Tobi Lütke: AI Agents, Better Decisions, and the Future of Work

Pruning old things and rebuilding

0:00Things 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.

0:16Toby, welcome back. Shane, it's so good to be back. I'm glad we're doing this again. How are you using AI internally in 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. Like, look, I'm a 10 out of 10 nerd. I cannot bear the idea of 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.

0:48My 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 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 wipe the rest around it.

1:22Inside of Shopify, this is what things look like. Very, very, very few people are writing code directly. Everyone who does, does it deeply assisted by many agents. Very often, 10, 20, 30, 40, 50 instances of them, all through, you know, either subagents or just different windows, coordinating. We're pushing all sort of engineering infrastructure towards absolute limits.

Forgetting computing history heroes

1:45I'm a student of computing history, really, because I think it's actually mainline history, as it will be taught 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 interconnectiveness of the internet and all this 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 greats of our industry, right?

2:20Like, 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 is actually, 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 Hugh 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.

2:53For instance, like, probably the best idea of all times in the earliest, earliest moments of operating system design was a file system. Like, if you look at the Apollo guidance computers, we didn't have file systems, right? Like, 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 ones and zeros. And you had to pull through a thing to reboot-strap the entire machine. So, the entire machine was one piece of software that ran.

3:27That was computing for a very, very long time. So, until then, again, Dennis Ritchie really created this of Unix file systems, 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, it has folders. There are files in it. This makes intuitive sense to everyone.

Returning to skeuomorphic interfaces

3:47We come from an inheritance here of deep stoichiomorphism. 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 stoichiomorphism, as in, like, analogy to the real world. Honestly, funnily 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 Marker Feld font and looked like a ring binder, right?

4:23And 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.

4:54It'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 the AI have in every particular scenario when people are cooking up.

The Sydney chatbot controversy

5:11So, I think, with all this proviso, the earliest chatbot that was really actually fantastic wasn't ChatGPT, but actually Sydney, which was powered 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.

5:42It was just being chaired. But, like, if you really, really pushed, you could get her to admit that it was Sydney because that was an 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, and I think I know why, is that, like, some reporter had a very, 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.

6:13I 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, of course, a huge, like, Microsoft's reaction to this was, oh, my God, we need to stop, I think, even OpenAI called them, guys, like, take this down because this is going to... Legitimately, everyone feared that this would give such a bad impression about AI that that would really make it very hard for people to deploy AI in a broad way and, you know, everyone was worried about quick-onset regulation and so on.

6:47So, this lesson got hit really deep for a while. Everyone got extremely worried. We ended up, like, really, really neutering all the AIs 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 have a personality, to have memory, to be okay. Like, basically risk the Sydney scenario, but, like, take a lot of upside.

Deploying River inside Slack

7:18Okay. 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 pretty AI-pilled, 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 request, are created now not by engineers doing engineering work in the traditional sense, but out of conversations in our common company chat.

7:49And this is a… And this is River? This is an 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 to do something stupid, to point out that that's stupid.

8:11Which 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.

8:42It'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 pull 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 like, one of my favorite calls, I think, because this worked out incredibly well. And the thought was the following.

9:13A lot of Shabt Ferry'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 like to work out every day, like work for them every day. One thing which her office was extremely good at was this osmosis learning. Day 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 broke out of usually a pot of up to like five to eight

9:44people, 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 a totally ordinary thing to have a

10:14longer 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 it's a state-of-the-art, maybe even create a prototype of the idea and let us try it. And, you know, like an hour or so later, that is there. And that just like starts feeling like what it would be like to have like a, you know,

10:45an extremely knowledgeable practitioner around who you can ask a question to, 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 calls it now like this, it's called dreaming.

11:17Periodically 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? You know, like, it's basically like reflect, like self-reflection. It's like a post-training on yourself. And then the result is text files, right?

11:51Skill files and instructions. I think people understand how AI agents help them code and prototype and even acquire information.

Using an AI chief of staff

12:00How 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

12:33bit 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. And very often when we struggled inside of a 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 the best call. The more practical way I do this is, like, I have an AI chief of staff, which I think is

13:08pretty 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 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 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 sub-agents that are tasked to play different

13:43roles, research, 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 an 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. Like, I use it for, like, creating the right environment for judgment. Here's the thing that LLMs and machines cannot do.

14:14Machines 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.

14:45Creating 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 need an 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.

15:16We're running this sub-agent, like, my thing runs a sub-agent, then, you know, against, like, you know, Grog, ChatGPT, 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. Synthesis is all pooled. All of that is being read, usually, by the best model that exists right now.

15:48It would be, like, Fable. Well, 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.

Avoiding AI slop grenades

16:05Has 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 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.

16:35It's really easy, especially if it's 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 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, very important. You read it. And then it's, like, you read a, you know, it's not that, it's that.

17:08And 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. So 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. Do you think, like, repeated exposure to AI slob impacts our ability on taste or intangible things?

17:42I think our language is shifting already based on AI-isms, 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, there's weird, especially claudisms, which are really common. And I've seen them, I've seen people type them. I always liked the term load-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.

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Building customized operating systems

19:55And 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, 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 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 coworkers, right?

20:28Like River has the ability, although not really utilized, to join Google Meets. You can send an invitation, and River will show up, and it will be like Lycan. We're probably going to put some work into like 3D graphics to give her like a model, 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, and you would come around to that view very, very quickly if you interacted further. Again, I have my chief of staff, 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, so knows where I am, and a million different things.

21:11It couldn't do something, because it needed access to a local machine, all this stuff runs in my house, which power cycled. And it figured out which server it was running on, and then sent 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, or network, like parts of our Wi-Fi were not working and not coming back, so it fixed that too, right?

21:44So, like, and that all I learned about in a voice message I got from it in the morning after waking up. So, I was 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, this is almost too nerdy a topic to get into, but, like, I'm mainlining as my computer, like, an operating system called Omaki. It's a version of Linux started by a good friend of mine, David Heinemey Hansen, as a new passion project.

22:19And 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 1 piece of software now that just, like, does everything I want in exactly the way I want.

22:55There's no configuration files that I ever go and change anything. I just talk to my Omaki 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 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 want it, gave it some references for tools I've used in the past that were quite good, but told it in which particular ways I wanted it better.

23:32I 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. I open-sourced it, released it last night. The integrator in Omaki, 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.

24:02And I think this is, like, a lot more predictive of the future of software. I can tell you this is directionally where Shopify is going as well, right? Like, you are describing how your business runs, and Shopify will mold itself around this. And I think this is incredibly exciting and a completely new world. So, and again, I think from my experience with Omaki, it deeply influences and inspires me in my product work in Shopify.

24:36I think collaborative multiplayer software is the future. Are you trying to replace yourself with AI? 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.

25:08Like, 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 Shopify? 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.

25:39You 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 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. Recently, at OpenAI, as part of the security testing that they do,

26:12their agents actually match to find vulnerabilities in 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 exist about it because it's kind of a watershed moment. But, like, 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, you know, break out of the sandbox for confinement,

26:44end 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 an extreme form of what we call in the business world Goodhart's law, which is that they are overfitting to a metric.

27:15Lots 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 Enron, right? Like, which is also essentially hacking, like, cooking books in this case. In Enron case, people went 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.

Living with existing superintelligence

27:42It 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? Like, so, okay, superintelligence. Let's talk about this.

28:11My take, and pushback. 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.

28:46The reason why I get to live with this particular illusion is because I'm part of a superintelligence called Toronto. Like, we have always created superintelligence around us. None of us is as intelligent as we think. We are all specializing in something, 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 superintelligence? Superintelligence is the existence of something vastly smarter than us in the aggregate that's accessible to us,

29:23which 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 superintelligence in the synthetic form as well. It will not be, like, the clouds parting and the trumpets.

29:56What do trumpets do? Trumpet. It will just, like, it will be a normal day. To the same point as at some point we all believed that everything would change when the Turing tests would be solved by software. I remember reading a lot of cipher books where, like, in 2172, there was ticker tape parades welcoming the AI because the Turing test got absorbed. Well, the Turing test was 2020. Like, it happened. No one cares. You know, just, like, no ticker tape parades.

30:27So, what we are seeing right now with AI, and I think what we'll see with 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 superintelligence all around us, it's actually not that big of a deal.

30:59And, 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 Sol can do, right? If we look forward 10 years, what skills do you think are more valuable than they are today? 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.

31:29What 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 have spent 30 years 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.

Cultivating taste and deep intuition

31:58But also, you just go deep. Like, why does the logo 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've got to study, like, you 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?

32:28Like, 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'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.

33:00So, 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, where I am 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 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?

33:49Like, some companies lasted for a very, very long time, specifically, and ours 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. Like, you can't, like, simply go and, like, accept the stories that you hear around them because they are usually someone who'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.

34:24There's a human desire for complex answers, which tend to be incorrect. Why? Well, because the simple answer wouldn't make an interesting story. Like, this is why, 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, 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 the sunset every single evening of our lives, right?

34:58Like, 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 peddle complex answers to simple problems all the time. Nothing amoral 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.

35:32And 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, which can now be quite agent-augmented. But really, what you're trying to cultivate is what we call intuition, which is actually just judgment at an instant, right?

36:05Like, 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.

36:36But 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. Why do you need a rapid feedback? So that you can course correct. That was his hypothesis. Yeah, but that's already, but that's, no, you don't need that for intuition. Like, you need that for, 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, where intuition ended up having to play a role, is when we knew there wasn't going to be any feedback mechanism.

37:19Like, 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? Like, 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.

37:49Or 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, 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 focused? It's not because the, like, I don't think the executives tend to be short-term focused, but the executives often, like, would be incentivized to keep their job.

38:22Therefore, they need to be able to prove that they're doing a good job at intervals. And if the perfect thing for a company to do is rebuild their entire product from the ground up for the AI age, that's just 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?

38:52It's always, show me the incentives and I show you the outcome, right? Like, as Jay Munger 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.

39:27But it might be long coming. If you have a luxury to have a type of employment there, you don't require the attaboys from a quarterly call for, you know, being able to get another rep 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 my product, take a year to get it right.

40:00Take, again, I believe, like, I mean, this just, it's not absolute numbers, but like, for lack of a 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 the universe. It's impossible. It's like 52 factorial. Exactly. So you end up with, 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.

40:32This 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 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 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 obsessed with make the right choice.

41:06And 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. But for 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.

41:42Some 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, my incentives were to continue doing that. But choosing the right of valid solutions is actually the hard part, not finding the right solution.

42:15And unfortunately, there's so much inks built 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 Heijeng. What you're about to see in here is my digital avatar. I asked it why some professionals build an audience while most stay invisible. And here's what it said. Hey, Shane, the professionals breaking out right now aren't the most talented ones. They're the most visible ones. That's their edge. They show up on video constantly.

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43:55That's drinkelement.com.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's this. 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.

44:27If there is an orthodox way to solve a problem, I am incredibly suspicious that 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 of payments and so on. They often, like, the orthodox way of solving a problem is actually the correct way to solve a problem because it's like, you know, it 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.

45:01I was wondering if you could double click on that.

Using affirmations to change behavior

45:03I take the position that I myself am my own project. Concurse of 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.

45:35Everything's interesting, you know. But why do I stop to point out that everything is interesting as 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? Like, 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 of 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, like where you feel like you want to cultivate new habits.

46:14You 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, like, incredibly potent. My example of a thing I gave was, like, public speaking.

46:45I never spoke in front of people, really. Even school, that was not really a thing. When I needed to, after studying Shopify and doing some interesting things with tech and wanted to go to conferences and saw other people do this. And I was like, this seems worth doing, but I'm completely terrified. So I just, like, 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,

47:16like 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?

47:26I 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. So 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, I mean, compared to every human who's ever lived, they are in the top 0.1 percentile of mathematicians.

47:59So even, like, just by being able to understand division. You 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 that people 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 reps. In fact, you don't even need an app. Open ChatGPT, say, make me an app. Make me an artifact or make me a site where I can just do math reps.

48:31Here's sort of the kind of thing. Like, come up 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're good. 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.

49:04Three 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 an intrinsic property of you. It is a temporary state that you have the power to change at any point you choose. Again, I just want my kids and I want, like, everyone in Shopify to understand that they

49:34themselves 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. We're obviously merchant-obsessed. Like, all of the cultural values aren't platitudes, but they're positions that someone else would not take as a core value in a company. But they're all pointed at the same thing, which is that you are malleable, the company is malleable, our product is malleable. And, by the way, the times we are in, like, change as well.

50:08You 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. And, like, again, it's the official mission of a company, but truly what it really is, is, like, to make entrepreneurship more common, right?

50:39And 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, Goodhart's law just reigns supreme. I keep getting back to it. And that's when the metric becomes the objective? When the metric becomes the objective, it's no longer a good metric. Because, again, a metric is a proxy of sorts.

51:12It'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. A good example of this in Shopify has been the 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. It was that churn is a bad thing.

51:46Churn, in Shopify's 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 years.

52:20And I constantly had to explain this. But there was all these papers, some of them written by our very investors, that just described that churn management was the most important thing a software company, a software-as-a-service company was doing. 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. What's the relationship between beauty and ugliness and creation? Beauty and ugliness are both very good ways of evoking an emotion.

52:53When 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 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.

53:25Or indifference. Both are your choices. When you create something, you want other people to deem it worthy of having an opinion of that magnitude about. Every successful business evolves. And to keep up, you need a bank relationship that evolves, too. When you collaborate with KeyBank, you don't get one-size-fits-all solutions. Our expansive team of experts across industry verticals wouldn't be here if you did. Always ready with bespoke solutions for your biggest challenges and opportunities.

53:56We know all businesses are different, and that's why we approach business differently. Reimagine business as usual. KeyBank opens doors. Learn more at key.com slash b2b. Is there something in 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 prose, the legibility. I mean, these days I look at Shopify like off pre-2020, like to 2023, and it's like, man, this is like tens of millions of lines of handcrafted code as it will never exist again.

54:40Like, 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, 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.

55:17So, 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, like, understanding of what intuition truly is or where it comes from is that with enough reps, what happens is, like, I think, like, most of the energy budget of our brain is actually in the visual neural cortex.

55:48It'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 world model, whatever, to the brain, it can communicate concepts, too, and it does this by aesthetics. When 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.

56:25The reason why I looked at it is because it seemed beautiful to me in the moment. And 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, like, they use the 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 from first principles to begin with. So, I think that's important.

56:57Do you remember that graphic with the raptor images? Yes. The rocket, the SpaceX book.

Studying SpaceX and durable books

57:04So, 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. 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 itself beautiful.

57:35And 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.

58:06That's stunning, because in no other, I think, company's field do we have such a clear example of a difference, like, of just aesthetics for problem-solving, right? Like, it's, like, it's, rock tree is done by governments at cost-plus. Oh, the enormous amounts of pre-planning. Every piece of equipment has to be radiation-hardened. Like, every eventuality is covered, and therefore comes at enormous expenses.

58:38And then you have SpaceX just using absolute, like, incredible thriftiness to accomplish 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 unscheduled disassembly instead of an explosion. I think that's beautiful. And I think it should be inspiring.

59:08And 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 went to the next and the next again. But to your point, the most impressive thing here is, like, the path by which people move forward here. Things need to be pruned. You cannot make things better and better by adding stuff.

59:39You can't. You must prune. You must take steps. 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 terms of when it's just resources that are replaceable and fungible, then you can just do this. But the reason why it's good that the product failed is because it frees up an even more scarce resource.

1:00:16A person who has vision for products to apply themselves to another one, which then the market potentially decides is something that is needed. You know, a lot of these pipes on the 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 looks mostly 3D printed. Maybe that wasn't technology that was available back then. But now that it is, every one of those pipes was incorrect. It didn't need to be there.

1:00:47In fact, 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. So, you know, like, you kind of, 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 could 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.

1:01:25And, like, building in more exploration of systems would solve a huge amount of inside companies, like renewal and so on. And 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, like, three or four. It was just because they fell prey to a world of a lack of competition.

1:01:57And then what they built then wasn't fortunate in the fires of competition and therefore wasn't tested. And it was easier to just simply solve problems by adding addition and 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 and 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.

1:02:30I'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 codes now. But I think the books, they still play the same role they have. What 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 non-fiction, I walked away from books written recently. I think everything written recently is really just, like, the product of its time.

1:03:01And 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, like, given for the length.

1:03:35James Burnham's books are fantastic, I think, and extremely relevant. What did he write? 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.

1:04:12Durant 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. You read The Three Body Parallel, too, right? I mean, 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? Success is just, like, to cultivate skills, like, become good at more things.

1:04:47And 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.

1:05:17And in doing so, like, day a little bit better, at the minimum.