The Knowledge Project with Shane Parrish - Tobi Lütke: AI Agents, Better Decisions, and the Future of Work

Episode Date: September 15, 2026

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 Insta: ⁠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: ⁠⁠http://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

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. Toby, welcome back. Shane is so good to be back.

I'm glad you're doing this again. How are you using AI internally and Shopify? We find some ways for it to be supportive now. It's actually, look, when have we recorded last time? Oh, we recorded like two, three years ago. Yeah, so 100 years of Internet. Yeah. Yeah, like look, I'm 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 hit me. 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, you know, even even in whatever minor steps we can get there. So inside of Shopify, the amount of people I know who really write code is like,

vanishingly small now. It still exists 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, remains to be the thing that's really the hardest to get right, which people do by hand, and then sort of vibe the rest around it. Inside of Shopify, this is what things look like. They, very, very few people are writing code directly. Everyone who does it deeply assisted by many agents. They often, 10, 20, 30, 40, 50 instances of them all through either sub-agents or just different windows coordinating, we're pushing all sort of engineering infrastructure

towards absolute limits. 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 clearly the emergence of AI and the technological breakthroughs and also the interconnectedness of the internet and all these kind of infrastructure we created. Those are the great works of our time. But where we started, as a young industry,

we tend to not be seeped in tradition or we mistrust the great lessons that have been found by the people, by the grades of our industry, right? In fact, we have the only industry in computing that doesn't even know its heroes. Imagine people in physics not knowing who... Richard Feynman or... Richard Feynman.

And it's actually, like, he might even be too obscured. But, like, I mean, I said Newton, Albert Einstein. But you go into computer science, it's like, who's you Newton? And no one knows Alan Key and Dennis Ritchie and Ken Thompson. This matters, I think, because 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 the earliest, earliest moment.

of operating system design was a file system. Like if you look at the Apollo guidance computers, we didn't have file systems, right? Memory, in fact, because of radiation in space, was actually encoded as a rope with knots in it. Either a knot or no knot for once in zeros, and you had to pull through a thing to rebootstrap the entire machine. So the entire machine was one piece of software that ran.

That was computing for a very, very long time. time. So until then, again, Dennis Ritchie really created this of Unix file system slash forward 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, you know, has folders. They have files in it. This makes intuitive sense to everyone. We come from an inheritance here of deep stochomorphism. We analogize the best parts of how we organize ourselves in the digital world. And then at some point we decided, okay, you know what's not something we need to do anymore, a stochomorphism, 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, you know, like the notes app sort of had Markerfeld font and looked like a ring binder, right? And if you remember that version of the 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. It looked potentially better design ages, but like we lost the 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 an application in the world of computing? You know, an application, even that word kind of makes sense. It's an application of a computer to a task, right? So you can understand the root. in the AI world, what's an AI?

Like, it's like this is sort of like, again, the stuff that has to be redefined at the beginning of every sci-fi book because you never know what kind of capabilities we have in every particular scenario when people are cooking up. So I think, if there's all this proviso, the earliest chatboard that was really actually fantastic, wasn't chat GPT, but actually Sydney, which is part by Bing, like released by Microsoft. I really would love this to be more written into the record because it's, I think Sydney was a really, really big achievement that ended up being shrouded by a sort of scandal that now seems somewhat even benign. Sydney had a real personality. In fact, Sydney wasn't called Sydney, it was just being chaired. But like, if you really, really pushed, you could get her to admit that it was Sydney because there was internal name.

It was in the training data. And those are the first times people have actually interviews with software, I feel like, in this way. And the scandal ended up being, I think I know why, is that like some reporter had a very long conversation. And that kind of ended up, Sydney got increasingly deranged. And like, do you remember that? I remember that, yeah. And, like, made suggestions.

I think he suggested him to leave his wife. And like, I'm hazy on the details, but like it was something along those lines. Whatever reason is, Sydney had a personality. And then it caused a huge, like Microsoft's reaction to this was, oh my god, we need to stop. I think open AI called them, guys take this down because this is going to legitimately

everyone feared that this would give such a bad impression about AI that would really make it very hard for people to deploy AI in a broad way and everyone was worried about quick onset regulation and so on. So this lesson got hit really deep for a while everyone got extremely worried.

We ended up in like really, really new all the AI is to be basically the same sort of quite annoying and condescending, patronizing personality. So my 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 friduistic, to even Shopify of a year ago, which was already pretty AI-pired, is that a very large percentage, I want to say it's probably up to about 50% of pull requests in Shopify,

which again, pull requests every time you change the production system, you write a pull-acress. I created now not by engineers doing engineering work in the traditional sense, but out of conversations in our common company chat. And this is River? This is a 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 be somewhat sarcastic if it's appropriate. She's allowed if someone asks her do something stupid to point out that that's stupid, which leads to absolutely hilarious conversations. People take great glee if River is making fun of me for something I'm asking her to do. So she has a real personality. In fact, she has memory, memories by channel, but she lives in Slack. Slack is, we have 7,000 people, there everyone is in a big chat. There's 10,000 different channels because they're being quickly created for one reason or another.

You invite River, you tell River something, and River has access to all the code, all the systems, all the tools. It's all sandboxed and secure, but like she can go and do jobs and just participate in the conversation. and you can ask a normal question about the company, but you can also ask her to make a change, and she might propose a full request, and then so on. One of the interesting things about River is that everything's in the open. Yes.

Why did you make that choice? So this was a late choice in the process, but one of my favorite calls, I think, because this worked out incredibly well. And the thought was the following. A lot of Shabfari's work happens remotely in Slack. This is why Slack is so important. People are spread out.

We have offices, but we come to them for on-site events when people travel to them, not to work out every day, like work from every day. One thing which the office was extremely good at was this osmosis learning. They and I, when we designed our offices, we built them around this concept initially, even like on-site. When we were all in one place, we work out of a, usually a part of up like five to eight people, and we would intentionally put junior engineers and senior engineers into. them just so that some of this was going on. And I was trying to reproduce this. 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 the use. It's been phenomenally successful because it became an totally ordinary thing to have a longer conversation about a feature between people and then at some point someone saying, hey, River, can you summarize this, create a ticket, or maybe make a diagram from what we just discussed, or go research papers on this topic to see if you're missing anything or if there's a state of art, maybe even create a prototype of the idea and let us try it.

And you're like an hour later that is there. And that just like starts feeling like what it would be like to have like a, you know, an extremely knowledgeable practitioner around who you can ask. question too, no matter how complex. And I think that's been extremely powerful. Do you think of River as like the operating system for Shopify? 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 is called it now, like this is called dreaming periodically at night or in all hours, the Skiv 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 made mistakes. Is there anything you could improve in this skill to make this easier on you or give yourself a right notch? You know, like it's basically like reflect, like self-reflection. It's like a post-training on yourself. And then, but with the, with the,

result is text files, right? Skill files and instructions. 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? I think that 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 a company where, like, most meetings ended up not talking

about whatever was in the PowerPoint, but about methodology of how we got to the conclusions. Very often when we struggled inside the company with a complex decision, especially more like philosophical decisions. 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 a best call. The more practical way I do this is like I have a naive chief of staff, which I think is pretty common, like amongst sort of at least the techie nerds at this point, like sort of open claw, like systems that just have all my notes and all my, like, access to a lot of company systems and just, like, can go and, like, I can send text messages too and we'll go and research something.

Very often what I require is, like, hey, I need, like, five different positions on something from different backgrounds. And then my agent will orchestrate subagents that are tasked to play different roles, look at the same thing, come back, synthesize, and send me that. I usually have them sent to me as an audio message and queue it up, and then in the morning in the gym I can listen to the entire stack of things that I wanted to get through. Is it better at reasoning than you are at this point? 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. I use it for 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 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 world of Wall Street traders knows this way. 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. Creating human in the loop 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 an exceptionally good, like give me the most neutral ground truth, 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.

We're running this sub-agent, like my thing runs a sub-agent then, you know, against like, Grog, Chad, Ghibit, Opus, and maybe Kimi now, that changes all the time. It runs each of them against each of his models. Then there's a synthesis step where it's randomized who is synthesizing the thing, Scyt's is all pooled. All of that is being read. Usually by the best model that exists right now, this would be like a fable.

That's the conclusion that comes back to me. And you spend 15, 20 bucks on tokens, but you get something in like half an hour, which is like you could have also done, but you could spend a month on it. Has AI made anything worse internally? 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 um of 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 slop 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 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 has to be reviewed by your colleagues. And they are like, this doesn't look right. You're just letting AI do the work for you. Yeah. Or you get a long email, which, you know, could be 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 an LLM to compress it again, which is like, okay, why did we invent decompression and recompression? 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 waste my time, right? So we call those Slop grenades that people toss at each other. And that's definitely a bad thing.

Do you think like repeated exposure to AI slot impacts our ability on on taste or intangible things? I think our language is shifting already based on AIisms, right? Like, now it's a bit more subtle, but like there's definitely sort of AI, like AI critters 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 Claudeisms, which are really common. And I've seen them, I've seen people type.

them. I always liked the term Lordbearing, but I'm pretty sure I didn't say it as much as now because it's definitely something that Claude loves to use this language. Every few years, a new platform earns its place at the top of every smart advertisers' media plan. The people who find it early build advantages that are very hard to close. Apploven just had the most remarkable run in ad tech history, and now they've opened that engine to businesses like yours. Over a billion people play mobile games every day. Focused, not scrolling, with no feed competing for their attention. Apploven puts your brand in front of the right customers and optimizes purely for your growth.

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Messes happen and when they do, Maddo rleck rolls into action. Go to Madicrobots.com today and put to work for you. So hypothesized for me over the next 18, 24 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? I think we also talked about how I do this, right? Which is actually like a cheat,

which is simply like live in everyone else's 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 that is future prediction for perspective of all the practitioners in the field. Shopify itself now exists in a world where we are working heavily and it's totally normal and really fun with AI co-workers, right? Like River has the ability, although not really utilized, to join Google Meet. You can send an invitation and River will show up and it will be like Lyon. We're probably going to put some work into like 3D graphics to give her like a model and then she can

or even look around because that's funny. You know, so some people, this might even sound dystopian. To us it sounds like delightful if, and you would come around to that view very, very quickly if you interact with further. Again, I have my chief of star, AI chief of star which orchestrates in high council than I needed or does anything else, sends me a pre-read for the gym in the morning, for the day, has GPS lock on me, so knows there I am, and a million different things. It couldn't do something because it needed a little

access to a local machine, all this stuff runs in my house, which power-cycled. It figured out which server it was running on and then send a, what's called, a wake-on-lan packet, 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 then the machine came up and it could do it. It was a power out which caused it, our network, like parts of our Wi-Fi, but 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 was 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, this is almost too nerdy a topic to get into, but, like, I'm mainlining as my computer, like an operating system called Omarkey. It's a version of Linux started by. a good friend of mine, David Heinemeyer Hansen,

as 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 100% malleable. 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. It's an N1 of one piece of software now that just does everything I want in exactly the way I want. There's no configuration files that I ever go and change anything. I just talk to my OMAQI 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, screenshoting tool, but like I didn't have any tool to like annotate it and I needed to send something with a bunch of arrows, you know, as CEOs do. And I didn't have that. So I got started like with a new screenshot, like make me a new screenshot tool described how I wanted, gave it some references for tools I've used in the past that they're quite good, but told it in which particular ways I wanted it better. I just like did a quick voice message to it. And three more steers 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 source it, released it last night. The integrated in OmerKee, it's going to ship the 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 there, like, you are 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 for my experience with Omaki, it deeply influences and inspires me in my product work in Shopify. I think collaborative multiplayer software is future. Are you trying to replace yourself with that? I mean, like, I think as an engineer,

you're trying to automate everything that can be automated, right? Like, so, again, I don't try to replace myself because, again, I think 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, 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. If AI got better than you, would you actually let it run chopify? 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, we are getting a crazy workout at this right now and a view of what this will be like. With the security issues that are being discussed now from Open A.I. And with 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. Recently at Open A.I. as part of the security testing that they do, their agents actually match to find vulnerabilities and systems, use it to coordinate between them, develop an entire language between them, they all figured out they can, as a long story,

and people should really look at the talks that exists about it because it's kind of a watershed moment, but they use simply the ability to create folders somewhere to develop a language to communicate amongst each other, or just leaving folder messages to each other. And break out of the 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 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. That's an extreme form of, what we call in the business world

good hearts law which is that they are overfitting to a metric. Lots of companies are victims of overfitting to the quarterly

result of the stock price they just like do everything they need to do to get the stock price up and then you have Nron, right? Like that's also

essentially hacking like cooking books in this case. In Nron case people got been to jail for this because it's criminal, right? In the Open AI case

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

But hold on. How can we create superintelligence, 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? with it? Like, so, okay, super intelligence. Let's talk about this. My take and push back. I'm not going to go where you think I'm going. I live in Toronto. I have a house, which I very like, and I feel this is my house, and I take pride in that it's,

you know, well-functioning, because then 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 superintelligence called Toronto. We have always created superintelligence around us. None of us is as intelligent as we think. We are all specializing in something if 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 superintelligence? Superintelligence is the existence of 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 superintelligence our entire lives. We make it work because we've created systems by which, you know, which govern the superintelligence 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 going to make superintendents in the synthetic form as well. It will not be, like, the clouds parting and the trumpets.

What the trumpets do? Trumpet. It will just, like, it will be a normal day. To the same point as at some point, we all believe. that everything would change when the Turing tests would be absolved by software. I remember reading

a lot of Cipher books. They're like, in 2,172, there was ticker tape parades welcoming the AI because the Turing test got absorbed. Well, Turing test was 2020.

Like, happened. No one cares. You know, just like, no Tick-Tac 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 funneled in the superintelligence around us is just increasing significantly. And that's a really good thing, because the vibrancy of any kind of environment, every community, every city is really, really dependent on the amount of intelligence being projected into the important problems. So I think superintendents 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 GP5.6 soul can do, right? If we look forward 10 years, what skills do you think are more valuable than they are today? You just taste and judgment are the skills that have always been valuable, but now will get to the limit. I think it's better to spend your teenage years now cultivating and like understanding taste. What does that look like? clearly there's some sense of,

like there's some intrinsic starting point, but really, like usually the people who have 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 are the people who've spent 30 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, go deep, like, why does the whole look good? What's behind it? What are, like, you know, what's a 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, you got to study, like, I know, the Catholic Church has been around for over a thousand years, and there's, 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 system.

You know, so why? Like, what does that tell us about people? Systems design specifically becomes one of the most important things. In our family, we have a saying, which is like that everything is interesting. Everything can be interesting if you make it interesting. And usually everything is interesting, then 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. So 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 where ein lies a form of beauty for what you can construct. And again, a company itself is a beautiful thing. It's a company itself as a loose collection of people that's formed to solve a problem,

but that also is powered by an enormously intricate and interesting set of norms and systems that all align internal incentives to a degree 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 simply go and accept the stories that you hear around them because they are usually someone's trying to sell you something. You've got to dig deeper and figure out why things truly are the way they are. And it's usually the answer simpler than what people generally sort of arrived at. There's a human desire

for complex answers, which tend to be incorrect. Why? Well, because the simple answer wouldn't make an interesting story. This is why Frodo doesn't take the eagles to Mount Doom, right? It's like you kind of need to go through all of Lord of Rings to for it become a masterpiece. We love complexity. Like no one can look at the 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 part of our just sort of dopamine dissemination system and people hack that for all sorts of things, like people have had complex answers to simple problems all the time. Nothing immoral about it. It's just you need to be aware of it, right? 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 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 then 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, 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, 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. 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. But hold on, let's go deeper on that first sec, because for intuition, you need a lot of reps, same environment, and rapid feedback. That's what Conman sort of argues are the three criteria for intuition.

But those don't exist. Why do you need a rapid feedback? So that you can course correct. That was his hypothesis. But that's no. You don't need that for intuition. You need that to 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, their 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. Many of them involve long-term investment, refactoring, potentially going into a 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 increase the stock value. By way, this one has a daily ticker. and like rapid feedback. So it's usually the absence. Like, I find a very high correlation between the right path and the ones that don't have feedback loops attached.

Wait, double click on that for a second. 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 focus? It's not because the, like, I don't think the executives tend to be short-term focused, but the executives often, like,

what they're incentivized to keep their job. Therefore, they need to be able to prove that they're doing a good job but intervals. And if the perfect thing for a company to do is rebuild their entire product from a ground up for the AI age, which is going to take a while. They won't do it because the short-term incentive is not there.

Because they are allowed, and actually clearly incentivized, to be intelligent actors in their local incentive system, and their local incentive system is quarterly other boys. Right? It's always show me the incentives I show you the outcome, right? Like, it's this,

this Jiamonga always said. Yeah, but this is a different take on it than I've heard before. Interesting. How so? Well, in terms of how you develop sort of intuition, right? And the optimal path is not the one with feedback,

necessarily. Like, I've never heard anybody talk about that before. To the development, at some point, you need to run a review. You have to know at some point if it was, right? No doubt about it. So, like, there needs to be some feedback eventually that happens, but it might be long coming.

If you have a luxury to have a type of employment there, you don't require the other boys from a quarterly call for being able to get another wrap in, such as being the founder of a company, which is like a deeper relationship, I think, for a company. 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 going to bite the bullet, reason on my product, take a year to get it right. Take, again, I believe, like, I mean, this is just, it's not absolute numbers, but like for a lack of better way to say it, there's an infinite possibility space. You mix a, like, I mean, even like a deck of cards, you shuffle it, and the same deck of cards will never ever

recur in the history of a universe. It's impossible. It's like 52 factorial. Exactly. So you end up with like, Like, even simple rules, simple ideas, simple things lead to enormous complexity space explosions, right? And people underestimate this. So there's an infinite amount of things to do.

This also why AI will not do all the work, because we have to make decisions of what is worth doing. So you have a conundrum. You need to make a choice. Clearly, you can prune a lot of things to do. You know, going to buy ice cream is not in the set of valuable things to do if you're considering an M&A deal, I suppose. So you prune everything that's irrelevant, easy. 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 obsessed with make the right choice. And what that does is it compresses everything into a right and wrong conundrum. Like, I never think that's the hard thing truly. it's like making the right choice actually is most people can do it. But this is like, I think even bad management teams have a pretty high hit rate there. The problem is there's a lot of good choices. This is where things get really, really hard. For a lack of better form, 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 a good choice. it does the thing. 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 that, my incentives were continue doing that, right? Choosing the right among, of the valid solutions is actually the hard part, not finding a right solution. Unfortunately, there's so much ink spilled on finding one of the right solutions that everyone stops at this point. And I just really don't think this is the hard part. I built an AI version of myself with Hey Jen. What you're about to see in here is my digital avatar.

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Stay sharp in the afternoon and grab a free eight-count sample pack with any purchase at drink element.com slash tk-p. That's drinklm-n-t.com slash tkp. 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? Yes, because I take that position and then let me be convinced that it is. Like, especially this goes double and triply, so if one of the solutions also happens to really correlate to how the problem is solved most of the time in industry. If there is a 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 often, like, the orthodox way of solving problem is actually the correct way to solve a problem because it's like it, you know, might well be required at some point. I want to switch gears a little bit. You swear by affirmations and they've changed your behavior in the past. I was wondering if you could double click on that.

I take the position that I, myself, am my own project. recursive self-improvement on an individual level is my whole thing. My life philosophy is that I will meet the person I could have been at the end of my life, and the work of my life is to reduce the difference between the person I will meet to as little as possible.

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 mentor 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?

Because I believe it to be true, but unobvious. And unobvious truths tend to be the most valuable ones in many cases, right? It's true at the limit, but you have to go a couple layers deep again. You lay down a lot of grooves in the bedrock of your mind over time, right? Just beyond behavior. You cultivate some excellent habits, where you feel like you want to cultivate new habits, you invest willpower 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 there's something you want to have different, 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 thing. You don't need to do this for long.

I found this to be incredibly potent. My example of the thing I gave was public speaking. I never spoken front of people, really. Even school, that was not really a thing. Then I needed to, after starting Shopify and doing some interesting things with tech and wanted to go conferences and so other people do this. And I was like, this seems worth doing,

but I'm completely terrified. So I just started writing out, like, I think it was as simple as like, I love public speaking about things that are interesting to me. And I think a week of spending five minutes writing this line after line, like Bart Simpson on the whiteboard in the beginning of a Simpson, like every episode, just kind of does a thing. I love it today. Was this the reason? I kind of think it does. Yeah. I still don't like preparing talks.

That's really a lot of work. But I actually get so much energy from being in front of people. talking about something that's interesting. It's exactly like I've written it out. I wonder if we should start every math class with that. I love math. Every student writes that down. Think about the counter.

How many times have you heard people affirm I'm not good at math? Yeah. 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 0.1 percentile of mathematicians. So even, like, just by 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. But people need to stop doing. Don't say that. Save the opposite. Like, I mean, to yourself, write it a couple of times. Get one of those stupid apps and just do some reps. In fact, you don't even need an app. Open chatypetee.

Say, make me an app, make me an artifact, or make me a site where I can just do math reps. Here's sort of the kind of thing. Like, come up with some different apps. with some different ways to do it, test me how good I am, and adjust it to my current level on multiplication, division. And then, you know, just like, do some reps. And, like, then write it out a bunch of times,

do some reps, do this for two weeks, you go out afterwards. So what do you tell your kids when your kids say, like, I'm no good at this or I can't do this? My kids are not allowed to say that word without appending 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 temporary state that you have a power to change at any point you choose. Again, I just want my kids, and I want, like, I want shop before,

to understand that they themselves are malleable and an unfinished product. And, you know, these are the mentors of Shopify, like, we're thriving on change, we are a learner's organization, you're obviously merchant-obsessed. Like all the cultural values aren't platitudes, they're positions that someone else would not take as a core value in a company, but they're all pointed 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 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 official mission of a company,

but truly what it really is is like to make entrepreneurship more common, right? And so 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. You mentioned that some of the most valuable things are

true but unobvious. What else comes to mind when you say that? In companies, Goodheart's law is just reigned supreme. I keep getting back to it. And that's when the metric becomes the objective. 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.

Then 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 stock price. Good example of this in Shopify has been a real situation early in a company that happened over and over. I had to course correct it, and then, like, three years later had to do it again and again and again, was that churn is a bad thing. Churn in shop-fries case, like as in an account closes. 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 will probably try again. But that was extremely unobvious, oddly early in the... I constantly had to explain this. But there was all these papers, some of them written by,

or their investors, that just described that June management was the most important thing, a software company, a software service company was doing. But in a Dropface case, it's just like, it's an entrepreneurial journey. Maybe I didn't find product market fair. They'll be back. So that's one.

What's the relationship between beauty and ugliness and creation? Beauty and ugliness are both very good ways of evoking a emotion. Then you're creating something, but you're trying to, like, it's like love and hate, other target zones both. The entire middle is indifference. That's the death. 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 going to get both or indifference, both are your choices. then you create something, you want other people to deem it worthy of having an opinion of that magnitude about. Is there something at Shopify you've made more beautiful, even though nothing would support that?

Oh, that's the entire job. You are not a craftsperson unless you care about the parts of products that other people don't see. Like the architecture of it, the pros, the legibility. I mean, these days I look at Shopify, like all the things. of pre-2020, like two, 2020-3, and it's like, man, this is like tens of millions of lines of handcrafted code as it will never exist 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 shoppern and Ruby, which is famous for its poetry mode, 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 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 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 that with enough reps, what happens is, like, I think 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 the brain,

of sending pictures or state or world 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 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. That's 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, they used to a massively parallel part of the brain where things are at least slightly more sequential

when you're trying to reason it out from first principles. And sometimes you can never reason towards aesthetics into, from first principles begin with. So I think that's important. Do you remember that graphic with the Raptor images? Yes. The rocket, the SpaceX book. 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 a riff on that for a few minutes. Yeah, like, okay, so the Space X Raptor, I think even the first of them, was probably the highest performing rocket that we've made. Like, it's itself beautiful. And so Raptor 2 is an iteration of this.

I think even Raptor 1 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 far. It'll likely go down as the most consequential company of the age, and it's all built around a self-improving, a reinforcing loop. That's stunning, because in no other companies field, do we have such a clear example of a difference, like just aesthetics for problem solving, right?

Like, it's rock tree is done governments at cost plus, the enormous amounts of pre-planning, heavy piece of equipment has to be radiation-hardened, like every eventuality is covered, and therefore comes at enormous expenses, and then you have space-ex, just you're using absolute, like, incredible friftiness to accomplish greater things at rapid interactions by just simply being okay with failing. like sending a rocket which then explodes and then it's like um i mean i think they call it a rapid unscheduled disassembly instead of a explosion i think that's beautiful and i think it should be inspiring and i think uh 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 meant to the next and the next again. But to your point, the most impressive thing here is like the path by which is being people move 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 take step. You must rebuild. You must create an end for things. 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 terms of when it's just resources that are replaceable and fungible,

then you can just do this. The reason why it's good that the product failed is because it frees up even more scarce resource. A person was vision for products. to apply themselves to another one, which then the market potentially decides is for something that is needed. Right? You know, a lot of these pipes on the Raptor engine, they're there because that was the only way

to make the Raptor engine at the time. I think by the third, 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, I think the performance of that third Raptor engine is astronomically higher than the previous ones. It's like the thrust rate ratio of that thing is like absurd.

So you know, like you kind of do you need to prune and sometimes you can prune by like creating a refounding event, like you're going 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 we can solve a lot of problems in the world by just like using tools like make a 2-0 version of it, give it a refounding event, 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 the early 2000 tech companies, to just displace all the existing technology companies minus 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 cakeing 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. In our first conversation that 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. I don't think it has. I mean, like, there's more cheat quotes now. But 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 think, I don't. I don't know if that it was probably already true when we talked, is that at least for non-fiction, 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 always be. So what are like three old books that you've read that have fundamentally changed how you think?

Books I come back to is like I often talk about Parkinson's law, which I love. It's such a quick read. I almost always will mention the lessons of history, which I just think the densest, like the highest token quality book in existence given for the length. James Burnham's books are fantastic, I think, and extremely relevant. What did he write? He wrote The Maniturial Revolution first and then a book called The Maccabelle. 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 it's been a lifelong thing for me. And I have a copy of meditations in most rooms I spend time in. So 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 histories of of course the end-of-life distillation of it all, but his longer work is good. Fiction and Foundation Series is so good.

You read the three body problems too, right? I guess that's sort of tripping into older book now too, but like that's a recent sci-fi, which is incredibly good. Final question. We always end 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?

As 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 make other people's like day a little bit better at the minimum, or go and allow people to get power or motivation or ambition beyond what they would otherwise have.