S1: Hey. What's up? All right, episode 497. Yeah. Hope things
S1: are starting off well this week. Um, got some lab
S1: results back. This is definitely too much information, but, uh,
S1: c metabolic is pristine. Liver is great. Kidneys not so good.
S1: Got to improve kidney function. Uh, turns out too much
S1: creatine is a bad thing. I was actually getting dizziness
S1: from ten grams of creatine, so I think I'm going
S1: to have to go back down to five, maybe even lower. Uh,
S1: because it turns out creatine is not great for the kidneys. And, um,
S1: it's not like real bad, but it's just like, not optimal.
S1: So I need to optimize that, uh, HDL a little
S1: bit too low, LDL a little bit too high. So
S1: I've basically been super sedentary for like the last 4
S1: or 5 months because of working on Kai and all the, uh,
S1: all the crazy stuff going on with AI and projects and,
S1: you know, all the typical stuff, all the crazy world stuff. So, um,
S1: starting to try to adjust to this, uh, stand up
S1: alarms for standing up with my standing desk, um, foam
S1: seating pad with, like, a cutout. So I'm not, like, sitting, um.
S1: In an uncomfortable position all day. Mandatory cardio twice a week. Uh,
S1: table tennis or rucking weights at least twice a week. Uh,
S1: more coffee to balance the Celsius. So that was the
S1: other problem. Wasn't just creatine. I'm drinking like two Celsius
S1: a day. Sometimes more, but usually only 1 to 2,
S1: and energy drinks and creatine are two of the things
S1: on the list for, um, things to avoid. If you
S1: have kidney function that's, uh, not optimal. And exercise. Yeah.
S1: Raises HDL. So let me know if you're on a
S1: similar journey. That's kind of where I'm at. Oh sugar
S1: was great. So my metabolic health was ideal. It was
S1: like perfect. So that was that was a great story.
S1: Okay Kai. Update massive context loading. Breakthrough. So I am
S1: now doing a really cool thing where I'm basically I
S1: changed the hook to point to load dynamic context, and
S1: I move that to point two load dynamic context MD
S1: so now my routing is actually in the MD file,
S1: which means I can actually navigate that whole thing contextually.
S1: Instead of having to edit TypeScript code, I am now
S1: able to write it out in text in markdown, basically describing. Yeah.
S1: If you see this type of question, um, that means
S1: I want you to use the researcher. If you see
S1: this type of thing, that means dynamically load this piece
S1: of context. If you see me talk about this project,
S1: that means go load this piece of context, which means
S1: my primary boot load just gets my core context right.
S1: So this whole UFC system that I talked about in
S1: the video is, um, it's all based on only loading
S1: what you need to load at that particular moment and
S1: keeping the context extremely clean. So, uh, this is just
S1: it's really powerful and it's working perfectly. Like I'm not
S1: having any misses. It's actually dynamically loading exactly what I need.
S1: And it's not just the context files, but it actually
S1: loads the correct researcher as well. Or I'm sorry, the
S1: correct agent, which could be researcher, engineer, designer or pentester.
S1: It can load all those different agents according to the
S1: type of asset that, um, that I give it. Right.
S1: So pretty. Pretty cool. And, um, speaking of Chi Pi,
S1: speaking of the whole Pi system, I am open sourcing it.
S1: In fact, I already have. In fact, it's already live.
S1: And I was just going to put the framework up
S1: there and say, hey, look, I'm going to add stuff later.
S1: But then I just started adding stuff. Um, and now
S1: I've added a whole bunch of stuff. It's kind of
S1: like the basic structure. It doesn't have the voice stuff
S1: in there yet, but I do have my basic outline
S1: for the main context file and the main tools file,
S1: and then the pointers to where like, it's pretty obvious
S1: where to go. Put the other context for the other pieces.
S1: So that is a lot of infrastructure there. I said
S1: in one of the git commits, I'm probably definitely going
S1: to leak something because I'm putting so much of like
S1: my actual stuff out there, and it's like, no secrets.
S1: Like I'm literally sharing the actual files. A couple of
S1: things are like redacted for like keys and stuff like that.
S1: But other than that, like, this is seriously the exact
S1: infrastructure that Cai is using, and you're going to have
S1: to tweak it for that reason, right? Because I still
S1: have Cai's name in there. I still have like exactly
S1: what I'm saying to him, exactly what what his personality
S1: is and stuff like that. So you'll have to customize
S1: some stuff. But the whole purpose of this is going forward.
S1: When you're watching videos on YouTube that I'm talking about,
S1: I'm not going to say, oh, here's like a gist
S1: file or like, here's some code in the YouTube description.
S1: It's going to be like, hey, go check the Pi
S1: repository and you will see it. And the Pi repository
S1: is set up with a very clear mission. It's like, look,
S1: enable humans to have this functionality. It's the same as fabric,
S1: the same mission as fabric. And now fabric basically falls
S1: under this, right? It falls under pi because fabric is
S1: just one of the sets of tools that I have available. Um,
S1: so Kai has full access to fabric, has full access
S1: to my foundry stuff, which is the fobs and the
S1: custom commands, the custom cloud commands, like all the different stuff,
S1: it's all in the commands directory and in mic, and
S1: Kai can use all of it. And that is the
S1: whole purpose of this entire project. And it is now
S1: open source. So it's capital Pi is the name of
S1: the project on GitHub. Okay. Oh, yeah. Just thought of
S1: a cool. Um. I was sitting here trying to write
S1: the newsletter, uh, and just kept adding more stuff. So
S1: I've got this one. I just added it. So sick.
S1: It's called capture learning. It's a command. And so the
S1: idea is, if I have a I'm working on something
S1: with Kai. We make something new or we're troubleshooting something
S1: and we finally get it to work. I'm just going
S1: to say, hey, write this down or document this, or
S1: capture learning or whatever. And that same thing that I
S1: told you about before, um, that dynamically loads context. Well,
S1: it could also listen because it's being triggered on the prompt,
S1: the user prompt submit that hook is what's actually triggering this.
S1: So if Kai hears anything like that, Kai now knows
S1: to go and execute capture learning. What does that do?
S1: that drops it into the Learning Context directory. The learning
S1: context directory includes a full report of the lesson, the
S1: false assumption that we had, the mistake that we were making,
S1: or whatever talks through the problem, talks through the process
S1: because it has the whole log of our conversation, the
S1: process of how we got there and then what the
S1: solution was and then what the takeaway is. So that's
S1: documented for each one. I'm going to have that going
S1: forward now. And guess what you could do. You could
S1: now say something like Harvest Learnings and then have that
S1: go and compare your current documentation, your current workflows, your
S1: current pipelines, your current context and instructions and everything, and
S1: compare it with the lessons learned and say, is there
S1: anything here that we should update based on the lessons
S1: learned over the last week or the last year or whatever.
S1: So I just think this is a really cool sort
S1: of meta improvement concept. All right. Cybersecurity. Npm's most used
S1: UI packages got backdoored to hijack crypto. Yeah. This, uh,
S1: aikido company evidently found this, and, um, put out a
S1: report about it. It's 18 different packages and, uh. Yeah,
S1: rewritten to steal crypto. Uh, lots of supply chain stuff
S1: going on. Uh, I really like the idea of using.
S1: AI for many eyes. I feel like many eyes is
S1: like my my big, uh, thing I keep coming back
S1: to with with AI. And I think I talked about
S1: this maybe last week or the week before, but SSL,
S1: you remember the giant SSL vulnerability? I think we still
S1: called it SSL back then. Maybe it was already TLS,
S1: but anyway, that was a huge vuln and everyone was like, hey,
S1: how could this possibly happen? This is open source. And
S1: it's like, well, turns out open source is just a guy.
S1: I heard someone say that recently. Open source is just
S1: a guy. You know, it's just Chris Richards or whatever
S1: who lives in Idaho. Turns out that whole open source,
S1: many eyes things. Turns out it's just Chris and Chris
S1: hurt his ankle and he hasn't been online in a while.
S1: You know what I mean? So it's like Many Eyes
S1: didn't turn out to be what we thought it was
S1: going to be. It's because what it means, what many eyes,
S1: what we thought many eyes was going to be was
S1: many eyes are looking at the project, but what it
S1: turned out to be was many eyes could look at
S1: the project, but they weren't actually. And so this is
S1: why I love the idea of AI. Many eyes. Millions
S1: of eyes. Right. Cheap eyes that don't get tired, don't
S1: get sick or whatever. And you just stick them on
S1: the internet. You're just like, hey, go watch Chris's project.
S1: You know, watch the code, you know, see if anything
S1: hasn't been updated, like, maybe reach out and ping them
S1: and say, hey, do you want to update something? Maybe
S1: offer to help, uh, you know, maintain the project or something?
S1: Or more importantly, if something nasty is in there, you
S1: can actually find it, go and report it to him
S1: or whatever. Or at the very least, maybe submit an
S1: issue and say there's a vulnerability here, right? It's like
S1: these are the eyes that we need. And I guess
S1: the naive assumption was, well, we'll just train people up
S1: in the school or in the trade schools, and eventually
S1: we'll have millions of developers, millions and millions and they'll
S1: all be security trained. And guess what? It didn't happen
S1: because one, there's not that many of them. And two,
S1: I mean, who's got time for that? Who's got time
S1: for going and watching all the internets, you know, open
S1: source projects and making sure there's nothing nasty in them
S1: or nothing nasty is being done to them. The answer
S1: is nobody. And it's likely to be nobody forever. Um,
S1: so I think this AI agents thing is a really
S1: good way to achieve this whole mini AIS thing. My
S1: buddy Clint Gibler and team found tons of vulns with
S1: a ten line cloud code prompt, so I think found
S1: like 400 vulns. I think he said it was something
S1: like 20 something Vulns were real, and it's actually fairly easy,
S1: I think, um, to whittle that down and get rid
S1: of a lot of those false positives. But the important
S1: point to me is that ten lines of, you know,
S1: a prompt in cloud code, and it actually found real vulns.
S1: These are real projects that are sitting online. Who knows
S1: if they've been assessed before, but either way, it found
S1: real violence. Now it was noisy. But again, I think
S1: that's a filter. Um, that is likely to, uh, be
S1: pretty easy to build to just, um, you know, take
S1: that in stages and clean those up. Um, yeah. And
S1: there might be a blog post about that. Uh, maybe
S1: a follow up would be nice, um, to maybe talk
S1: about that whole cleanup process, but, uh, very cool work.
S1: Hiring fraud flips zero. Trust from network to identity. So, yeah,
S1: somebody's talking about here Hiring fake people, like they don't
S1: have to break in and they don't have to phish
S1: you if they can just get onboarded as regular employees
S1: with full credentials. So this whole fake hiring thing is
S1: becoming a serious issue. It's funny that it's happening at
S1: the same time that people can't get hired. So it's like, okay, well,
S1: if nobody's getting hired, and obviously it's not nobody. But
S1: if it's hard to get hired right now, why are
S1: we hiring all these North Koreans anyway? Yeah. Identity becoming
S1: more important than zero trust. Or like the headline said,
S1: zero trust moves to identity instead of, you know, perimeter
S1: or whatever. Critical fixes for Chrome definitely go update their
S1: scattered spider now targets browsers as enterprises move operations there. Yeah. So, uh,
S1: my buddy Jason Haddox has been talking about AI moving
S1: to the browser as the next phase. And he's right.
S1: He's right. I didn't think it would go this heavy,
S1: but it's going heavy like tons of browsers coming out
S1: with AI built directly in. And, uh, yeah. And now
S1: attackers are going after it as well because. And this
S1: was Jason. This is what Jason was explaining to me
S1: why he thought this was going to happen. It's just
S1: like it is the focal point. Like we are usually
S1: in the browser. We need to log into things with
S1: the browser. So we've got like our passkeys set up.
S1: We got like our password set up. And it's just
S1: like it's a focal point of so much that we do.
S1: So it's a good attack point. Attackers can serve poison
S1: websites only to agents. Yeah, I love this. This is
S1: a really cool one. So you can actually. Yeah. Have
S1: a site that looks fine and acts fine if it's
S1: a human browsing it and using it. But if it's
S1: an AI, they basically get fed, uh, prompt AI stuff
S1: that takes them astray. Kind of like steganography. Actually, think
S1: about it. US puts $10 million bounties on three Russian
S1: FSB hackers. Yeah. This administration. Trump is a little bit
S1: going after Putin, a little bit in a way that
S1: I quite like. Seems like the relationship is fraying and
S1: I'm very happy with that. And it looks like he's
S1: going after some of their, uh, hacker groups. Yeah. Good news.
S1: CISOs face growing pressure to hide breaches Cisa pushes universal
S1: software ingredients lists. Yeah, this is great. This is all
S1: part of the whole supply chain stuff. My buddy, uh,
S1: Sasha's dealer is, over at crosspoint and he talks tons
S1: about software supply chain stuff. Uh, and definitely in relation to, uh,
S1: reversing labs, which, as far as I could tell, is
S1: the best company doing this stuff. I'm not affiliated with them,
S1: but they are, uh, really cool at this stuff. And, um, yeah,
S1: probably should get, uh, more affiliated with them. Um, but yeah.
S1: CSA's talking about this. Uh, we got the NPM story.
S1: Lots of people have been working on this. It goes
S1: back to what I was just saying about Many Eyes.
S1: It reminds me of also vendor lists, like I used to, uh,
S1: work a lot with vendor lists when I was at Apple, and.
S1: Holy crap, you you think you got a lot of vendors?
S1: You should see Apple. They got a lot of vendors. Um,
S1: but how many eyes do you need to watch all
S1: the vendors that you have? Let's say you're a small startup.
S1: Let's say you're a medium sized company. Whatever. You don't
S1: have to be Apple or Google, right? How many eyes
S1: do you need to watch all the different contracts to watch. Conduct, request. Read, parse,
S1: make sense of and do something with all the different
S1: assessments that have to be happening continuously. Then how about
S1: determining where that stuff is installed on your network and
S1: what impact that might have to the business? How many
S1: people you need for that? Do you need to hire
S1: three extra people? Because that's going to be a hard ask.
S1: Like we're trying to reduce headcount right now. We can
S1: maybe get you one. How much is that going to help? Right.
S1: I mean, it's just ridiculous. It's a ridiculous question. So.
S1: We need millions of extra eyes who can watch continuously
S1: and constantly like, it's just like, you know, the solution
S1: is not, you know, an extra person. So I love
S1: this combination of many eyes with the supply chain problem.
S1: You can find bugs by reading code. Yeah. Really cool. Um,
S1: article here by Alex. Over 1100 exposed Olama servers found
S1: via Shodan. And that's messed up because the question is,
S1: what models are they running? What models are they pointing to?
S1: Are we using up their GPUs. Like yeah what infrastructure
S1: is that on. You can start asking questions like are
S1: they vulnerable? Can you pivot. But you can also ask
S1: resource exhaustion questions. National security US launches a Department of
S1: War site. So our guy was supposed to be like
S1: the isolationist guy. sky. Getting us out of this stuff.
S1: Not going to go political here, but. Yeah. Department of war. Cool.
S1: America steps back from the information fight. This one is
S1: disturbing to me. Anne Applebaum says the current team is
S1: gutting US overseas media and Anti-propaganda systems, which in my opinion,
S1: is basically handing that over to China and Russia to
S1: have like, full control over the narrative and story about
S1: the West, West versus East, you know, China versus US,
S1: Russia versus the West, whatever. I mean, this work is
S1: nasty regardless. It's nasty. If the US is doing it
S1: and of course we have done it and we continue
S1: to do it, I'm sure. So it's kind of gross
S1: no matter who's doing it, but. I don't know. That's
S1: a longer conversation and definitely, uh, somewhat political. So I'm
S1: going to skip it. But I would say if you
S1: don't want China and Russia to win, maybe don't allow
S1: them to control the narrative in every other country other
S1: than the US. F-35's head to Puerto Rico as US
S1: Venezuela standoff heats up. Hmm. Yeah. Sending ten F-35s to
S1: Puerto Rico after Venezuelan F-16s buzzed a Navy destroyer. And. Yeah,
S1: and then that's when that, uh, cartel boat got hit.
S1: Strange times. Uh, State Department says non-immigrant visa applicants now
S1: need to interview from their actual country or their actual residence, residents,
S1: not inside the US. Sudan closes oil facilities after drone strikes.
S1: DHS wants $100 million for counter drone systems to protect America.
S1: I'm on board. I'm on board. I think we need
S1: to stop spending money on F-35s or whatever modern fighters.
S1: I think we need to move to the next phase.
S1: And China is using its private sector to advance military capabilities. Uh, yes. Yes.
S1: And it's explicit and it's like direct. And it's kind
S1: of super gross and nasty, but also not really. It's nationalistic.
S1: It's like, I mean, doesn't super bother me. What bothers
S1: me is when they claim it's not happening and they're
S1: trying to, you know, spread across the world and basically
S1: get control of everything. And they're hiding this and people
S1: are accepting them in like with Huawei, for example. Like
S1: that's the part that bothers me, them being nationalistic and
S1: having unity between their private sector and the goals of
S1: the country. And it doesn't really bother me. AI OpenAI
S1: launches an academy and jobs board to reskill displaced workers.
S1: I mean, to give credit to Sam Altman here, he's
S1: been saying for like the whole time, starting in like 22,
S1: probably way before that. But I started paying attention mostly
S1: in 22. And he's like, look, there's going to be
S1: tremendous job loss from AGI or AI in general or whatever.
S1: But definitely after AGI, depending on how you define it.
S1: But he's like, yeah, we're going to have to figure
S1: out things for people to do. He's been saying this
S1: over and over in interviews for years and years and years. Um,
S1: so if you didn't know that, then this is going
S1: to look kind of crazy. Like all the reports come
S1: out saying everyone's getting laid off. And then he's like, hey,
S1: you know, we launched a job board. It's a bulletin board.
S1: And you can come and you can pin a piece
S1: of paper to it, and someone can come by and
S1: offer you a job. Thanks, Sam. Super helpful. That's one
S1: way to look at it. Another way to look at
S1: it is obviously you would want to do this to
S1: help people. I'm not sure if this is the same
S1: article as the one competing with LinkedIn. Did I include
S1: that one or not? That was something else I read.
S1: I think it is. I think this is the one
S1: that people are saying is competing with LinkedIn. It's probably
S1: how could they possibly launch two? Anyway, there's another thing
S1: where they they're trying to compete directly with LinkedIn and
S1: basically help people find jobs by matching skills, which is
S1: exactly what LinkedIn Microsoft is doing. A lot of people
S1: forget that Microsoft owns LinkedIn. I forget sometimes, which is
S1: why I just said a lot of people. But really,
S1: it's just me. Anthropic agrees to pay authors at least
S1: 1.5 billion in settlement. So they're doing this to try
S1: to avoid a much bigger one. This is for authors
S1: of books. So roughly $3,000 per book. Huh? Can I
S1: get $3,000? How do I find out if my data
S1: is in here? Anthropic valued at 183 billion after $13 billion.
S1: Raise anthropic blocks. Chinese owned firms from Claude. This is
S1: because of that threat research that came out that basically
S1: showed a whole bunch of Chinese companies are actually using
S1: it to do, you know, military oriented stuff and then
S1: handing it directly to the Chinese government. So they disallow
S1: listed a bunch of them. DeepMind's AI cuts gravitational wave
S1: detector noise by 100,000. I'm telling you DeepMind Google stuff,
S1: they are quiet and they just make these massive jumps.
S1: And I I'm very long on Google, very long on Google,
S1: especially as it relates to AI. I think they're just
S1: they're business mind is there, especially with Sundar. Like he's
S1: like the real deal. And they woke up on AI
S1: like they're just they're just crushing it. AI agents could
S1: reshape entire economies within the next decade. This is a
S1: arXiv archived paper. Agents on MD emerges as the universal
S1: standard for AI coding agent instructions. So I'm messing with
S1: using agents versus coded MD with Chi. I don't know.
S1: I've gone back and forth twice now. Um, right now
S1: I'm currently back on Cloudmd because I felt like I
S1: was getting less enforcement. Yeah, I'm going to watch it closely.
S1: High school senior says AI is destroying real learning for
S1: his generation. And, uh, yeah. Says classmates constantly use ChatGPT
S1: for everything from literature annotations to math homework and basically
S1: copy paste exercises from AI, which. Well, I mean, that's
S1: to be expected. The question is, are they also doing
S1: good things with it? And I think from this person's answer,
S1: the answer is no. And this was an article in
S1: The Atlantic. Okay. Um, evidence shows AI is already replacing
S1: entry level workers. Derek Thompson looks at this. Yeah, there's
S1: just more and more data on this coming out. This.
S1: I don't think it's really debatable at this point, but
S1: good to have additional data there in the newsletter. Technology.
S1: Google gets to keep Chrome but must end exclusive deals
S1: and share search data. So kind of a mostly a
S1: win I would say for Google to not get, uh,
S1: Chrome divested out. OpenAI moves to make its own AI
S1: chips with Broadcom and UC Santa Cruz. Engineers show Wi-Fi
S1: signals can measure heart rate. Yeah, I love this stuff.
S1: You can actually see through walls. You can measure your
S1: heart rate. You can. Yeah. You could do all sorts
S1: of stuff with Wi-Fi signals. Can't wait to see more
S1: of this. Tech comes to the consumer side. SpaceX can
S1: now launch 120 times a year from Florida humans. Job
S1: growth stalls as unemployment hits four year high. Looks like
S1: we added just 22,000 jobs in August. Got a new
S1: drug that outperforms aspirin for heart attack prevention. Private equity
S1: rentals make suburbs more diverse, but apply pressure to buyers.
S1: So sometimes it raises the prices, but sometimes it does
S1: bring in other people who normally couldn't get into that neighborhood.
S1: Interesting idea to have like. The houses being bought up
S1: by giant investment companies. And it's like I guess it's
S1: just another landlord. So I guess maybe it's not that
S1: much different than what we already have, but landlords now
S1: it's just a guy, you know, just a guy or
S1: a woman or whatever. And it's just like. They have
S1: like three properties and that's their life. Their landlord feels
S1: kind of weird to just see houses go off the
S1: market and it's, you know, Blackrock or whoever it is.
S1: More people are opting out of news to protect their mood. 40%
S1: now skip news, according to Reuters. Mathematicians just broke an
S1: 87 year old knot theory, conjecture and attention loops. Quietly
S1: rewrite your model of reality. Whatever you stare at long
S1: enough starts echoing back and reshaping you. Yeah. Who was it?
S1: Mark Twain. Somebody said, uh, whatever. You pay attention, you
S1: become whatever you pay attention to. So be careful what
S1: you pay attention to. Not sure if that was Mark
S1: Twain or not. Phones on the toilet raise hemorrhoid risk. Discovery,
S1: Rick Rubin's The Way of Code. This is a very
S1: strange site. Gorgeous. Not sure exactly how it has to
S1: do with code, but I was just checking it out.
S1: Quite nice. Muscle memory turns repeated agent tasks into deterministic replays.
S1: This thing is sick, so it monitors what your AI
S1: is doing on your behalf when it's calling tools and everything.
S1: And then it's just like learning how to do that
S1: and turning that into steps that it can then replay.
S1: So yeah, it's just kind of like learning from what
S1: AI does and incorporating that into your workflows. Being good
S1: isn't enough to win anymore. John Sword's last name is swords.
S1: Is that the coolest last name? It's one of them.
S1: Argues that craft alone doesn't carry you. You need distribution,
S1: timing and taste. Or your good never gets found. This
S1: is why I'm arguing that everyone needs to become a creator.
S1: It's not that you need to become what a creator
S1: is today, but creator just needs to be the new
S1: way of living, which is thinking, building, sharing. I'm arguing
S1: that these should be human things, not creator things. Blogs
S1: used to be weird and personal. So this is a
S1: blog by Jet Girl. Really really good. You should check
S1: it out. Cutting end to end test time. 84% with
S1: Cloud Code SDK. Cloud code. Cloud code SDK. By the way,
S1: is just you run cloud with a switch of P
S1: and that is a standalone like AI. It's it's completely insane.
S1: I don't know why they call it the SDK. It's
S1: just a switch P command. Anyway, probably something I'm missing there.
S1: But anyway, that is it's extremely powerful functionality and I'm
S1: going to be using it a lot more. Make your
S1: own handwriting font easily. Claude FAQs tool use unless you
S1: enforce strict tool calling. I have this in tons of
S1: my scaffolding and I have this. Well, it's all in
S1: the Pi repo now you can go check it out.
S1: AI enables live phone calls across language barriers. Oh, I
S1: just saw the, um, Apple event to today. Two new
S1: AirPods live transcription. Talking to anybody. They could just talk
S1: in their language and you get the translation in your ear.
S1: Absolutely insane. I wonder if it works at the haircut
S1: place with Vietnamese people. Like having conversations around you and
S1: you don't know if it's like. Damn, his feet are big.
S1: Or if it's like they're trying to figure out lunch.
S1: Like you're not quite sure. Tech interviews reward complexity over
S1: practical engineering. Diallo's blog post. Yeah, this is a really
S1: good blog on kind of the problems with overall interviewing, which, yeah,
S1: there's just yeah, this is why a lot of AI interviewing,
S1: recruiting services I think are starting to do fairly well
S1: is not so much that they're awesome, it's just that
S1: the status quo is notably bad. Chibi. I think that's
S1: how you pronounce it, analyzes why users churn. This is
S1: actually just a straight link to a vendor, and I
S1: just thought the vendor was pretty cool. And um, no
S1: sponsorship obviously. Otherwise I'd have like a block for them and,
S1: you know, the asterisk or sponsorship or something to indicate
S1: that it's a sponsor. But no, this is just some
S1: pretty cool tech. I feel like churn is like one
S1: of the biggest things. It's like not about the gaining
S1: the users. It's about keeping the users. Random walks almost
S1: never return home in three dimensions. This is a cool
S1: physics thing. Recommendation. Whoa. Recommendation of the week. I'm going
S1: to reuse one that I typically have to ask myself
S1: and kind of always try to ask myself. And that
S1: is especially important right now with like extraordinary change, I think.
S1: What would you do if you're not afraid? Now, normally
S1: I would follow up and say, you shouldn't be afraid, right?
S1: Everything's fine. And, you know, you should just be okay
S1: and think what you would do if you weren't afraid.
S1: But everything isn't okay. But that doesn't mean it's still
S1: not a really good time to ask this question. So
S1: I think the question still stands. What would you do
S1: if you were not afraid? Here's what I would challenge
S1: here Just to add to this. Think about what your
S1: ideal self looks like. Think about what you and your
S1: perfect Super Saiyan form. What abilities and skills would you have?
S1: What confidence would you have? What narratives would you be
S1: able to tell people? And here's the question is that
S1: person more prepared for what is coming in the future
S1: than you are? And if that's the case, then you
S1: need to think up some dramatic ways, some extreme ways
S1: to possibly migrate to that version of yourself, because that
S1: version is going to survive a lot better maybe, than
S1: your current version. And the aphorism of the week, very
S1: much in line with this, the privilege of a lifetime
S1: is to become who you truly are. The privilege of
S1: a lifetime is to become who you truly are. Carl Jung.