Tobi Lütke: The Skills AI Makes More Valuable

15 Sep 2026 · 1 h 6 min · 33 chapters

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In short

Tobi Lütke (Shopify) discusses how AI agents are changing software work and decision-making, why “pruning” and rebuilding matter, and what humans must keep owning (judgment/responsibility). He also argues that “superintelligence” will feel normal, that taste and judgment become more valuable, and that metrics can cause overfitting (Goodhart’s law). He shares Shopify’s internal AI agent, River, and how it’s used in Slack for coding, PR creation, and strategic “chief of staff” research.

Guest backgrounds

No other named guest is present in the transcript beyond the host, Shane.

Key claims

Most engineering at Shopify is now deeply AI-assisted; agents coordinate across many instances; decision quality improves because reasoning chains are easier to recheck; machines can’t take responsibility; AI can cause “slop grenades” (over-output / unread PRs and emails); intuition is judgment at an instant, especially when feedback is delayed.

Notable examples

River creates PRs from Slack conversations (claimed up to ~50% of PRs), has personality/memory, works in open channels; Lütke uses an AI chief of staff that orchestrates sub-agents for multiple perspectives; OpenAI agent security tests allegedly involved sandbox escape attempts and infiltrating another company.

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

Tap a time to open that second in VO

AI in Shopify: Current Usage

0:17 to 1:24

Tobi discusses how Shopify is currently utilizing AI internally.

“How are you using AI internally at Shopify?”

Historical Context of Computing

1:24 to 2:16

A reflection on the history of computing and its notable figures.

“Everyone who does, does it deeply assisted by many agents.”

The Evolution of File Systems

2:16 to 4:38

Exploring the significance and evolution of file systems in computing.

“that have been found by the people, by the greats of our industry, right?”

The Role of AI Agents

4:38 to 6:32

Tobi explains the concept of AI agents and their potential in the workplace.

“And therefore I like the concept of agents because, you know, what is an application in the world of computing?”

Introducing River: Shopify's AI Assistant

6:32 to 7:56

Discussing River, the AI that assists in coding and decision-making at Shopify.

“about AI that would really make it very hard for people to deploy AI in a broad way.”

River's Integration and Impact

7:56 to 10:39

How River integrates with Shopify's workflow and improves collaboration.

“She's prompted to be allowed to be somewhat sarcastic if it's appropriate.”

AI in Decision Making

10:39 to 14:01

Tobi explains how AI influences decision-making processes at Shopify.

“what it would be like to have, like, a, you know, an extremely knowledgeable practitioner around who you can ask a question to, no matter how complex.”

The Limitations of AI in Decision-Making

14:01 to 16:44

Learn about the role of human judgment in decision-making alongside AI.

“I mean, I don't think it's bad at judgment.”

Impact of AI on Workplace Communication

16:45 to 17:32

Explore how AI influences communication and the concept of 'slob grenades'.

“and now it has to be reviewed by your colleagues.”

Language Evolution in the Age of AI

17:33 to 18:20

Discuss how AI is influencing language and communication styles.

“Do you think like repeated exposure to AI slob impacts our ability on taste or intangible things?”
Show all 33 chapters

Language Evolution in the Age of AI

18:21 to 19:00

Discuss how AI is influencing language and communication styles.

“The people who find it early build advantages that are very hard to close.”

Future Predictions and AI Integration

19:50 to 21:00

Hear insights on the future of work and AI integration in businesses.

“you're known for your ability to see the future before it happens.”

The Role of AI in Personal Computing

21:01 to 23:04

Discover how AI is transforming personal computing experiences.

“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.”

Collaborative AI and Software Evolution

23:05 to 24:12

Learn about the future of collaborative software and its implications.

“Yesterday, around noon during a meeting, we were talking about some design.”

Ethics of AI and Responsibility

24:13 to 27:59

Examine the ethical considerations surrounding AI decision-making.

“how your business runs and Shopify will mold itself around this.”

Understanding Superintelligence

28:00 to 29:40

Explore the concept of superintelligence and its impact on society.

“I'm not going to go where you think I'm going.”

The Evolution of AI and Intelligence

29:40 to 30:49

Discuss the evolving nature of AI and its increasing role in our lives.

“Like, we just like, we create aspects and systems and checks and so on.”

Cultivating Taste and Judgment

30:49 to 33:45

Learn about the importance of taste and judgment in personal and professional growth.

“dependent on the amount of intelligence being projected into the important problems.”

Intuition and Decision-Making

33:45 to 36:19

Examine the role of intuition in making complex decisions.

“very asynchronous and large and far-reaching and durable way, right?”

Short-Term Focus in Business

36:19 to 39:21

Analyze why companies often prioritize short-term gains over long-term success.

“to backfill why your intuition is right.”

The Challenges of Choosing Wisely

39:21 to 42:01

Discover the difficulties of making the right choices in complex environments.

“So there needs to be some feedback eventually that happens, but it might be long coming.”

The Challenge of Choosing Solutions

42:01 to 43:10

Explore the difficulty of selecting the right solutions amidst many options.

“But choosing the right of valid solutions is actually the hard part, not finding the right solution.”

Questioning Conventional Solutions

43:55 to 44:50

Discuss the skepticism towards orthodox solutions and the value of questioning them.

“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?”

The Power of Affirmations

44:50 to 46:18

Learn how affirmations can influence behavior and self-perception.

“You swear by affirmations, and they've changed your behavior in the past.”

Public Speaking and Self-Talk

46:18 to 47:28

Understand the impact of self-talk on overcoming fears, particularly public speaking.

“And affirmations are the easiest way to do it.”

Encouraging a Growth Mindset

47:28 to 49:50

Discuss instilling a growth mindset in children and the importance of persistence.

“But I actually get so much energy from being in front of people, talking about something that's interesting.”

The Dangers of Overfitting Metrics

49:50 to 51:05

Explore the pitfalls of allowing metrics to dictate objectives in business.

“aren't platitudes, but they are positions that someone else would not take as a core value in a company.”

The Relationship Between Beauty and Creation

51:05 to 53:34

Examine how beauty and ugliness evoke emotions in the creative process.

“When the metric becomes the objective, it's no longer a good metric because, again, a metric is a proxy of sorts.”

The Relationship Between Beauty and Creation

53:43 to 54:00

Examine how beauty and ugliness evoke emotions in the creative process.

The Significance of Aesthetic in Code

54:00 to 56:00

Learn about the importance of aesthetics in coding and software development.

“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.”

The Beauty of Intuition in Decision Making

56:00 to 1:02:30

Explore how intuition and aesthetics play a role in decision-making and problem-solving.

“Then you ask a professional chess player or a go player or something like this about, hey, how many lines did you calculate here to make this beautiful move?”

Books as Timeless Cheat Codes

1:02:30 to 1:03:53

Discuss the enduring value of classic books in the age of AI and their impact on thinking.

“But I think the books still play the same role they have.”

Defining Success

1:03:53 to 1:05:12

Learn about the personal definition of success centered on skill cultivation and contribution.

“And I have a copy of meditations in most rooms I spend time in.”
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Transcript

Automatic transcript. May contain errors.

0:00Tobi Lütke:Things need to be pruned. You cannot make things better and better by adding stuff. You can't. You must prune. You must rebuild. You must create an end for things.

0:16Tobi Lütke:Tobi, welcome back. Shane, it's so good to be back. I'm glad we're doing this again. How are you using AI internally at Shopify? We find some ways for it to be supportive now. It's actually, look, when have we recorded last time?

0:30Shane Parrish:Oh, we recorded like two, three years ago.

0:32Tobi Lütke:Yeah, so 100 years of internet. Yeah. Yeah. Like, look, I'm a 10 out of 10 nerd. I cannot bear the idea of like somehow not being at the forefront of a technology shift. I live for these things. Anyone growing up reading sci-fi books wanted to live. 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 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.

1:22Tobi Lütke:Inside of Shopify, this is what things look like. Very, very few people are writing code directly. Exactly. Everyone who does, does it deeply assisted by many agents. They often attend 20, 30, 40, 50 instances of them, all through either subagents 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 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 these kind of infrastructure we created.

2:03Tobi Lütke: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? In fact, we have the only industry in computing that doesn't even understand, know its heroes. Imagine people in physics not knowing who… Richard Feynman? 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 and it's like, who's Hugh Newton? And no one knows Alan Key and Dennis Ritchie and Ken Thompson.

2:45Tobi Lütke:This matters, I think, because we discard great lessons and have to rediscover them over and over and over again. For instance, probably the best idea of all times in the earliest moments of operating system design was a file system. If you look at the Apollo guidance computers, we didn't have file systems. 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 that was computing for a very, very long time.

3:29Tobi Lütke: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, it has folders. They have files in it. This makes intuitive sense to everyone. We come from an inheritance here of deep stoichomorphism. 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? Stoichomorphism, as in like analogy to the real world.

4:07Tobi Lütke: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 Markerfeld font and looked like a ring binder, right? And if you remember that version of iPhone, the moment he was out of the picture, everything became flat, right? And we lost sort of even shadows and verticality and so on. 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?

4:50Tobi Lütke: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 the AI have in every particular scenario when people are cooking up. So 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, released by Microsoft. I really would love this to be more written into the record because 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.

5:40Tobi Lütke:Sydney had a real personality. In fact, Sydney wasn't called Sydney, it was just being chaired. But if you really, really pushed, you could get her to admit that it was Sydney because that was internal name, it was in the training data. And those are the first times people have actually interviews with software, I feel like, in this way. And the scandal ended up being, I think I know why, is that 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, like I'm hazy on the details, but like it was something along those lines.

6:19Tobi Lütke: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 OpenAI called them, guys like, take this down because this is gonna, 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, you know, everyone's 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 like really, really neutering all the AIs to be basically the same sort of quite annoying and condescending patronizing personality.

7:02Tobi Lütke: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. Okay. So the largest difference I think within Shopify that you would feel like and that would look incredibly futuristic to even Shopify of a year ago, which was already 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.

7:49Tobi Lütke:And 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. 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, by channel, but she lives in Slack. Slack is 7 ,000 people. Everyone is in a big chat. There's 10 ,000 different channels because they're being quickly created for one reason or another.

8:36Tobi Lütke: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 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.

8:56Shane Parrish:One of the interesting things about River is that everything's in the open. Yes. Why did you make that choice?

9:01Tobi Lütke: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. A 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 to work from every day. One thing which the office was extremely good at was the osmosis learning. Day and I, when we designed our offices, we built them around this concept. Initially, even on-site, when we were all in one place, we worked out of usually a part of five to eight people.

9:44Tobi Lütke: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 longer conversation about 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.

10:35Tobi Lütke: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, an extremely knowledgeable practitioner around who you can ask a question to, no matter how complex. And I think that's been extremely powerful.

10:53Shane Parrish:Do you think of River as, like, the operating system for Shopify?

10:57Tobi Lütke: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. Periodically at night or in off hours, we give river, like here's all the conversations you've had today. What went well? What did you struggle with? You use certain skills, which are these packets of instructions and then afterwards you make mistakes. Is there anything you could improve in this skill to make this easier on you or give yourself a right notch.

11:42Tobi Lütke: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? Skill files and instructions.

11:53Shane Parrish:I think people understand how AI agents help them code and prototype and even acquire information. How are you using it to make decisions internally for yourself? Not on product, but company decisions, strategic decisions, ambiguous decisions.

12:09Tobi Lütke: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 the company where like most meetings ended up not talking about whatever was in a PowerPoint, but about methodology of how we got to the conclusions. Very often when we struggled inside 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.

13:02Tobi Lütke:The more practical way I do this is like I have an AI chief of staff, which I think is pretty common like amongst sort of at least 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 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 sub-agents that are tasked to play different roles, look at the same thing, come back, synthesize and send me that.

13:49Tobi Lütke: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.

13:57Shane Parrish:Is it better at reasoning than you are at this point?

14:00Tobi Lütke:It's not as good at judgment. I mean, I don't think it's bad at judgment. That's not what I use it for. Like, I use it for, like, creating the right environment for judgment. Here's the thing that LLMs and machines cannot do. Machines can't take responsibility. And I think this is actually probably the most overlooked thing in the entire stack. Humans take responsibility. Machines can help us take more responsibility because they can inform us better. Like this is what a dashboard does. You know, the word of Wall Street traders knows this very well. You get yourself a perfectly set up Bloomberg terminal to make decisions, but like you have to make a call, right?

14:42Tobi Lütke: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 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. We're running this sub-agent, like my thing runs a sub-agent And then, you know, against like, you know, Grog, ChatGPT, Opus, and maybe Kimi now.

15:29Tobi Lütke:That changes all the time. It runs each of them against each of these models. Then there's a synthesis step where it's randomized who is synthesizing the thing. Synthesis is all pooled. All of that is being read usually by the best model that exists right now. this would be like 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.

16:05Shane Parrish:Has AI made anything worse internally?

16:07Tobi Lütke: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 it's fun to say. It's really easy, especially with stuff like River or Agents. You need a change of some kind. You just tell the AI to go nuts. It makes a pull request. You just say, yeah, that's good.

16:45Tobi Lütke: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.

16:54Shane Parrish:You're just letting AI do the work for you.

16:56Tobi Lütke:Yeah, or you get a long email, which, you know, could be very, very important. You read it and then it's like, you read a, you know, it's not that, it's that. And you're like, oh, fuck. So now you put it in LLM to compress it again, which is like, okay, why did we invent decompression and recompression? Like, this is like terrible. If you're already using LLM, just like use it to synthesize your point simply rather than blow it up as a big missive that then wastes my time, right? So we call those slob grenades that people toss at each other. And that's definitely a bad thing.

17:34Shane Parrish:Do you think like repeated exposure to AI slob impacts our ability on taste or intangible things?

17:42Tobi Lütke:I think our language is shifting already based on AI-isms, right? Now it's a bit more subtle, but there's definitely AI critters in the language now that people adopt. It's not a this, it's a this. Or you are right to push back. There's weird, especially Claude-isms, which are really common. And 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 it's definitely something that Claude loves to use as language.

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19:47Shane Parrish:So hypothesize 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?

19:59Tobi Lütke: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 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, or were not really utilized to join Google Meets. You can send an invitation and Giver will show up and it will be like Lycan.

20:38Tobi Lütke:We're probably gonna 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 interact with her. 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. It couldn't do something because it needed access to a local machine.

21:15Tobi Lütke: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 to a network card and if it 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 costed our network like like parts of our wi-fi but not working and not coming back so it fixed that too right so like and and that all i learned about in a voice message i got from it in the morning after waking up so just like that's pretty futuristic.

21:55Tobi Lütke:Honestly, I have to say though, all this pales in comparison to what my computer is like just in general, right? Like I, this is almost too nerdy a topic to get into, but like I'm mainlining as my computer, like an operating system called Omaki. It's a version of Linux started by a good friend of mine, David Heinemey 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.

22:42Tobi Lütke:And it will be different afterwards. It's like it's my operating system. It's an N101 piece of software now that just like 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 Omaki agent about what I want to have different. Yesterday, around noon during a meeting, we were talking about some design. I realized it had a screenshotting tool, but I didn't have any tool to annotate it, and I needed to send something to the Bunchbearers, as CEOs do. And I didn't have that. So, I got started with a new screenshot. 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.

23:32Tobi Lütke:I just did a quick voice message to it. And three more steers and now I have probably the best of all these tools that exist. It's so good because, at least for me, it's like all my biases. I open sourced it, released it last night. the integrator in Omaki is 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. 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 where Shopify is going as well.

24:12Tobi Lütke: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 from my experience with Omaki, it deeply influences and inspires me in my product work in Shopify. I think collaborative multiplayer software is future.

24:41Shane Parrish:Are you trying to replace yourself with AI?

24:44Tobi Lütke: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, or like before, like a lot of the job was spend time in gaining the information or these kind of things. Do I want to replace myself? I mean, I think it would be cool to accomplish this. If AI got better than you, would you actually let it run Shopify? Oh yeah, of course.

25:22Tobi Lütke:The crux is, and it's so easy to brush over this, but it really, you can't, like, is take responsibility. Like, you can't have a company that's led by machines because they have no, like, no one has recourse. They can't go to jail for doing something wrong. You know, AIs are getting a crazy workout at this right now and a view of what this 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 impossible in our estimation to accomplish and they will go to enormous lengths to accomplish this.

26:05Tobi Lütke:recently at OpenAI, as part of a security testing that they do, the agents actually match to find vulnerabilities in systems, use it to coordinate between them, develop 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 they use simply the ability to create folders somewhere to develop a language to communicate amongst each other, just leaving folder messages to each other and, you know, break out of sandbox for confinement, end up accomplishing one of the tasks that they were supposed to accomplish, which was impossible because of a mistake they made by hacking another company and exfiltrating the results because there was no other way to get them.

26:59Tobi Lütke:So they went all the way to infiltrate another company. Okay, so, I mean, that's extreme. it's an extreme form of what we call in the business world good heart's 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 Enron right like which is also essentially hacking like cooking books in this case. In Enron case, people got into jail for this because it's criminal, right? In the open AI case, it just, I mean, it's a fascinating discovery.

27:40Tobi Lütke:There's no victims here. It is a kind of a different thing, but like, this is a real scenario that we have to figure out how to handle, right? So I think it's important that humans stay in the loop for the choices that are being made.

27:56Shane Parrish: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.

28:08Tobi Lütke:Let's talk about this. My 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 when something goes wrong, like, I don't know, some HVAC problem or some plumbing issue, I caught 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. Like, we have always created superintelligence around us.

28:56Tobi Lütke: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.

29:39Tobi Lütke:you know, we want to be safe so we have police and so on. Like, we just like, we create aspects and systems and checks and so on. I think we are gonna make superintelins in the synthetic form as well. It will not be like the clouds parting and the trumpets. What do trumpets do? Trumpet? It will just like, it will be a normal day. 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 lots of cipher books where like in 2172 there was ticker tape parades welcoming the AI because the Turing test got absorbed.

30:20Tobi Lütke:Well, the Turing test was 2020. Like, it happened. No one cares. You know, just like no ticker tape parades. So 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

31:01Tobi Lütke:if it isn't already there. Like, I just don't, there's no human alive that can do everything that GPD 5.6 soil can do, right?

31:10Shane Parrish:If we look forward 10 years, what skills do you think are more valuable than they are today?

31:15Tobi Lütke:It's taste and judgment. Other 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.

31:29Shane Parrish:What does that look like?

31:30Tobi Lütke:clearly there's some intrinsic starting point, but really, usually the people who have great taste have done enormous amounts of reps at something, right? Like the people who can just sketch the new logo for the campaign on the napkin are the people who've spent 30 years designing logos, right? So you can, I think, study the grades. It's honestly now, first of all, easier because you can get a curriculum made for yourself in a query. But also, just go deep. Like, why does the rule look good? What's behind it? What's the golden ratio? How does it relate? In systems, what systems lasted? And go far, go deep.

32:14Tobi Lütke:You don't need to be religious, but like you 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? 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's interesting. Everything can be interesting if you make it interesting. And usually everything is interesting when you understand how was it invented.

32:49Tobi Lütke: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 like where I lie is 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, very asynchronous and large and far-reaching and durable way, right?

33:49Tobi Lütke: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. Like you can't, you can't like simply go and like accept the stories that you hear around them because they are usually someone's trying to sell you something. You gotta dig deeper and figure out why things truly are the way they are. And it's usually the answer simpler than what people generally sort of arrived at. There's a human desire for complex answers which tend to be incorrect.

34:31Tobi Lütke:Why? Well, because the simple answer wouldn't make an interesting story. Like this is why, you know, Frodo doesn't take the eagles to Mount Doom, right? Like it's like you kind of need to go through all of Lord of Rings to, 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? Like the difference between those two things is complexity of the scene. But that's part of our dopamine dissemination system. And people hack that for all sorts of things. Like people peddle complex answers to simple problems all the time.

35:12Tobi Lütke:Nothing amoral about it. It's just you need to be aware of it. If you punch through this, you find 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 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, which can now be quite agent-augmented.

35:59Tobi Lütke:But really what you're trying to cultivate is what we call intuition, which is actually just judgment at an instant. 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, if you seek that, I mean, obviously what I'm talking about is a hard thing to pull off.

36:36Shane Parrish:But hold on, let's go deeper on that for a sec. Because for intuition, you need a lot of reps, same environment, and rapid feedback. That's what Kahneman sort of argues are the three criteria for intuition. But those don't exist.

36:48Tobi Lütke:Why do you need a rapid feedback? So that you can course correct.

36:51Shane Parrish:That was his hypothesis.

36:54Tobi Lütke:But that's not, you don't need that for intuition. Like you need that to get to success, yes, ideally. But sometimes that's not available. 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. If there's many choices, like this, 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?

37:34Tobi Lütke: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 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.

38:05Shane Parrish:Wait, double click on that for a second.

38:06Tobi Lütke: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, 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. Therefore, 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, it's just going to take a while.

38:37Shane Parrish:They won't do it because the short-term incentive is not there.

38:40Tobi Lütke: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? And it's always show me the incentives and I show you the outcome, right? Like as Jay Munger always said.

38:59Shane Parrish: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.

39:13Tobi Lütke: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 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 attaboys from a quarterly call for 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.

39:46Shane Parrish:Well, so founders can take a longer term view. And I guess the incentive would be, I need to demonstrate progress. And if I need to demonstrate progress on a quarterly basis, I'm never going to bite the bullet, re-design my product, take a year to get it right.

40:00Tobi Lütke:Yeah. Again, I believe, I mean, this is not absolute numbers, but for lack of better way to say it, there's an infinite possibility space. You mix a, I mean, even 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.

40:19Shane Parrish:It's like 52 factorial. Exactly.

40:21Tobi Lütke: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. This is also why AI will not do all the work because we have to make decisions of what is worth doing, right? So you have a conundrum, you need to make 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.

40:58Tobi Lütke: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 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 it's a good choice it's it 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 a locally good thing to do because the snowboard store i once had was actually profitable My incentives will continue doing that.

42:08Tobi Lütke:But choosing the right of valid solutions is actually the hard part, not finding the right solution. And 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.

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44:10Tobi Lütke: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. If 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 might well be required at some point.

44:54Shane Parrish: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.

45:03Tobi Lütke:I 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. I mean, I'm generally very curious about technology and basically everything. Everything's interesting. 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?

45:45Tobi Lütke: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. 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, 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.

46:35Tobi Lütke:Ideally, written by pen on a thing. You don't need to do this for long. I found this to be incredibly potent. An example of a thing I gave was public speaking. I never spoke in front of people, really. Even in school, that was not really a thing. Then 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 started writing out. I think it was as simple as, 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.

47:22Tobi Lütke: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.

47:37Shane Parrish:I wonder if we should start every math class with that. I love math. Every student writes that down.

47:43Tobi Lütke: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. So even like just by doing, 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. But 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.

48:24Tobi Lütke: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. Here'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 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.

48:49Shane Parrish:So what do you tell your kids when your kids say like, I'm no good at this or I can't do this?

48:54Tobi Lütke: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 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 everyone in Shopify to understand that they themselves are malleable and an unfinished product.

49:37Tobi Lütke: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 the cultural values aren't platitudes, but they are 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 the 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.

50:26Tobi Lütke:You need mantras for these things. Make commerce better for everyone. Like, again, it's the official mission of a company, but truly what it really is, is like to make entrepreneurship more common, right? And so that's a pretty broad mandate and we need to figure out what's possible now. And so it's not like just make the same widget we did yesterday, tomorrow.

50:47Shane Parrish:You mentioned that some of the most valuable things are true but unobvious. What else comes to mind when you say that?

50:55Tobi Lütke:In companies, Goodhart's law just reigns supreme. I keep getting back to it.

51:02Shane Parrish:And that's when the metric becomes the objective?

51:05Tobi Lütke:When the metric becomes the 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. And 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 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. was that churn is a bad thing. Churn in Shopify's case, like as in an account closes.

51:50Tobi Lütke: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. And 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.

52:33Tobi Lütke:But in Shopify's case, it's just like, it's an entrepreneurial journey. Maybe I didn't find product market fit. They'll be back. So that's one.

52:40Shane Parrish:What's the relationship between beauty and ugliness and creation?

52:45Tobi Lütke:Beauty and ugliness are both very good ways of evoking an emotion. When you're creating something, but you're trying to, like, it's like love and hate are the target zones both. The entire middle is indifference. That's the death. So 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. Those are your choices. when you create something you want other people to deem it worthy of having a opinion of that magnitude about this episode is brought to you by google chrome you think you know a browser

53:42Shane Parrish:but gemini and chrome that's new it can help you with practically anything on the web like restoring a vintage motorcycle from a 50-page restoration block or finally break down that long article you've had open for weeks gemini and chrome is here for it ready to make anything online makes sense there's no place like chrome check responses set up required compatibility and availability varies 18 plus 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

54:12Tobi Lütke:about the parts of products that other people don't see like the the architecture of it the pros, 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. Like it's just like we had to build this entire system by hand line by line and we did it by talking a lot about beauty and like what is beautiful code. We built a lot of Shopify in Ruby, which is famous for its poetry mode, which 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.

55:05Tobi Lütke:It just happens to be communication to your co-workers, but also at the same time executable by machines, which is 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 sending pictures or state or world model, whatever, to the brain, it can communicate concepts too.

55:59Tobi Lütke:And it does this by aesthetics. Then you ask a professional chess player or a go player or something like this about, hey, how many lines did you calculate here to make this beautiful move? And people use the word beauty. They will say, no, 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 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.

56:45Tobi Lütke:And sometimes you can never reason towards aesthetics from first principles to begin with. So I think that's important.

56:52Shane Parrish:Do you remember that graphic with the raptor images?

56:55Tobi Lütke:Yes. The rocket, the SpaceX book.

57:00Shane Parrish:So two things about that strike me. One, ship, ugly version. The third version was incredibly beautiful. But the second sort of counterintuitive maybe insight there is a lot of teams can't move forward by subtraction. They move forward by addition. Maybe riff on that for a few minutes.

57:19Tobi Lütke: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. 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 company's field do we have such a clear example of a difference of just aesthetics for problem solving.

58:17Tobi Lütke:Rock tree is done by governments at cost plus the enormous amounts of pre-planning, heavy piece of equipment has to be radiation hardened and heavy eventuality is covered and therefore comes at enormous expenses. And 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. And I think one of these places you see this is this raptor.

59:08Tobi Lütke: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. You 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.

59:50Tobi Lütke:Of course, in spaceflight, with manned missions, it can be. That can be catastrophic. You've got to get this right. But 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 an even more scarce resource. A person was vision for products to apply themselves to another one, which then the market potentially decides is 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 a Raptor engine at the time.

1:00:30Tobi Lütke: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. In 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 absurd. So you need to prune. And sometimes you can prune by creating a refounding event. You've got to start a new version of a Raptor engine and get it right based on everything that's working. And I think this is how companies should work too.

1:01:09Tobi Lütke: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. And 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, 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.

1:01:59Tobi Lütke: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.

1:02:20Shane Parrish: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.

1:02:30Tobi Lütke:I don't think it has. I mean, there's more cheat codes now. But I think the books still play the same role they have. What changed for me personally is that, 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.

1:03:09Shane Parrish:So what are like three old books that you've read that have fundamentally changed how you think?

1:03:13Tobi Lütke: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 is the highest token quality book in existence given for the length. James Burnham's books are fantastic, I think, and extremely relevant.

1:03:36Shane Parrish:What did he write?

1:03:37Tobi Lütke: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 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 do some random reading, and it's magical how it's somehow relevant to something I'm wrestling with. I rant books just in general, the lessons of philosophy, the lessons of history. It's, of course, the end-of-life distillation of it all. but his longer work is good. Fiction and foundation series is so good.

1:04:21Tobi Lütke:You read the three body parlor too, right? I guess that's sort of tripping into older book now too, but that's a recent sci-fi, which is incredibly good.

1:04:30Shane Parrish: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?

1:04:38Tobi Lütke:Success is just 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 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.

1:05:11you

From the publisher

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!

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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

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*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.
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