26:54,492 S1: for AI coding agent instructions. So I'm messing with using 375 00:26:54,532 --> 00:26:59,941 S1: agents versus Is clotted with chi. I don't know. I've 376 00:26:59,982 --> 00:27:02,662 S1: gone back and forth twice now. Um, right now, I'm 377 00:27:02,662 --> 00:27:05,582 S1: currently back on Cloudmd because I felt like I was 378 00:27:05,582 --> 00:27:11,101 S1: getting less enforcement. Yeah, I'm going to watch it closely. 379 00:27:11,502 --> 00:27:14,822 S1: High school senior says AI is destroying real learning for 380 00:27:14,821 --> 00:27:22,302 S1: his generation. And, uh, yeah. Says classmates constantly use ChatGPT 381 00:27:22,342 --> 00:27:26,982 S1: for everything from literature annotations to math homework and basically 382 00:27:26,982 --> 00:27:32,502 S1: copy paste exercises from AI, which. Well, I mean, that's 383 00:27:32,502 --> 00:27:36,061 S1: to be expected. The question is, are they also doing 384 00:27:36,061 --> 00:27:40,222 S1: good things with it? And I think from this person's answer, 385 00:27:40,262 --> 00:27:43,182 S1: the answer is no. And this was an article in 386 00:27:43,182 --> 00:27:51,102 S1: The Atlantic. Okay. Um, evidence shows AI is already replacing 387 00:27:51,102 --> 00:27:55,442 S1: entry level workers. Derek Thompson looks at this. Yeah, there's 388 00:27:55,442 --> 00:27:57,841 S1: just more and more data on this coming out. I 389 00:27:57,882 --> 00:28:01,122 S1: don't think it's really debatable at this point, but good 390 00:28:01,122 --> 00:28:05,962 S1: to have additional data there in the newsletter. Technology. Google 391 00:28:06,002 --> 00:28:09,922 S1: gets to keep Chrome but must end exclusive deals and 392 00:28:09,922 --> 00:28:14,322 S1: share search data. So kind of a mostly a win 393 00:28:14,321 --> 00:28:19,361 S1: I would say for Google to not get Chrome divested out. 394 00:28:20,282 --> 00:28:23,522 S1: OpenAI moves to make its own AI chips with Broadcom 395 00:28:24,282 --> 00:28:27,601 S1: and UC Santa Cruz. Engineers show Wi-Fi signals can measure 396 00:28:27,602 --> 00:28:30,962 S1: heart rate. Yeah, I love this stuff. You can actually 397 00:28:31,002 --> 00:28:33,162 S1: see through walls. You can measure the heart rate. You 398 00:28:33,162 --> 00:28:35,602 S1: can yeah, you can do all sorts of stuff with 399 00:28:35,602 --> 00:28:39,322 S1: Wi-Fi signals. Can't wait to see more of this tech 400 00:28:39,322 --> 00:28:43,202 S1: comes to the consumer side. SpaceX can now launch 120 401 00:28:43,242 --> 00:28:47,722 S1: times a year from Florida. Humans job growth stalls as 402 00:28:47,722 --> 00:28:52,442 S1: unemployment hits four year high. Looks like we added just 403 00:28:52,442 --> 00:28:58,412 S1: 22,000 jobs in August. Got a new drug that outperforms 404 00:28:58,452 --> 00:29:03,372 S1: aspirin for heart attack prevention. Private equity rentals make suburbs 405 00:29:03,372 --> 00:29:08,652 S1: more diverse, but apply pressure to buyers. So sometimes it 406 00:29:08,692 --> 00:29:11,852 S1: raises the prices, but sometimes it does bring in other 407 00:29:11,852 --> 00:29:16,852 S1: people who normally couldn't get into that neighborhood. Interesting idea 408 00:29:16,892 --> 00:29:22,492 S1: to have like. The houses being bought up by giant 409 00:29:22,492 --> 00:29:27,452 S1: investment companies. And it's like I guess it's just another landlord. 410 00:29:27,452 --> 00:29:30,332 S1: So I guess maybe it's not that much different than 411 00:29:30,732 --> 00:29:35,132 S1: what we already have, but landlords now it's just a guy, 412 00:29:35,172 --> 00:29:39,612 S1: you know, just a guy or a woman or whatever. 413 00:29:39,652 --> 00:29:43,972 S1: And it's just like they have like three properties and 414 00:29:43,972 --> 00:29:47,012 S1: that's their life. Their landlord feels kind of weird to 415 00:29:47,052 --> 00:29:51,532 S1: just see houses go off the market and it's, you know, 416 00:29:51,572 --> 00:29:56,112 S1: Blackrock or whoever it is. more people are opting out 417 00:29:56,112 --> 00:30:02,472 S1: of news to protect their mood. 40% now skip news, 418 00:30:02,632 --> 00:30:07,512 S1: according to Reuters. Mathematicians just broke an 87 year old 419 00:30:07,512 --> 00:30:13,472 S1: knot theory, conjecture and attention loops. Quietly rewrite your model 420 00:30:13,472 --> 00:30:17,432 S1: of reality. Whatever you stare at long enough starts echoing 421 00:30:17,432 --> 00:30:22,632 S1: back and reshaping you. Yeah. Who was it? Mark Twain. 422 00:30:24,232 --> 00:30:27,792 S1: Somebody said, uh, whatever. You pay attention, you become whatever 423 00:30:27,792 --> 00:30:29,912 S1: you pay attention to. So be careful what you pay 424 00:30:29,912 --> 00:30:33,472 S1: attention to. Not sure if that was Mark Twain or not. 425 00:30:34,592 --> 00:30:42,912 S1: Phones on the toilet. Ray's hemorrhoid risk. Ideas. Here's a 426 00:30:43,272 --> 00:30:46,952 S1: quick idea here. Oh, and by the way, ideas is 427 00:30:46,952 --> 00:30:49,992 S1: essentially something I want to make an essay, but it's 428 00:30:49,992 --> 00:30:52,632 S1: not quite an essay. So quality of a government is 429 00:30:52,762 --> 00:30:56,122 S1: determined by the ease in which its population can be 430 00:30:56,122 --> 00:31:02,162 S1: emotionally manipulated. Emotion versus critical thinking, bro. Knowledge versus deeper education. 431 00:31:02,202 --> 00:31:08,002 S1: Tribalism versus humanism. It's not about religion versus reason, which 432 00:31:08,002 --> 00:31:09,762 S1: is what I used to think when I was younger. 433 00:31:10,002 --> 00:31:12,642 S1: It's about whether you deeply understand how the world works 434 00:31:12,642 --> 00:31:17,002 S1: and can identify and untangle attempts to manipulate you emotionally. 435 00:31:17,322 --> 00:31:19,442 S1: One other thing I'll add here that I didn't put 436 00:31:19,442 --> 00:31:24,642 S1: in the little paragraph here is if you're off balance 437 00:31:24,642 --> 00:31:28,242 S1: because you don't have any money and you're struggling to 438 00:31:28,282 --> 00:31:31,722 S1: find work, and like your life is drama, it's also 439 00:31:31,722 --> 00:31:35,042 S1: hard to have emotional balance. So these emotional arguments that 440 00:31:35,042 --> 00:31:37,802 S1: you're getting of like blaming the other guy or blaming 441 00:31:37,802 --> 00:31:41,122 S1: them or that outgroup or whatever, they're more likely to 442 00:31:41,162 --> 00:31:46,042 S1: land when you have mass instability in the economy and the, 443 00:31:46,082 --> 00:31:49,322 S1: you know, in the country or whatever. So that that 444 00:31:49,322 --> 00:31:53,732 S1: exacerbates the whole problem as well. Continuing on, when I 445 00:31:53,732 --> 00:31:56,692 S1: think about our government for the last 5 or 10 years, 446 00:31:56,692 --> 00:31:58,572 S1: I'm starting to think less about all the messed up 447 00:31:58,572 --> 00:32:01,372 S1: things that the government is doing or has done, and 448 00:32:01,372 --> 00:32:05,492 S1: instead about the deterioration of our education, critical thinking and 449 00:32:05,492 --> 00:32:09,492 S1: wisdom as a population, which is what allowed it. It's 450 00:32:09,492 --> 00:32:11,652 S1: like trying to fill a bathtub when you've taken the 451 00:32:11,652 --> 00:32:14,492 S1: plug out of the bottom. That's why I think the world, 452 00:32:14,492 --> 00:32:17,132 S1: especially Europe, is going to turn away from us. When 453 00:32:17,132 --> 00:32:19,812 S1: I say us, I mean the United States. The problem 454 00:32:19,812 --> 00:32:22,092 S1: isn't who we've elected. It's the fact that there's no 455 00:32:22,092 --> 00:32:26,252 S1: reason to think we won't do it again. Again, because 456 00:32:26,252 --> 00:32:32,411 S1: the population. Because the population can be manipulated. I think 457 00:32:32,412 --> 00:32:36,692 S1: this is like a foundational problem. And when people talk about, 458 00:32:37,052 --> 00:32:40,492 S1: you know, the government's going bad, I'm starting to use 459 00:32:40,492 --> 00:32:44,412 S1: this frame of nope, it's the population that went bad. 460 00:32:46,692 --> 00:32:49,172 S1: And then there's whole conversations about what that means. What 461 00:32:49,172 --> 00:32:52,112 S1: does real education actually look like? It's just the beginning 462 00:32:52,112 --> 00:32:56,152 S1: of the conversation, right? Discovery Rick Rubin's The Way of Code. 463 00:32:57,832 --> 00:33:01,872 S1: This is a very strange site. Gorgeous. Not sure exactly 464 00:33:01,872 --> 00:33:04,152 S1: how it has to do with code, but I was 465 00:33:04,152 --> 00:33:08,432 S1: just checking it out. Quite nice. Muscle mem turns repeated 466 00:33:08,472 --> 00:33:12,792 S1: agent tasks into deterministic replays. This thing is sick, so 467 00:33:12,792 --> 00:33:15,872 S1: it monitors what your AI is doing on your behalf 468 00:33:15,872 --> 00:33:18,992 S1: when it's calling tools and everything. And then it's just 469 00:33:18,992 --> 00:33:22,832 S1: like learning how to do that and turning that into 470 00:33:22,832 --> 00:33:28,552 S1: steps that it can then replay. So yeah, it's just 471 00:33:28,552 --> 00:33:31,632 S1: kind of like learning from what AI does and incorporating 472 00:33:31,632 --> 00:33:36,872 S1: that into your workflows. Being good isn't enough to win anymore. 473 00:33:37,152 --> 00:33:40,992 S1: John Sword's last name is swords. Is that the coolest 474 00:33:40,992 --> 00:33:44,312 S1: last name? It's one of them. Argues that craft alone 475 00:33:44,312 --> 00:33:49,882 S1: doesn't carry you. You need distribution, timing and taste. East 476 00:33:50,282 --> 00:33:53,682 S1: or your good never gets found. This is why I'm 477 00:33:53,682 --> 00:33:55,882 S1: arguing that everyone needs to become a creator. It's not 478 00:33:55,882 --> 00:33:58,762 S1: that you need to become what a creator is today, 479 00:33:59,882 --> 00:34:04,642 S1: but creator just needs to be the new way of living, 480 00:34:04,642 --> 00:34:08,721 S1: which is thinking, building, sharing. I'm arguing that these should 481 00:34:08,722 --> 00:34:13,402 S1: be human things, not creator things. Blogs used to be 482 00:34:13,402 --> 00:34:17,042 S1: weird and personal. So this is a blog by Jet Girl. 483 00:34:17,242 --> 00:34:20,562 S1: Really really good. You should check it out. Cutting end 484 00:34:20,562 --> 00:34:25,602 S1: to end test time. 84% with Cloud Code SDK. Cloud code. 485 00:34:25,922 --> 00:34:28,402 S1: Cloud code SDK. By the way, is just you run 486 00:34:28,402 --> 00:34:32,082 S1: cloud with a switch of P and that is a 487 00:34:32,242 --> 00:34:36,682 S1: standalone like AI. It's it's completely insane. I don't know 488 00:34:36,682 --> 00:34:40,362 S1: why they call it the SDK. It's just a switch 489 00:34:40,402 --> 00:34:46,482 S1: P command. Anyway, probably something I'm missing there. But anyway, 490 00:34:46,522 --> 00:34:50,132 S1: that is it's extremely powerful functionality and I'm going to 491 00:34:50,132 --> 00:34:53,372 S1: be using it a lot more. Make your own handwriting 492 00:34:53,412 --> 00:34:57,892 S1: font easily. Claude FAQs. Tool use unless you enforce strict 493 00:34:57,932 --> 00:35:01,612 S1: tool calling. I have this in tons of my scaffolding 494 00:35:02,492 --> 00:35:06,172 S1: and I have this. Well, it's all in the py repo. 495 00:35:06,212 --> 00:35:09,052 S1: Now you can go check it out. AI enables live 496 00:35:09,052 --> 00:35:12,892 S1: phone calls across language barriers. Oh, I just saw the, um, 497 00:35:13,132 --> 00:35:18,852 S1: Apple Event two today. Two new AirPods live. Transcription. Talking 498 00:35:18,892 --> 00:35:21,452 S1: to anybody. They could just talk in their language and 499 00:35:21,452 --> 00:35:27,532 S1: you get the translation in your ear. Absolutely insane. Wonder 500 00:35:27,532 --> 00:35:31,932 S1: if it works at the haircut place with Vietnamese people. 501 00:35:33,372 --> 00:35:36,132 S1: Like having conversations around you and you don't know if 502 00:35:36,132 --> 00:35:40,812 S1: it's like. Damn, his feet are big. Or if it's 503 00:35:40,852 --> 00:35:43,572 S1: like they're trying to figure out lunch. Like you're not 504 00:35:43,572 --> 00:35:55,792 S1: quite sure. Tech interviews reward complexity over practical engineering. Diallo's 505 00:35:55,912 --> 00:35:59,472 S1: blog post. Yeah, this is a really good blog on 506 00:35:59,512 --> 00:36:04,152 S1: kind of the problems with overall interviewing, which, yeah, they're 507 00:36:04,152 --> 00:36:10,552 S1: just yeah, this is why a lot of AI interviewing, 508 00:36:10,752 --> 00:36:14,192 S1: recruiting services I think are starting to do fairly well 509 00:36:14,872 --> 00:36:17,472 S1: is not so much that they're awesome, it's just that 510 00:36:17,472 --> 00:36:23,752 S1: the status quo is notably bad. Chibi. I think that's 511 00:36:23,752 --> 00:36:27,872 S1: how you pronounce it, analyzes why users churn. This is 512 00:36:27,912 --> 00:36:30,272 S1: actually just a straight link to a vendor, and I 513 00:36:30,272 --> 00:36:34,152 S1: just thought the vendor was pretty cool. And um, no 514 00:36:34,152 --> 00:36:38,952 S1: sponsorship obviously. Otherwise I'd have like a block for them and, 515 00:36:38,992 --> 00:36:43,392 S1: you know, the asterisk or sponsorship or something to indicate 516 00:36:43,392 --> 00:36:46,392 S1: that it's a sponsor. But no, this was just some 517 00:36:46,392 --> 00:36:48,842 S1: pretty cool tech. I feel like churn is like one 518 00:36:48,842 --> 00:36:53,602 S1: of the biggest things. It's like not about the gaining 519 00:36:53,602 --> 00:36:58,362 S1: the users. It's about keeping the users. Random walks almost 520 00:36:58,362 --> 00:37:01,202 S1: never return home in three dimensions. This is a cool 521 00:37:01,202 --> 00:37:07,922 S1: physics thing. Recommendation. Whoa. Recommendation of the week. I'm going 522 00:37:07,922 --> 00:37:11,362 S1: to reuse one that I typically have to ask myself 523 00:37:11,402 --> 00:37:15,482 S1: and kind of always try to ask myself. And that 524 00:37:15,482 --> 00:37:20,402 S1: is especially important right now with like extraordinary change, I think. 525 00:37:20,402 --> 00:37:23,002 S1: What would you do if you're not afraid? Now, normally 526 00:37:23,002 --> 00:37:25,322 S1: I would follow up and say, you shouldn't be afraid, right? 527 00:37:25,362 --> 00:37:28,842 S1: Everything's fine. And, you know, you should just be okay 528 00:37:28,842 --> 00:37:31,602 S1: and think what you would do if you weren't afraid. 529 00:37:32,722 --> 00:37:38,322 S1: But everything isn't okay. But that doesn't mean it's still 530 00:37:38,322 --> 00:37:40,442 S1: not a really good time to ask this question. So 531 00:37:40,482 --> 00:37:43,762 S1: I think the question still stands. What would you do 532 00:37:43,762 --> 00:37:47,382 S1: if you were not afraid? Here's what I would challenge here. 533 00:37:47,382 --> 00:37:53,062 S1: Just to add to this. Think about what your ideal 534 00:37:53,062 --> 00:37:58,022 S1: self looks like. Think about what you and your perfect 535 00:37:58,022 --> 00:38:02,342 S1: Super Saiyan form. What abilities and skills would you have? 536 00:38:02,342 --> 00:38:05,462 S1: What confidence would you have? What narratives would you be 537 00:38:05,502 --> 00:38:09,982 S1: able to tell people? And here's the question is that 538 00:38:09,982 --> 00:38:13,422 S1: person more prepared for what is coming in the future 539 00:38:13,422 --> 00:38:16,622 S1: than you are? And if that's the case, then you 540 00:38:16,622 --> 00:38:20,902 S1: need to think up some dramatic ways, some extreme ways 541 00:38:20,902 --> 00:38:25,502 S1: to possibly migrate to that version of yourself, because that 542 00:38:25,502 --> 00:38:28,462 S1: version is going to survive a lot better maybe, than 543 00:38:28,462 --> 00:38:32,022 S1: your current version. And the aphorism of the week, very 544 00:38:32,022 --> 00:38:35,222 S1: much in line with this, the privilege of a lifetime 545 00:38:35,222 --> 00:38:39,262 S1: is to become who you truly are. The privilege of 546 00:38:39,262 --> 00:38:43,822 S1: a lifetime is to become who you truly are. Carl Jung.