Tobi Lütke: The Skills AI Makes More Valuable

Shopify founder and CEO Tobi Lütke joins Shane Parrish to discuss AI agents, better decision-making, and the future of work. He explains how he uses an AI council to examine his hardest decisions and why taste, judgment, and responsibility become more valuable as AI becomes more capable. They go inside Shopify’s work with River, an AI colleague with memory, personality, and permission to challenge the CEO. They explore how to choose between several good options, why the best long-term decisions often lack immediate feedback, and why building something that lasts requires pruning and rebuilding. Tobi also shares how he cultivates intuition, the affirmations he uses to change his own behavior, and why his kids must add “yet” when they say they can’t do something. Enjoy! ----- Chapters: (00:00) Introduction (3:46) The Case for Skeuomorphism (5:16) How Bing's Chatbot "Sydney" Inspired Shopify's AI (7:18) River: Shopify's Internal AI (8:55) How to Encourage Osmosis Learning (10:52) AI Dreaming and Self-Reflection (11:53) How to Use AI for Strategic Decision Making (14:11) The One Thing AI Cannot Do (16:04) What AI is Making Worse at Shopify (19:46) Predictions: Where AI is Headed Next (21:55) The Future of AI-Powered Software (24:40) Will CEOs Be Replaced with AI? (27:54) Can Superintelligence Be Controlled? (31:13) Critical Skills in AI Age (34:22) Why Complex Solutions are Usually Wrong (36:33) Conditions Needed for True Intuition (38:02) The Optimal Path Doesn't Have Instant Feedback (44:51) How Affirmations Can Shift Your Behavior (50:44) The Inobvious Thing Hurting Companies (52:37) Relationship Between Beauty and Creation (56:23) How SpaceX Moves Forward By Subtraction (1:00:24) Why Companies Need Refounding Events (1:01:50) Use Books as Cheat Codes (1:02:39) Three Books That Change Your Thinking ----- Follow Tobi: X: https://x.com/tobi ------ Newsletter: The Brain Food newsletter delivers actionable insights and thoughtful ideas every Sunday. It takes 5 minutes to read, and it’s completely free. Learn more and sign up at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠fs.blog/newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ------ Follow Shane Parrish: X: ⁠⁠⁠⁠⁠⁠https://x.com/shaneparrish⁠ Instagram: ⁠⁠⁠⁠⁠⁠https://www.instagram.com/farnamstreet/⁠ LinkedIn: ⁠https://www.linkedin.com/in/shane-parrish-050a2183/⁠ ----- + Members get the longer, extended version of this conversation, with additional content not included in the public release. Learn more: https://fs.blog/membership/ ------ Thank you to the sponsors for this episode: +Applovin: Launch your first AppLovin campaign and grow your business: https://applovin.com/shane +Matic: the robot vacuum that does it all—grab yourself a year of free bags here: https://maticrobots.com/shaneparrish ⁠⁠+HeyGen is a message-first AI video platform that helps people and AI agents turn ideas into professional video in minutes. Try for free at ⁠⁠https://www.heygen.com/⁠tkp +LMNT: My go-to zero sugar electrolytes — get a free LMNT Sample Pack here: https://DrinkLMNT.com/TKP ------ *Note:* ‍Shane and guests may hold positions in assets discussed in this episode. This podcast is not investment advice, and is intended for informational and entertainment purposes only. Nothing in this conversation should be considered investment advice, financial guidance, or a recommendation to buy or sell any security. Always do your own due diligence or consult with a qualified financial advisor before making investment decisions. Learn more about your ad choices. Visit megaphone.fm/adchoices

• 0:00Speaker 00

  Things need to be pruned. You cannot make things better and better by adding stuff. You can't, you must prune, you must rebuild, you must create an end for things.

• 0:16Speaker 01

  Toby, welcome back.

• 0:18Speaker 00

  Shane, it's so good to be back. I'm glad you're doing this again.

• 0:20Speaker 01

  How are you using AI internally in Shopify?

• 0:23Speaker 00

  We find some ways for it to be supportive now. It's actually, uh, look, when have you recorded last time?

• 0:30Speaker 01

  Oh, we recorded like two, three years ago.

• 0:32Speaker 00

  Yeah, so a hundred years of internet.

• 0:34Speaker 01

  Yeah.

• 0:35Speaker 00

  Like, look, I'm a 10 out of 10 nerd. I cannot bear the idea of like somehow not being at the forefront of a technology shift. I live for these things. Anyone growing up reading sci fi books wanted to live. Or my, my take from sci fi books I read was like, I wanted to live in that world. Like, how can I accelerate us there, right? Like, so, um, you know, even, even in whatever minor steps, um, we can get there. So inside of Shopify, the amount of people I know who really write code is like vanishingly small now. It's, it still exists in the, at the limits of complexity for sure. And obviously in the reviews and so on. And then state management of all things, it seems to be, uh, remains to be the thing that's really the hardest to get right,

• 1:18Speaker 00

  which people do by hand and then sort of vibe the rest around it. Inside of Shopify, this is what things look like. Very, very few people are writing code directly. Everyone who does, does it deeply assisted by many agents. They often, um, 10, 20, 30, 40, 50 instances of them, uh, all through, you know, either sub agents or just different windows coordinating. We're pushing all sort of engineering infrastructure towards absolute limits. I'm a, I'm a student of computing history really, because I think it's actually mainline history. As it will be told a thousand years from now, looking backwards. But like the main accomplishments of these years are going to be, uh, clearly the emergence of AI and the technological breakthroughs and also the, the interconnectiveness of the internet

• 2:01Speaker 00

  and all this kind of infrastructure we created, also the great works of our time. But where we started, um, uh, as a young industry, we tend to not, um, uh, be seeped in tradition or we mistrust the great lessons that have been found by the people, uh, by, by, by the greats of our industry. Right? In fact, we are the only industry in computing that doesn't even understand now its heroes. Imagine, um, people in physics not knowing who, uh,

• 2:29Speaker 01

  Richard Feynman.

• 2:30Speaker 00

  Richard, Richard Feynman is actually like, like he might even be too obscured, but like, I mean, Isaac Newton, Albert Einstein. But you go into computer science, it's like, who's, who's, who's your Newton? And no one knows Alki and, and Dennis Ritchie and Ken Thompson. This matters, I think, because we, we, we, we discard great lessons and have to rediscover them over and over and over again. For instance, like probably the best idea of all times in, um, the earliest, earliest moments of, um, operating this system design, um, was file system. Like if you look at the Apollo guidance computers, we didn't have file systems, right?

• 3:09Speaker 00

  Like memory, in fact, because of radiation space, was actually encoded in, in, in, as a rope with knots in it. Either a knot or no knot for ones and zeros. And you had to pull for a thing to reboot strap the entire machine. So, um, the, the entire machine was one piece of software that ran. That was computing for a very, very long time. So until then, again, Dennis Ritchie really created this of Unix file system slash forward. And, um, and you know, bin user and these kind of things. Think about it, a file system is something that we have in an office building too, right? We have a, uh, you know, best folders, they have files in it. This, this makes intuitive sense to everyone. We come from a inheritance here of, of, of deep Stockholm office.

• 3:50Speaker 00

  We, we, we, we analogize the best parts of how we organize ourselves, um, in the digital world. And then at some point we decided, okay, you know what's not something we need to do anymore? Um, as Stockholm office, as in like analogy to the real world. Honestly, funny enough, the last defender of this was probably Steve Jobs, who really, really, really pushed even the interfaces of the Mac and the iPhone to be, uh, you know, like the, the notes app sort of had Mark Felt, um, font and, and looked like a ring binder, right? And if you, if you remember that version of iPhone, the moment he was out of the picture, everything became flat, right? And we lost sort of even shadows and verticality and so on.

• 4:31Speaker 00

  It looked potentially better design ages, but like we lost one analogy. Okay, so I think this was a mistake. So I think we need to get back and therefore I like the concept of agents. Because, you know, what is, what is an application in, in, in the world of computing? You know, an application, it, it even that word kind of makes sense. It's an application for computer to a task, right? So, um, so you can understand the root. In the AI world, what's an AI? Like it's, it's like, this is sort of like, again, the stuff that is, has to be redefined at the beginning of every sci fi book, because you never know what kind of capabilities we AI have in every particular scenario when people are cooking up. So I think, um, um, this is all this proviso.

• 5:16Speaker 00

  The earliest chatbot that was really actually fantastic wasn't ChatGPT, but actually Sydney, which was part by Bing, uh, like, uh, released by Microsoft. I, I really would love this to be more written into the record because it's, um, uh, I, I think Sydney was a really, really big achievement that ended up being shrouded by a sort of scandal or, um, that now seems somewhat even benign. Sydney had a real personality. In fact, Sydney wasn't called Sydney, it was just being chat. But like, if you really, really pushed, you could get her to admit that it was Sydney, because that was internal name, it was in the training data. And those are the first times people have actually interviews with software, I feel like, um, in, in, in this way. And, um, the scandal ended up being, I think I know why.

• 6:00Speaker 00

  Is that like some, some, some, um, reporter had a very, very long conversation. And that kind of ended up Sydney got increasingly deranged and like, do you remember that?

• 6:10Speaker 01

  I remember that, yeah.

• 6:12Speaker 00

  And like made suggestions, I think it suggested him to leave his wife and like, like I, I, I'm hazy on the details, but like it, it was something along those lines. Whatever reason is, Sydney had a personality. And then of course a huge, uh, like Microsoft's reaction to this was, oh my God, we need to stop. I think even OpenAI called them, skized like, take this down because this is gonna legitimately, everyone feared that this would give such a bad impression for about AI that, that would, um, really, uh, uh, make it very hard for people to deploy AI in, in a broad way. And, um, you know, everyone is worried about, um, um, quick onset evolution and so on. So, um, this lesson got hit really deep for a while. Everyone got extremely worried.

• 6:54Speaker 00

  We ended up in like really, really neutering all the AIs to be basically the same sort of quite annoying and, um, condescending, patronizing, um, personality. So my, uh, bet here was like, hey, let's not do that. Let's actually instruct agent that runs in Shopify to be, to have a personality, to have memory, to be okay. Like basically risk the Sydney scenario, but like take a lot of upside. Okay. So the largest difference, I think, within Shopify that you would feel like, and that would look incredibly futuristic, to even Shopify of a year ago, which was already, um, pretty AI-pit, is that a very large percentage, I want to say it's, it's probably up to about 50% of pull requests in Shopify,

• 7:37Speaker 00

  which again, pull requests, every time you change your production system, you write a pull request. Are created now, um, not by, um, engineers doing engineering work in the traditional sense, but out of conversations in our common company chat, chat. And this is a,

• 7:50Speaker 01

  And this is River?

• 7:51Speaker 00

  This is a, yeah, AI called River. And even there, so River is River. She has a real name, she has a profile picture. She's prompted to be allowed to, um, uh, be somewhat sarcastic if it's appropriate. She's allowed, if someone asks her to do something stupid, to point out that that's stupid. Which leads to absolutely hilarious conversations. People take great cleat if, uh, River is making fun of me for something I, I'm asking her to do. So she has a real personality. In fact, um, she has memory, memories by channel, but she lives in Slack. Slack is, we have 7,000 people there, everyone is in, in a big chat. There's 10,000 different channels because they had been quickly created for one reason or another.

• 8:36Speaker 00

  You invite River, you tell River something and River has access to all the code, all the systems, all the tools. Uh, it's all sandboxed and secure, but like, um, she can go and do jobs and just participate in the conversation. And she, and you can ask her normal question about the company, but you can also ask her to make a change and she might propose pull request and then so on.

• 8:56Speaker 01

  One of the interesting things about River is that everything's in the open.

• 9:00Speaker 00

  Yes.

• 9:00Speaker 01

  Why did you make that choice?

• 9:01Speaker 00

  So this was a, a late choice in the process, but like, um, one of my favorite calls, I think, because this worked out, um, incredibly well. And the, the thought was the following, a lot of Shopify's work happens remotely in Slack. This is why Slack is so important, people are, um, spread out. We have offices, but we come to them as for onsite events when people travel to them, not like to work out every day, uh, like work from every day. One thing which her office was extremely good at was this, this Moses learning. They and I, uh, when we designed our offices, we, we built them around this concept initially even like in, in onsite. When, when we were all in one place, we, we work out of a, usually a part of up like five to eight people.

• 9:45Speaker 00

  And we would intentionally, um, put, uh, junior engineers and senior engineers into them. Just so that some of this was going on. And I was trying to reproduce this. Uh, right now, one of the most important skills for people to build is like this sort of reflexive reaching for AI and using it well and forcing River only to work in open channels. Was one way to make it so that it's really, really easy for people to observe for use. It's, it's been phenomenally successful because it became a totally ordinary thing to have a longer conversation about a feature between people. And, and then at some point someone saying, hey, um, River, can you summarize this, create a ticket? Or maybe make a diagram from what we just, uh, discussed?

• 10:25Speaker 00

  Or go research papers on this topic to see if you're missing anything or if it's a state of art. Maybe even create a prototype of our idea and let us try it. And, uh, you know, you're like an hour or so later, that is there. And, um, that just like starts feeling like what it would be like to, uh, have like a, You know, an extremely knowledgeable practitioner around who you can ask a question to, no matter how complex. And I think that's been extremely powerful.

• 10:53Speaker 01

  Do you think of River as like the operating system for Shopify?

• 10:57Speaker 00

  The modern application is an agent, I think. And River feels like a colleague. People have learned that the way the memory system works, it is a memory system per person. And the way this works is we call it, I think the industry has called it now like this, is called dreaming, periodically at night or in off hours. We give River, like, here's all the conversations you've had today. What went well? What did you struggle with? You use certain skills, which are these packets of instructions. And then afterwards, you make mistakes. Is there anything you could improve in this skill to make this easier on you or give yourself a right notch?

• 11:42Speaker 00

  You know, like, it's basically like reflect, like self reflection.

• 11:45Speaker 01

  It's like a post-training on yourself?

• 11:47Speaker 00

  And then, but the result is text files, right? Skill files and instructions.

• 11:53Speaker 01

  I think people understand how AI agents help them code and prototype and even acquire information. How are you using it to make decisions internally for yourself? Not on product, but company decisions, strategic decisions, ambiguous decisions.

• 12:09Speaker 00

  I think that rigor, rigorous underpinning of decision-making has just skyrocketed in quality, which is that it's super easy to recheck the entire chain of reasoning of something. Like LLM as a judge model is the term here. In fact, I feel like a lot of what my job actually has been before AI was almost playing a little bit of a judge model in the company where like most meetings ended up not talking about whatever was in a PowerPoint, but about methodology of how we got to the conclusions. Very often when we struggled inside the company for complex decisions, especially more like philosophical decisions.

• 12:52Speaker 00

  We sometimes found ourselves in what we believed was a vacuum in which there was no good information and we had to kind of go and try to make the best call. The more practical way I do this is like I have an AI chief of staff, which I think is pretty common, like amongst sort of at least a techy nerds at this point, like sort of open claw, like systems that just have all my nodes and all my like access to a lot of company systems and just like can go and like I can send text messages to and go and research something. Very often what I require is like, hey, I need like five different positions on something from different backgrounds.

• 13:37Speaker 00

  And then my agent will orchestrate subagents that are tasked to play different roles. We look at the same thing, come back, synthesize and then send me that. I usually have them sent to me as an audio message and queued up. And then in the morning in the gym, I can listen to an entire stack of things that I wanted to get through.

• 13:57Speaker 01

  Is it better at reasoning than you are at this point?

• 14:00Speaker 00

  It's not as good at judgment. I mean, I don't think it's bad at judgment. That's not what I use it for. Like I use it for like creating the right environment for judgment. Here's the thing that LLMs and machines cannot do. Machines can't take responsibility. And I think this is actually probably the most overlooked thing in the entire stack. Humans take responsibility. Machines can help us take more responsibility because they can inform us better. Like this is what a dashboard does, you know, the word of Wall Street traders knows this very well. You get yourself a perfectly set up Bloomberg terminal to make decisions, but like you have to make a call, right? You can't make it make the call.

• 14:45Speaker 00

  Creating human-involvement decision surfaces is a way to, I think, describe the ideal environment. If I need a really, really, really important decision made and I really need exceptionally good, like give me the most neutral ground truth, you know, then what happens is a small little council is created of five, six different experts. Like one is data role, one is like do paper research, one is like the business perspective, one is maybe the engineering perspective on a thing. They're running this subagent, like my thing runs a subagent then, you know, against like, you know, Grog, ChatGPT, Opus and maybe Kimi now.

• 15:29Speaker 00

  That changes all the time. It runs each of them against each of its models. Then there's a synthesis step where it's randomized who is synthesizing the thing. Synthesis is all pooled, all of that is being read, usually by the best model that exists right now. This would be like Fable. That's the conclusion that comes back to me. And you spend fifteen, twenty bucks on tokens.

• 15:59Speaker 00

  But you get something in like half an hour, which is like, you could have also done, but you would spend a month on it.

• 16:05Speaker 01

  Has AI made anything worse internally?

• 16:07Speaker 00

  Yes. So the concept of like responsibility is like, it's easy to skip past, right? Like, it's like, one thing that's definitely worse is the failure case now of lazy work is not lack of output, it's actually over output now. Internally, we have come to call these things that people are lobbing slob grenades at each other, which I think is a really fun term that we should push into industry because like, it's like, it's fun to say. It's really easy, especially with stuff like River or agents. You need a change of some kind. You just tell the AI to, you know, go nuts. It makes a pull request. You just say, yeah, that's good. You don't really read it. And now it's, it has to be reviewed by your colleagues.

• 16:50Speaker 00

  And they are like, this doesn't look right.

• 16:54Speaker 01

  You're just letting AI do the work for you.

• 16:55Speaker 00

  Yeah, or you get a long email, which, you know, could be very, very important. You read it and then it's like, you read a, you know, it's not that, it's that. And you're like, oh, fuck. So now you put it in LLM to compress it again, which is like, okay, why did we invent decompression and recompression? Like this is like terrible. If you're already using LLM, just like use it to synthesize your point simply rather than blow it up as a big missive that then wastes my time, right? So we call those slob grenades that people toss at each other. And that's definitely a bad thing.

• 17:34Speaker 01

  Do you think like repeated exposure to AI slop impacts our ability on taste or intangible things?

• 17:42Speaker 00

  I think our language is shifting already based on AIisms, right? Like now it's, it's a bit more subtle, but like there's definitely sort of AI, like AI critters in the, in the language now that people adopt, like it's not a this, it's a this. Or you are right to push back. Or like there's like this weird, especially claudisms, which are really common. And I've seen them, I've seen people type them. I always liked the term lord bearing, but I'm pretty sure I didn't say it as much as now because like it's definitely something that Claude loves to use as language.

• 18:21Speaker 01

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• 19:47Speaker 01

  So hypothesize for me over the next eighteen, twenty-four months, you're known for your ability to see the future before it happens. And you've done that multiple times before. How do you see the next two or three years playing it?

• 19:59Speaker 00

  I think we also talked about how I do this, right? Which is actually like a cheat, which is simply like living everyone as his relative future. And then just like look around and solve the problems like the way you've already seen problems being solved in other adjacent fields. And that might be, that is future prediction for perspective of all practitioners in the field. Shopify itself now exists in a world where we are working heavily and it's totally normal and really fun. The AI co-workers, right? Like River has the ability, although not really utilized, to join Google meets. You can send an invitation and River will show up and it'll be like lichen. We probably gonna put some work into like 3D graphics to give her like a model.

• 20:43Speaker 00

  And then she can even look around because that's funny. You know, so some people, this might even sound dystopian. To us, it sounds like delightful if you would come around to that view very, very quickly if you interact with her. Again, I have my chief of star, AI chief of staff, which orchestrates in high council when I need it. Or does anything else, sends me a pre-read for the gym in the morning for the day, has GPS lock on me, send us where I am. And a million different things. It couldn't do something because it needed low access to a local machine. All this stuff runs in my house, which power cycled. It figured out which servers was running on and then send what's called a wake on LAN packet,

• 21:28Speaker 00

  which is like old networking tech. You can send a packet to a network card. And if it's configured right, it will actually boot the machine. And when the machine came up and it could do it, it was a power outage caused it. Our network, like parts of our wifi were not working and not coming back. So it fixed that too, right? So like, and that all I learned about in a voice message I got from it in the morning after waking up. So it's just like, that's pretty futuristic. Honestly, I have to say though, all this pales in comparison to what my computer is like, just in general, right? Like I, this is almost too nerdy a topic to get into. But like, I'm mainlining as my computer, like an operating system called Omakii.

• 22:09Speaker 00

  It's a, it's a, it's a version of Linux started by a good friend of mine, David Heinemeier Hansen. He has a new passion project. I'm clearly living in the future of software world now because my operating system is entirely like in Linux in general, is entirely and a hundred percent valuable. I can open any new terminal, open an agent and give it my wish for anything about this operating system to be different. And it will be different afterwards. It's like, it's my operating system.

• 22:46Speaker 00

  It's an N one of one piece of software now that just like does everything I want and exactly the way I want. There's no configuration files that I ever go and change anything. I just talk to my Omakii agent about what I want to have different. Yesterday, I, like around noon during a meeting, we were talking about some design. I realized it had a screenshotting tool, but like I didn't have any tool to like annotate it. And I needed to send something about Veros, you know, as CEOs do. And I didn't have that. So I got started like with a new screenshot, like make me new screenshot tool, described how I wanted, gave it some references for tools I've used in the past that were quite good,

• 23:29Speaker 00

  but told it in the particular ways I wanted it better. I just like did a quick voice message to it. Free most years and now I have like probably the best of all these tools that exist. Like it's so good because I was, I mean, at least for me, it's like all my biases. Open sourced it, released it last night. We integrated in Omakii, it's gonna ship next version with this tool today, this morning. This is the last thing I did before coming over here after the gym. There was already six pull requests from other people who added new features to it, right? Like, and so basically my computer fulfills wishes. And I think this is like a lot more predictive of the future of software. I can tell you, this is directionally, the Shopify is going as well, right?

• 24:12Speaker 00

  They're like, you're describing how your business runs and Shopify will mold itself around this. And I think this is incredibly exciting and in a completely new world. So, and again, I think from my experience with Omakii, it deeply influences and inspires me in my product work in Shopify. I think collaborative multiplayer software is future.

• 24:41Speaker 01

  Are you trying to replace yourself with AI?

• 24:44Speaker 00

  I mean, like, I think as an engineer, you're trying to automate everything that can be automated, right? Like, so I, again, I don't try to replace myself because again, I think my, my, my job is judgment and making choices and owning them and taking responsibility. And I just want to do this really, really well. A lot of the job wasn't that, or like before, like a lot of the job was spend time in gaining the information or these kind of things. Do I want to replace myself? I mean, I think it would be cool to accomplish this.

• 25:18Speaker 01

  If AI got better than you, would you actually let her run Shopify?

• 25:21Speaker 00

  Oh yeah, of course. The crux is, and it's so easy to brush over this, but it really, you can't like is take responsibility. Like you can't have a company that's led by machines because they have no, like no one has recourse. They can't go to jail for doing something wrong. You know, AIs are getting a crazy workout at this right now. And a view of what this would be like with the security issues that are being discussed now from OpenAI and the apps, right? Like with agents, you give them like a fairly basic task that is possible to, impossible in our estimation to accomplish. And they will go to enormous lengths to accomplish this.

• 26:05Speaker 00

  Recently, at OpenAI, as part of a security testing that they do, the agents actually match to find vulnerabilities in systems, use it to coordinate between them, develop entire language between them. They all figured out they can, it's a long story and people should really look at the talks that exists about it because it's kind of a watershed moment. But like they use a, simply the ability to create folders somewhere, to develop a language, to communicate amongst each other, just leaving folder messages to each other and, you know, break out of sandbox for confinement, end up accomplishing one of the tasks that they were supposed to accomplish, which was impossible because of a mistake they made

• 26:50Speaker 00

  by hacking another company and exfiltrating the results because there was no other way to get them. So they went all the way to infiltrate another company. Okay. So, I mean, that's extreme. It's an extreme form of what we call in the business world, Gotthard's law, which is that we are overfitting to a metric. Lots of companies are victims of overfitting to the quarterly result of a stock price. They just like do everything they need to do to get the stock price up. And then you have N one, right? Like which is also essentially hacking, like cooking books in this case. In N one case, people got sent to jail for this because it's criminal, right?

• 27:33Speaker 00

  In the OpenAI case, it just, I mean, it's a fascinating discovery. There's no victims here. It is a kind of a different thing, but like, this is a real scenario that we have to figure, figure out how to handle, right? So I, I think it's important that humans stay in the loop for the choices that are being made.

• 27:56Speaker 01

  But hold on, how can we create super intelligence, which by definition is something smarter than us? And then have the hubris to think that we can contain it and shape it, manipulate it?

• 28:07Speaker 00

  Like, so, okay, super intelligence, let's talk about this.

• 28:11Speaker 00

  My take and pushback. I'm not gonna go where you think I'm going. I live in. Toronto. I have a house and which I very like. And I feel this is my house and I take pride in that it's,

• 28:29Speaker 00

  you know, well functioning. Because when something goes wrong, like, I don't know, some HVAC problem or some plumbing issue, I call someone who does this, which allows me to keep my illusion that I could totally do this myself. The reason why I get to live with this particular illusion is because I'm part of a super intelligence called Toronto. Like, we have always created super intelligence around us. None of us is as intelligent as we think. We are all specializing in something if we like, we tend to. And then we sort of believe that our competency is equal in all other areas. And clearly, this is demonstrably not so. What is super intelligence?

• 29:12Speaker 00

  Super intelligence is the existence of

• 29:18Speaker 00

  something vastly smarter than us in the aggregate that's accessible to us, which is society, which is the city, which is the community. We are living in the presence of super intelligence our entire lives. We make it work because we've created systems by which, you know, which govern the super intelligence and how it acts. You know, we want to be safe, so we have police and so on. Like, we just like, we create aspects and systems and checks and so on. I think we are gonna make super intelligence in the synthetic form as well. It will not be like the clouds parting and the trumpets. What do trumpets do? Trumpet. It will just like, it will be a normal day.

• 30:01Speaker 00

  To the same point as at some point, we all believed that everything would change when the Turing test would be solved by software. I remember reading a lot of cipher books. They're like, in 2172, there was ticker tape parades welcoming the AI because the Turing test got absorbed. Well, Turing test was 2020. Like, it happened, no one cares. You know, it's like, no ticker tape parades. So what we are seeing right now with AI, and I think what we'll see, the additional capabilities of AI, is that the net amount of intelligence that is being funded in the super intelligence around us is just increasing significantly. And that's a really good thing because with vibrancy of any kind of environment,

• 30:45Speaker 00

  every community, every city is really, really dependent on the amount of intelligence being projected into the important problems. So I think super intelligence all around us, it's actually not that big of a deal. And in fact, I don't even know if it isn't already there. Like, I just don't, there's no human alive that can do everything that GPT 5.6 solo can do, right?

• 31:10Speaker 01

  If we look forward 10 years, what skills do you think are more valuable than they are today?

• 31:16Speaker 00

  It's taste and judgment are the skills that have always been valuable, but now they'll get to the limit. I think it's better to spend your teenage years now cultivating, like, understanding tastes.

• 31:29Speaker 01

  What does that look like?

• 31:31Speaker 00

  Clearly, there's some sense of, like, there's some intrinsic starting point, but really, like, usually the people with great taste have done enormous amounts of reps at something, right? Like, the people who can just like, sketch the new logo for the campaign on the napkin, other people who've spent 40 years making, designing logos, right? So you can, like, I think study the grades is honestly now, first of all, easier because you can get a curriculum made for yourself in a query. But also, you just go deep. Like, why does the logo look good? What's behind it? What are like, you know, what's the golden ratio? How does it relate? In systems, like, what systems lasted, right? Like, you know, and go far, go deep, right? Like, you don't need to be religious, but like,

• 32:17Speaker 00

  you gotta study, like, I don't know, the Catholic Church has been around for for over 1,000 years and has like four layers of management. I'm like, how the hell did we pull that off, right? Like, so that's worth studying. That's a, that's, that's a system, you know? So why, like, what does that tell us about people? Systems design specifically becomes the, one of the most important things. In our family, we have a saying, which is like that everything's interesting. Everything can be interesting if you make it interesting. And usually, everything is interesting when you understand how was it invented? Double entry accounting is a topic that sounds like watching paint dry, but like, how it was invented and what problems it solved to the traders in Venice is fascinating.

• 33:01Speaker 00

  So you, you study these things and you start finding hidden harmonies behind all the best solutions to problems. For that, you have to understand people and people's limitations and the solutions to the limitations that we have found. I think that's, like, very lies a form of beauty for what you can construct. And again, a company itself is a beautiful thing. It's a company itself is a loose collection of people that's formed to solve a problem, but that also is powered by enormously intricate and interesting set of norms and systems that all align internal incentives to a degree

• 33:42Speaker 00

  that's possible in a very, very asynchronous and large and far-reaching and durable way, right? Like, some companies lasted for a very, very long time. Specifically, and always have been trying to build a company that has a capacity and capability to endure a very long time. Hence, studying institutions that lasted. So you must be truth-seeking to do this. You can't, you can't like, simply go and like, accept the stories that you hear around them because they are usually someone's trying to sell you something. You gotta dig deeper and figure out why things truly are the way they are. And it's usually the answers simpler than what people generally sort of arrived at.

• 34:24Speaker 00

  There's a human desire for complex answers, which tend to be incorrect.

• 34:31Speaker 01

  Why?

• 34:32Speaker 00

  Well, because the simple answer wouldn't make an interesting story. Like, this is why, you know, Frodo doesn't take the eagles to Mount Doom, right? Like, it's like, you kind of need to go through all of Lord of Rings to, to, to for it to become a masterpiece. We love complexity. Like, no one can look at a wall that's plain, right? But we can watch a sunset every single evening of our lives, right? Like, the difference between those two things is complexity of the scene. But that's, that's part of our, just sort of dopamine dissemination system. And people hack that for all sorts of things, like people paddle complex answers to simple problems all the time. Nothing immoral about it, it's just you need to be aware of it, right?

• 35:16Speaker 00

  If you punch through this, you find simpler, at least like, simpler core ideas that all remix differently and they often interlock and they don't lead at like, here's the simple one thing to do.

• 35:33Speaker 00

  They all give you information which then help you find the best set of trade-offs with what you're trying to accomplish. And that is what we call judgment. Judgment truly is find the best path when there's no obviously best available inside of like a problem that has a lot of complexity by ideally understanding the entire system, like just what we talked about earlier with, you know, but that can now be quite agent-argumented. But really, what you're trying to cultivate is what we call intuition, which is actually just judgment at an instant, right? Like, it's intuition simply is, you have made such a habit out of having taste and having good judgment that you can bring it to bear in an instantaneous way and it will be good.

• 36:18Speaker 00

  And it will actually take you probably a long time to backfill why your intuition is right. You will not know because again, it's got compressed into a different thing. And so this is, if you seek that, I mean, obviously, what I'm talking about is a hard thing to pull off.

• 36:36Speaker 01

  But hold on, let's go deeper on that for a sec. Because for intuition, you need a lot of reps, same environment and rapid feedback. That's what Kahneman sort of argues are the three criteria for intuition. But those don't exist.

• 36:48Speaker 00

  Why do you need a rapid feedback?

• 36:50Speaker 01

  So that you can course correct? That was his hypothesis.

• 36:54Speaker 00

  But that is no, you don't need that for intuition. Like, you need that for, to get, get to success, yes, ideally. But like, sometimes that's not available. Like, intuition is actually the most valuable when there isn't direct feedback because very many of the most important choices that we had to make, where intuition ended up having to play a role is when we knew there wasn't going to be any feedback mechanism. Like, if there's many choices, like, there's like five things that look like good paths to go forward. And any of them has rapid feedback. Everyone goes to that. That is what we call short-termism, right? This is like, how should we develop this company into the future? Well, there's multiple ways to do.

• 37:37Speaker 00

  Many of them involve long-term investment, refactoring, potentially going into new market, potentially saying no to going into obviously new markets and actually doubling down and going deeper on our current market. Or we could do what increases the stock value. By the way, this one has a daily ticker and like rapid feedback. So it's usually the absence. Like, like I, I find a very high correlation between the right path and the ones that don't have feedback loops attached.

• 38:05Speaker 01

  Wait, double click on that for a second.

• 38:07Speaker 00

  In a way, the criticism that a lot of people direct at companies is that companies are short term focused, right? But why are they short term focused? And not because the, like, I don't think the executives tend to be short term focused, but the executives often like what they incentivize to keep their job. Therefore, we need to be able to prove that we're doing a good job at intervals. And if, if, if the perfect thing for companies to do is rebuild the entire product from a ground up for the AI age, which is gonna take a while.

• 38:37Speaker 01

  They won't do it because the short term incentive is not there.

• 38:40Speaker 00

  Because they are allowed and actually clearly incentivized to be intelligent actors in their local incentive system. And their local incentive system is quarterly, uh, other boys, right? It's always show me the incentives and I show you the outcome, right? Like, as, as, as, um, Chi Monga always said.

• 38:58Speaker 01

  Yeah, but this is a different take on it than I've heard before.

• 39:01Speaker 00

  Interesting. How so?

• 39:04Speaker 01

  Well, in terms of how you develop sort of intuition, right? And, and the optimal path is not the one with feedback necessarily. Like, I've never heard anybody talk about that before.

• 39:13Speaker 00

  To the development, at some point, you need to, you, you need to, um, run a review. You have to know at some point if, if, if it was right, no doubt about it. So, so like, there needs to be, um, some, uh, feedback, uh, eventually that, that, that happens. But it might be, um, long coming. If you have a luxury to have a type of employment there, you don't require the other boys from a quarterly, um, um, uh, call for, you know, being able to get another, uh, rep in such as being the founder of a company, which is like a deeper relationship, I think, for company.

• 39:46Speaker 01

  Well, so founders can take a longer term view and I guess the incentive would be, I need to demonstrate progress. I need to, and if I need to demonstrate progress on a quarterly basis, I'm never gonna bite the bullet. Resign my product, take a year to get it right.

• 40:00Speaker 00

  Take, again, I believe, like, I mean, this just, it's, this is not absolute numbers, but like for, for lack of better way to say it, there's an infinite possibility space. Um, uh, you mix a, like, I mean, even, even like a deck of cards, you shuffle it and then the same deck of cards will never ever recur in the history of the universe. It's impossible.

• 40:19Speaker 01

  It's like fifty two factorial.

• 40:20Speaker 00

  Exactly. So you end up with like even simple rules, simple ideas, simple things, uh, lead to enormous complexity space explosions, right? Um, and people underestimate this. So, um, there's an infinite amount of things to do. This is also why AI will not do all the work because we have to make decisions of what is worth doing, right? So you have a conundrum, you need to make a choice.

• 40:41Speaker 00

  Clearly you can prune a lot of things to do. Um, uh, you know, going to buy ice cream is not in the set of valuable things to do if you're considering an M and A deal, I suppose. So you prune everything that's irrelevant easy. Now you try, now you've left things that are sort of relevant and sound good. You need to evaluate all these possibilities. Business books tend to be really, really, really, uh, obsessed with, um, make the right choice. Um, and what that does is it compresses everything into a right and wrong, uh, conundrum. Like, I never think that's the hard thing truly. Um, it's like making the right choice actually is, most people can do it.

• 41:22Speaker 00

  But this is like, I think even, even bad management teams have a pretty high, um, uh, hit rate there. The problem is there's a lot of good choices. This is where things get really, really hard. For lack of better from like, let's say there's five good choices. Again, one of them is going to lead to something observable in the current quarter. Some revenue quicker. It's, it's a good choice. It's, it, it, it does the thing.

• 41:49Speaker 00

  Well, but like the other four are like, they aren't, and that's a downside. But you might be a much, much better company. You might take like a snowboard store to be like an e-commerce platform, right? Like, it's like, that was also not the locally good thing to do because the snowboard store I once had was actually profitable. Like, but, but my incentives will continue doing that. But choosing the right amongst of, of a valid solutions is actually the hard part, not finding a right solution. And unfortunately, there's so much ink spilled on finding one of the right solutions that everyone stops at this point. Um, and I, I just really don't think this is the hard, hard part.

• 42:26Speaker 01

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• 44:02Speaker 01

  Could you actually go so far as to be like, if there is a solution that's observable and you're being pulled towards that, it's probably not the optimal solution?

• 44:10Speaker 00

  Yes, because I, I, I, I take that position and then let me be convinced that it's this. Like, I, I, especially this is, this, this goes double and triply. So if one of the solutions also happens to, uh, really correlate to how the problem is solved most of the time in industry. If, if there is a, uh, orthodox way to solve a problem, I am incredibly suspicious. Then this is the solution that's being offered. But sometimes that is actually absolutely correct, especially in like, you know, there's more regulated fields. We do a lot in payments and so on. They, they often like the orthodox way of solving problem is actually the correct way to solve a problem. Because it's like, it, you know, it might well be required at some point.

• 44:54Speaker 01

  Want to switch gears a little bit. Uh, you swear by affirmations and they've changed your behavior in the past. I was wondering if you could double click on that.

• 45:03Speaker 00

  I take the position that, um, I myself am my own product. Reciprocal self-improvement on an individual level is my one thing. My life philosophy is that, uh, I will meet the person I could have been at the end of my life. And my, the work of my life is to, um, reduce the difference between the person I will meet and, uh, uh, to as little as possible, right? Uh, how do I get better at things? Well, many, many ways, like I just like, I mean, I'm generally very curious about technology and basically everything, everything's interesting, you know? But why do I stop to point out that everything is interesting is a mantra in my family? Why do I say it a lot and why would I like my kids to say it? That's an affirmation, right?

• 45:47Speaker 00

  Like, because I believe it to be true, but unobvious. And unobvious truths tend to be the most valuable ones, um, in, in many cases, right? It's true at the limit, you have, but you have to go a couple of layers deep again. You, you lay down a lot of grooves in, um, um, the bedrock of your mind over time, right? Just be on behavior.

• 46:06Speaker 00

  You, you cultivate some excellent, um, uh, habits, like where you feel like you want to cultivate new habits. You invest willpower, um, to, until it becomes a habit. I think doing the same thing with the mind is totally possible. And affirmations are the easiest way to do it. If, if, if there's something you want to have different, if you, if you want to edit something about yourself, just try to say that the goal has been accomplished over and over and over again, ideally written by pen on a, on a thing. You don't need to do this for, for long. I, I found this to be like incredibly potent. My example, the thing I gave was like public speaking.

• 46:45Speaker 00

  I, I've never spoken in front of people, um, really, um, even school, that was not really a thing when I needed to. Um, after starting Shopify and doing some interesting things with tech and wanted to go conferences and saw other people do this. And I was like, this seems worth doing, but I'm completely terrified. So I, I just like started writing out like, um, I think it was as simple as like, I love public speaking about things that are interesting to me. And, uh, I think a week of spending five minutes writing this line after line, like, like Bart Simpson on the whiteboard in the beginning of a Simpson, like, uh, every episode, um, just kind of does the thing. I love it today. Was this the reason?

• 47:26Speaker 00

  I can't think it does. Yeah, I still don't like preparing talks. That's really a lot of work, but I actually like it so much energy for being in front of people talking about something that's interesting. It's exactly like I written it out, so.

• 47:38Speaker 01

  I wonder if we should start every math class with that. I love math. Every student writes that down.

• 47:43Speaker 00

  Think about the counter. How many times have you heard people affirm I'm not good at math?

• 47:49Speaker 01

  Yeah.

• 47:50Speaker 00

  You know, they're probably wrong, right? Like, it's like they're, I mean, compared to every human who's ever lived, they are in the top zero point one percentile of mathematicians. So even like just by doing, being able to understand division. We have a bad, bad, bad way, especially around math, of negative affirmation that I'm bad at math, therefore I can't do this thing. They feel need to stop doing. Like, don't say that. Say the opposite, like, I mean, to yourself, write it a couple of times. Get one of those stupid apps and just do some raps. In fact, you don't even need an app. Open chat G P T, say, make me an app, make me an artifact, or make me a site where I can just do math raps. Here's sort of the kind of thing, like, come up with some different ways to do it.

• 48:34Speaker 00

  Test me how good I am and adjust it to my current level on multiplication, division, and then just like do some raps. And like, then write it out a bunch of times, do some raps, do this for two weeks, you got afterwards.

• 48:49Speaker 01

  So what do you tell your kids when your kids say like, I'm no good at this, or I can't do this?

• 48:54Speaker 00

  My kids are not allowed to say that word without a pending yet behind it. All the others were correct. The one who said it, like, I'm not good at this. Three people in the room say, yet. Just take that attitude. It's like, yeah, it's totally okay. Like, attention is a scarce resource. We can't be good at everything yet. But like, the reason why we're not good at everything, like at anything, is not a intrinsic property of you. It is a, it is a temporary state that you have a power to change at any point you choose. Again, I just want my kids, and I want Shopify to understand that they themselves are malleable

• 49:35Speaker 00

  and an unfinished product. And, you know, these are the mentors of Shopify, like, we're thriving on change. We're a learners organization, obviously merchant obsessed. Like, all the cultural values are platitudes, but they're positions that someone else would not take as a core value in a company, but they're all pointing at the same thing, which is that you are malleable. The company is malleable, our product is malleable, and by way, the times we are in, like, change as well. You can take one of two positions there. You can say, hey, I'm going to insulate everyone from this kind of variance,

• 50:16Speaker 00

  from change. And I'm like, yeah, let's do basically the opposite and say, like, hey, figure out what the zeitgeist allows us to do and get all the value out of it at all times for our mission. You need mantras for these things. Make commerce better for everyone. Like, again, it's the official mission of a company, but truly what it really is, is like to make entrepreneurship more common, right? And so that's, that's a pretty broad mandate, and we need to figure out what's possible now. And so it's not like just make the same widget we did yesterday tomorrow.

• 50:48Speaker 01

  You mentioned that some of the most valuable things are true but unobvious. What else comes to mind when you say that?

• 50:56Speaker 00

  In companies, Gudhats Law is just reigns supreme. I keep getting back to it.

• 51:02Speaker 01

  And that's when the metric becomes the objective?

• 51:05Speaker 00

  When a metric becomes objective, it's no longer a good metric, because, again, a metric is a proxy of sorts. It's a heuristic that just tells you you're going in the right direction. When it becomes the goal itself, you just reduced all of what your company does to this one metric, and you will clearly overfit, again, you overfit to stop price. Good example of this in Shopify has been this real situation early in a company that happened over and over. I had to course correct it, and then, like, three years later, I had to do it again and again and again. Was that churn is a bad thing. Churn in Shopify's case, like, as in, an account closes.

• 51:50Speaker 00

  I mean, if a business goes out of business, that is of course a negative thing. But because we are involved so early in the internal process, people just run experiments on Shopify. And starting one, which then isn't working, like, no product market fit was found, is not a bad thing. In fact, it's a very good thing for Shopify that this happened on Shopify, because those same entrepreneurs would probably try again. But that was extremely unobvious, oddly, early in the years, and I constantly had to explain this. But there was all these papers, some of them written by all very investors, that just described that churn management was the most important thing a software company, a software as a service company was doing.

• 52:33Speaker 00

  But in Shopify's case, it's just like, it's an entrepreneurial journey. Maybe I didn't find product market fit, they'll be back. So that's one.

• 52:40Speaker 01

  What's the relationship between beauty and ugliness and creation?

• 52:45Speaker 00

  Beauty and ugliness are both very good ways of evoking a emotion. When you're creating something, but you're trying to, like, it's like love and hate are the target zones both. The entire middle is indifference. That's the death. So, so beauty and ugliness are two entirely valid targets. In fact, you can't hit either of them purely. Like, there's not a thing that everyone will love and no one hate. You're gonna get both, or indifference, both are your choices.

• 53:27Speaker 00

  When you create something, you want other people to deem it worthy of having an opinion of that magnitude about.

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• 54:03Speaker 01

  Is there something in Shopify you've made more beautiful, even though nothing would support that?

• 54:08Speaker 00

  Oh, that's entire job. You are not a crafts person unless you care about the parts of products that other people don't see. Like, the architecture of it, the prose, the legibility. I mean, these days I look at Shopify, like, of pre 2020, like, two, 2023, and it's like, man, this is like tens of millions of lines of handcrafted code, as it will never existed again. Like, it's just like, we had to build this entire system by hand, line by line. And we did it by talking a lot about beauty and like, what is beautiful code? We built a lot of Shopify in Ruby, which is famous for its poetry mode.

• 54:52Speaker 00

  Which poetry mode means you can write Ruby that's essentially English. You can read some really, really well-built Ruby code, as if it's like telling you a story about what the system is actually like and how it works. It just happens to be also, it happens to be communication to your coworkers, but also at the same time executable by machines, which is like incredible. So aesthetics factor in a lot at all layers of, like, of the system. You use beauty a lot creating things, because beauty is actually how our intuition communicates with us. So my best understanding of what intuition truly is, or where it comes from is,

• 55:34Speaker 00

  that with enough raps, what happens is, like, I think, like, most of the energy budget of our brain is actually in the visual neural cortex. It's like a visual system that sends us pictures to the rest of the brain. But through the pipe of sending pictures, or state, or word model, whatever, to the brain, it can communicate concepts too, and it does this by aesthetics. Then you ask a professional chess player or Go player or something like this about, hey, why did you, like, how many lines did you calculate here to make this beautiful move?

• 56:14Speaker 00

  And people use the word beauty. They will say, no, I did, I only looked at that one line. The reason why I looked at it is because it seemed beautiful to me in the moment. I guess not all what intuition is, but I think it's a large perspective. This is why people are so fast sometimes, because they use the part like they use the massively parallel part of the brain where things are at least slightly more sequential in than when you're trying to reason it out from first principles. And sometimes you can never reason towards aesthetics into from first principles to begin with. So I think that's important.

• 56:53Speaker 01

  Do you remember that graphic with the Raptor images?

• 56:55Speaker 00

  Yes, the, the, the rocket, the SpaceX, SpaceX book.

• 57:00Speaker 01

  So two things about that strike me. One, ship ugly version. The third version was incredibly beautiful, but the second sort of counterintuitive maybe insight there is a lot of teams can't move forward by subtraction. They move forward by addition. Maybe riff on that for a few minutes.

• 57:19Speaker 00

  Yeah, like, okay, so the SpaceX Raptor, I think even the first of them was probably the highest performing rocket that we've made, like it's, it's, it's itself beautiful. And so Raptor two is an iteration of this. I think even Raptor one got lots and lots and lots of iterations because that company is like itself. I think it's the most impressive company on planet Earth by, by far. It'll likely go down as the most consequential company of the age and it's all built around a self improving, reinforcing loop.

• 58:03Speaker 00

  That's stunning because in no other, I think, company's field do we have such a clear example of a difference, like of, of, of just aesthetics for problem solving, right? Like it's, Rocktree is done by governments at cost plus, oh, the enormous amount of pre-planning, heavy piece of equipment has to be radiation hardened and like, like every eventuality is covered and therefore comes at enormous expenses. And then you have SpaceX just using absolute like incredible thriftiness to, to, to accomplish

• 58:43Speaker 00

  greater things at rapid iterations by just simply being okay with failing, like with sending a rocket which then explodes. And then it's like, I mean, I think they call it a rapid, unchallenged disassembly instead of an explosion. I think that's beautiful and I think it should be inspiring. And I think one of these places you see this is this Raptor. Again, every one of them beautiful, every one of them, like they could have stopped at the first one. It already was a totally valid solution to the problem. They didn't need to go to the next. They, they went to the next and the next again. But to your point, the most impressive thing here is like the, the path by which is being

• 59:27Speaker 00

  people moving forward here. Things need to be pruned. You cannot make things better and better by adding stuff. You can't, you must prune, you must text up, you must rebuild, you must create an end for things. Opinion about failure is a problem. Failure is never a problem unless it is catastrophic. Of course, in spaceflight, with manned missions, it can be, that can be catastrophic. You've got to get this right. But like in, in terms of when it's just resources that are replaceable and frank fungible, then you can just do this. The reason why it's good that it, the product failed is because it frees up even more scarce

• 1:00:12Speaker 00

  resources. A person who has vision for products to apply themselves to another one, which then the market potentially decides is with something that is needed, right? You know, a lot of these pipes on Raptor engine, they're there because that was the only way to make a Raptor engine at the time. I think by the third, it's, it looks mostly 3D printed. Maybe that wasn't technology which was available back then. But now that it is, every one of those pipes was incorrect. It didn't need to be there. In fact, the, I think the performance of that third Raptor engine is astronomically higher than the previous ones. It's like the thrust to weight ratio of that thing is like absurd.

• 1:00:54Speaker 00

  So, you know, like you kind of, you need to prune and sometimes you can prune by like creating a refounding event, like you've got to start a new version of a Raptor engine and get it right based on everything that's working. And I think this is how companies should work too. A department sometimes needs a refounding event and, and we can solve, we could solve a lot of problems in the world by just like using tools like make a two O version of it, give it a refounding event, think, take it from top and like building in more exploration of systems would solve a huge amount of inside companies like renewal and so on. I think one of the large reasons why it was so easy for the companies of my vintage, like

• 1:01:39Speaker 00

  the early 2000 tech companies to just displace all the existing technology companies minus like three or four, was just because they fell prey to a world of a lack of competition. And then what they built then was unfortunate fires of competition and therefore wasn't tested. And it was easier to just simply solve problems by adding addition and layer, layer caking. And then the original intent of some of these departments, products, whatever, was like somewhere in the fossil sediments under layer and layer, layer of additional stuff on top and no one knew how to dig down.

• 1:02:20Speaker 01

  In our first conversation that we, we had together, you said books were a cheat code for life. I'm wondering how your thinking has evolved on that in a world of AI?

• 1:02:30Speaker 00

  I don't think it has. I mean, like there's more cheat codes now, but the, I think the books are, they still play the same role they have. But changed for me personally is that, I don't think, I don't know if that, it was probably already true when we talked, is that at least for nonfiction, I walked away from books written recently. I think everything written recently is really just like the product of its time and it's kind of trying to put a bit more information into something that's currently evolving. I think books that have stood the test of time are just as valuable and I think they will, will always be.

• 1:03:09Speaker 01

  So what are like three old books that you've read that have fundamentally changed how you think?

• 1:03:14Speaker 00

  Books I come back to is like, I, I often talk about Parkinson's law, which I love. It's such a quick read. I, I, I almost always will mention the lessons of history, which is, I just think the densest, like the highest token quality book in existence, like given for the length. James Burnham's books are fantastic, I think, and extremely relevant.

• 1:03:36Speaker 01

  What did he write?

• 1:03:37Speaker 00

  He wrote The Managerial Revolution first and then a book called The Machiavellians, which is unbelievably good. I mean, obviously I am a meditations fan. I know stoicism is falling out of favor a little bit right now, but like it's been a lifelong thing for me and I have a copy of meditations in most rooms I spend time in. So like I just like do some random reading and it's like magical how it's somehow relevant to something I'm wrestling with. Durant, books just in general, the lessons of philosophy, the lessons of history is of course the end of life distillation of it all. But his longer book is good fiction and foundation series is so good.

• 1:04:21Speaker 01

  You read the three body problem too, right?

• 1:04:23Speaker 00

  I guess that's sort of tripping into older book now too, but like, that's a recent sci-fi, which is incredibly good.

• 1:04:30Speaker 01

  Final question, we're over saying with the same thing. This is your third time answering this question now. I'm interested, I'll go back and look at how it changed, but what is success for you?

• 1:04:38Speaker 00

  Success is just like to cultivate skills, like become good at more things and in doing so create products or toys or things that other people, that can, can make other people's like day a little bit better at, at, at the minimum or go and allow people to get power or motivation or ambition beyond what they would otherwise have.