The Exchanges

Q Where did your love of reading come from?

A It came pretty late. I'm, so I, I'm actually dyslexic, so it's actually hard for me to read, and I read very slowly. Um, so I, I didn't read any books for the first sort of 20 years of my life, and, um, then I, at some point, I challenged myself to, uh, Read a book fully, and, um, there was, um, a wonderful book called Cryptonomicon by Neil Stephenson. Still one of my favorite books. And, um, uh, I, I, like, this was so good of a book to pick up first, um, and it was sort of almost random, because, you know, I just learned so much from this book. It's, it's, it's like, it's, it's a piece of fiction, but you learn so much about, you know, this, like, even cryptography and all these things that are relevant to me. And, um, You know, I, I, I started picking up more and more books, and just sort of devouring them from that point on, and I, you know, I found, um, books are sort of the closest you'll ever come to, uh, finding cheat codes for real life. It's like, you can access the entire learnings of someone, someone else's career, and, you know, sitting down for, you know, what is it, 12:14 hours, if you're, if you're a slow reader. So, I read a lot.

AI assessment note: “I challenged myself to, uh, Read a book fully... Cryptonomicon by Neil Stephenson.”

Q What have you learned from going back and reading that? Not, not about outcomes of decisions, but maybe more about the process by which you use to reach a decision.

A Yeah, I think, um, uh, Kahneman calls it hindsight bias, right? Like, we have a very, very strong, uh, bias to, uh, um, underestimate how difficult it was to make a, um, uh, decision and, and, and really, um, um, Uh, just, just, just treat difficult decisions that were made as if they were obvious all along, because you now have obvious additional information afterwards, right? Um, so it cures you of that to a degree, which is really, really, really helpful, um, for anyone who leads people. Um, it's also, um, like I've just learned, you know, every single time I got a decision wrong, uh, which just happens, um, Like, I found that the piece of information I was missing was actually totally available to me, and I just, you know, I, I just didn't go get it.

AI assessment note: “I found that the piece of information I was missing was actually totally available to me”

Q What have you learned from going back and reading that? Not, not about outcomes of decisions, but maybe more about the process by which you use to reach a decision.

A Yeah, I think, um, uh, Kahneman calls it hindsight bias, right? Like, we have a very, very strong, uh, bias to, uh, um, underestimate how difficult it was to make a, um, uh, decision and, and, and really, um, um, Uh, just, just, just treat difficult decisions that were made as if they were obvious all along, because you now have obvious additional information afterwards, right? Um, so it cures you of that to a degree, which is really, really, really helpful, um, for anyone who leads people. Um, it's also, um, like I've just learned, you know, every single time I got a decision wrong, uh, which just happens, um, Like, I found that the piece of information I was missing was actually totally available to me, and I just, you know, I, I just didn't go get it.

AI assessment note: “the piece of information I was missing was actually totally available to me”

Q Um, last question that I want to ask you is, what do you think of algorithmic decision making and where we're going in that sense, in terms of not only scaling and running an organization, but in terms of machine intelligence, if you will?

A A very complex set of thoughts, um, on, on, on this. Um, but I, I, I'm sort of in the, I think broadly, I'm probably in the Gary Kasparov kind of camp of thinking, um, One thing he points out, which I really, really love, is that, uh, obviously famously lost to Deep Blue in, in, in, in chess, and he did not like that one bit, so finally he wrote a book about what that experience was like, sort of, 20 years later. And one thing he did point out is that, um, the discussion is framed too much about people against machines. Um, it's, it's a narrative slight, slight of hand. It's not really what we're seeing in the world. Um, it's, it's, uh, it potentially even comes from this sort of deep blue experience, right, because there was the best grandmaster in the world, the world champion, playing against a computer, and the computer came out victorious. But that's not the way reality works, because, uh, uh, what he says is, if even a reasonably good chess player with an engine plays against just an engine, it's always the human and the engine who will win. So it's the, we are interested in trying to get the best result, right? And so I think humans assisted by technology are probably the thing that we should be going for instead of trying to replace people, um, so much. And I think we will see that effect significantly more. And in a way, that's kind of what Shopify kind of is, right? L…

AI assessment note: “I think humans assisted by technology are probably the thing that we should be going for”

Q What's the most common mistake that you see people make over and over again?

A Um, uh, it's, it's, it's, uh, people are terrible at deciphering, um, uh, cause and effect, uh, or even correlation, um, versus causation, right? Like, again, I said this earlier, um, systems thinking is the best cure for this kind of thing, but, um, like, there, there isn't always a cause for things. There, there, much more often there's a system that just reinforces something, like, everyone's complaining, why is everyone, like, why is all of them, The word of business, um, so short-term focused, well, it's because Wall Street wants quarterly reports, right? Um, so, you know, it's, it's, it's, it's system reinforcing the thing that you want to fix, and then people love putting hacks on easily identifiable problems, um, and then think the problem goes away, even though the full thing that's reinforcing this is not, is not being addressed. So that, that's, that's what I see, um, see a lot.

AI assessment note: “people are terrible at deciphering, um, uh, cause and effect”

Q Can you expand on that? Like, why is the, the barrier to entry increasing? Is it because of the data that the company is Accumulate, or what, what are the?

A It's not even that. It's just like, what kind of qualifications do you need, um, to, uh, be a tech, uh, co-founder, right? Like, uh, like, what kind of things do you have to put on your application to Y Combinator to be even considered, right? Like, you essentially have to spend your life in a, in a, in almost a perfect, um, linear arrow towards this goal. Um, you have to have the right skills. Ideally, you have to have, um, Um, all sorts of extracurricular kind of things, which, you know, are, as we all know, are associated with middle or upper middle class upbringings, because that's where people have time for all these extracurricular kind of, ah, like things that give you an advantage, then. And so, um, you, you have to be, uh, without lots of dependence, because you're gonna go into a hole for a decade to build a company. I suddenly had to do that, and, you know, um, That, that was good then, but could I do it again now? Probably not. I forget. So there's a lot of kind of requirements that exist. So it became actually cheaper, uh, to start companies for a ever decreasing circle of people, um, the more and more fortunate. And so I, um, what I love and what gets me out of bed every day to, to do Shopify and work on it is, um, that it's a counterforce to this, right? Like it's, what, what, what Shopify allows People to do is like have, you know, for 29 dollars a month get som…

AI assessment note: “It's not even that. It's just like, what kind of qualifications do you need”

Q Is that what it's called? Okay. So it's got a trust battery. Like what is on this, this list?

A So it's a, um, a friend of mine put, put me on to the idea, Luke Levesque. Um, essentially the, like, it takes a long time for people to learn how to work with each other. So I always look for ways to short circuit this kind of process as much as I can. So in this particular case, I, I just wrote out the things that people otherwise take a year to figure out about, uh, uh, about me, like how I work, how I think. Um, and, uh, so that's on our internal wiki and it's under, you know, You know, wall.jobify.com slash Tobi, although that's an internal, um, address, and, um, everyone can, who has their first meeting with me can kind of figure out, you know, what's probably a good thing to do and what isn't a good thing to do, so I think it's very, very helpful.

AI assessment note: “I just wrote out the things that people otherwise take a year to figure out”

Q Is there one lesson from history that stands out when you think of how to go about making a great company that you think may be underappreciated?

A Yeah, um, for sure. Um, to me, this is such a big topic. Um, So almost all companies have been created, um, in a world that can be described as, um, complicated problem solving, right? So like, you look at Henry Ford's, uh, factories or, or, you know, something like Bethlehem Steel or whatever, and essentially you, you have this incredibly, um, um, long chains of cause and effect where, um, you know, at one point you put, um, iron ore in and, and sheep and, um, or at least, uh, sheep wool. And then on the other side, a model T comes, comes out. And every single step in this process, um, was, uh, like this, this got popularized by a guy called Frederick Taylor, um, um, under the name of scientific management, I think. Um, and, um, uh, so, so break this incredibly complicated task down into a single task, which can be individually taught and can be done by absolutely anyone. And then, um, Um, you do this. This really is the story of industrial revolution.

AI assessment note: “popularized by a guy called Frederick Taylor, um, um, under the name of scientific management”

Q And you did some of that during COVID, right, with the rapid grants?

A Yeah, I mean, Rapid Grants was great. I mean, there's an entire sort of emergent field led by a bunch of, like, non-academics or sort of academic patients, sometimes founder-builder types, called progress studies, um, which, um, says a very basic thing about, hey, we should probably study how progress happens, like, because it's probably slowing down a lot right now, and we should kind of have a theoretical framework by which to Just, like, you know, like, meta-academics is probably almost a, a better, uh, term there, um, before Watchers and Watchmen, so to speak, and, um, um, I don't, I think that's very nascent and probably not, like, university-loved, and potentially, um, what I, I don't know if it can get off the ground, but, like, we did some experiments with fast brands and some other things where we just said, like, hey, with enormous time pressure, Give us a proposal and we'll tell you if you better get money for it in, like, a couple of days, because that was really needed at the beginning of COVID.

AI assessment note: “Yeah, I mean, Rapid Grants was great. I mean, there's an entire sort of emergent field”

Q You said in the past that, I want to read this so I get it right, people should make decisions based on the decision they assume the company in 10 years from now wishes they would have done. Can you expand on that?

A I love, um, having these questions as one of governing, like, like, like putting it as an input there, um, um, or at least as a, as sort of, um, a linting rule, if you will, um, On the quality of the decision. It's very easy to do what's popular right now and, and, and, and commit yourself to more pain in the future. It's, um, it's, it's, this is always, like, almost every important decision that doesn't have an automatic ends up being a little bit of a, do we do what's right or do we do what's easy, right? Um, those are the only real decisions that people get hung up on outside of, uh, Hey, we see no path forward. We will have to eat shit, which is like, which is the pile we should start nibbling on. It's like, that's, that exists too. I mean, especially in times of crisis or sort of wartime, um, um, both will also end up becoming, um, discussions, but like, usually it's the, it's in the form of, um, Are we allowing ourselves to do what's expedient or easy? Uh, and I want to have good heuristics for spewing towards best decision overall in the long term. Um, ideally, again, at, especially at this strategy level and, um, people systems levels, uh, it should, these things should be along the lines of a, um, long-term benefits and inclusive of some of the secondary and third The tertiary effects that are predictable, and so this is why I try to, um, ask people, hey, I found this …

AI assessment note: “I want to have good heuristics for spewing towards best decision overall in the long term.”

Q Does that experience of, like, not being able to make payroll or being desperate to get money to make payroll, does it change how you run the company today?

A Oh, yeah. It's, I mean, it just, it, you just have to, I had to learn to make every dollar count, and it's hard, it's a hard habit to, to, to, to shake, right? Like, um, it's, uh, you know, I actually think it's one of those kind of lessons that you get deprived of if you go straight to an, into a startup accelerator, and then go and, uh, Get, uh, the Series A funding with not a lot of effort, and, you know, like, every company that's being funded, you're gonna get a lot more of whatever they were already doing, right? Um, so, if the company at this point of getting funding was already good at making every dollar count, really understood its market, you know, like, then you can kick, kickstart a story that produces almost a hundred percent growth for a very extended period of time, um, And, uh, you know, in some cases you're actually, um, fueling something, some completely different behavior. So, I think it helps a lot.

AI assessment note: “Oh, yeah. It's, I mean, it just, it, you just have to, I had to learn to make every dollar count”

Q Aside from being a learning kind of organization or learning culture, what other words would you use to describe the culture that you're instilling or trying to get at Shopify?

A I've mixed opinions on culture. You know, I think, I think we're getting dangerously close to the point where a lot of people think that culture is this sort of manageable and, uh, it is just something that managers have to kind of own in some kind of form. I think culture is just the sum total of all the people who work with each other. Um, in fact, um, Shopify is super happy with internal multiculturalism. You know, one thing, again, we are a Canadian company, and one thing Canada is, like, increasingly known for is that, um, you know, for the last 3040 years, Canada has run the biggest worldwide experiment in multiculturalism, and, um, by the way, it worked well. Um, in fact, it probably works better than the alternatives, and that's a very, very, sort of, important lesson Canada is starting to teach the rest of the world, because I can tell you, When Germany, 10 years ago, had this conversation about, hey, should we double click on assimilation or multiculturalism? Um, no one talked about the example that Canada has actually been running this experiment successfully. So, um, that's something that I find so inspiring about Canada, especially as an immigrant from Germany. And, um, um, that's something we really, really like within Shopify as well. Every one of our offices has different culture, and that's okay. There's no Shopify culture. I know there's, like, companies like …

AI assessment note: “Shopify is super happy with internal multiculturalism.”

Q about, what he used to spend time on that he now sees as a waste, and how he fixed his sleep. Longtime listeners will note this is the second time Toby has appeared on the show. The first time was episode 41, which I think was five years ago, which feels like generations ago. It's time to listen and learn. How do you lead through such a period of volatility?

A Uh, I mean, it was, uh, um, I don't know if I did a very good job of it, but like, I certainly did it. Like, I certainly had to deal with volatility. That's true. Um, I think Shopify sort of captured their imagination, uh, like of everyone, um, in this massive swing towards digital services, um, and, um, um, uh, market beta caused Shopify to be extremely, uh, Exposed and, like, just, uh, you know, on everyone's mind, and then, and then, uh, the, the pullback was equally drastic, which was a fascinating experience eternally, right? I guess lots of discussions, you get always, everyone's gotten messages from their parents about, like, hey, what's going on? I mean, I, I, I've never thought that, um, companies are, and, and, and their stock have that much to do with each other, right? Like, it's, it's, uh, It's, it's, it's related, but not, ah, like, like, no one in a company works on the stock, um, if things are going well. I think if people start working on stock, things are actually, like, that should be a sign that things are going pretty poorly in the company. Um, and so, um, it's been, you know, it's been a challenging time to, for, for, for leadership, because you'd, like, you kind of never knew what kind of puzzle box planet Earth would drop onto your desk in the morning, and, um, um, I think, well, the, the things that have been important during that time, the things that …

AI assessment note: “make a product that's really appreciated by entrepreneurs”

Q Coming back to the revision to the mean, one of the other ways, so best practices is a way to sort of, um, start the path towards revision to the mean. Another way would be bureaucracy. How do you fight against that? You're 8000 employees now. How do you fight against...

A It's good to know more, actually. Um, it's, um, well, I mean, Yeah, like, I mean, subtraction helps a lot. You know, sometimes, again, bureaucracy happens because people put sediment layers of bureaucracies on top of each other, like, ah, like, I have found people don't actually describe things that work really well as bureaucracy. I think bureaucracy, um, and process are almost terms that are exclusive to the things that did not work. Um, so if top people talk about some area having a lot of, um, bureaucracy, it's actually usually an area that if you apply some first principle thinking, you might actually find a way of, um, just streamlining this enormously, right? It's not all bad. You know, like, this, this is, It is fundamentally extremely hard to, um, build things in groups of people, right? Like, there's very few very, very important things that can be done by individuals anymore on, on, just, we, we've almost mined the entire value space. Like, like all, basically all the minerals that are, like, like on the surface have been mined out, right? Like, so, Oh, like, minerals of value. Um, the, um, Other, like, the, the, the valuable minerals are now fairly deep underground. For that, you need organized groups of people to build the infrastructure, the support and air tissue, the safety, like, you, you, you, you have to, like, the automation, you have to build, ah, high-tech…

AI assessment note: “subtraction helps a lot. You know, sometimes, again, bureaucracy happens because people put sediment”

Q What technology are you most excited about right now?

A Um, well, I, I would say, um, I mean, look, I'll say Metaverse and Emma's Rolling the Ice. I think the Metaverse is like a Hemingway implementation. It's like nowhere, and then suddenly everywhere, and it's like, it's hard to predict where it's going to be. We definitely have platform requirements around glasses, but like, they are always, like, The labs are yielding words. Um, we, we, we know how to, I think we know how to make the lasers for the glasses now. Mine is maybe red. Um, and like, like, this is really where academia shines, and, and there, there's a lot of practical, um, uh, industry, industry-relevant work happening. Um, uh, so, so that is going to happen, and I'm excited about it. Uh, I think that, um, uh, it's, It, it'll just be clear that it's openly going to that word. Um, um, it's not as far away as to think. Right now, you've got to say, like, machine learning. So machine learning has been unreasonably effective already, um, but, boy, do Transformer models change everything. Like, it, I, it, it's another one of those, they, Transformer models feel a little bit more of a vocational than academic, and, like, they're probably not as good an analogy to the brain as, Maybe some of the other, like, approaches, or at least it's not as pure play as, um, some of them. Um, but, but like, it's crazy what's happening. Like, it's crazy. And another thing that I love about…

AI assessment note: “I'll say Metaverse... Right now, you've got to say, like, machine learning.”

Q You were part of the core Ruby team, right?

A Exactly. Well, yeah, core Ruby on Rails team. I used the software. I loved it. It's a wonderful story there, too. So people were using, like, people were looking at this, this online store, and it provided some legitimacy that Ruby on Rails was real technology you can use for real The, uh, real life book. And, um, asked, he came to me and asked, hey, can I license this software? Can I, can I use this? And so, um, based on this, what we did, we sat down and turned, um, uh, this online store into what is now Shopify and people come to us and, uh, um, you know, you, you, you sign up, you tell us about your products. Um, you get an amazing looking website, uh, online store that just works really well and it's really optimized around selling and, and ease of maintenance and so on. Um, you get everything you need. Um, so I had to make a copy of my passport and fax it to American Fork Utah, um, to get a merchant account. Um, that process took two and a half months. Of course, after you sign up in Shopify, you just have a merchant account, and therefore you can take credit cards and these kind of things. So it's very easy to use. It's what a lot of people use to get into entrepreneurship, to start their own businesses, and that's what we do.

AI assessment note: “Exactly. Well, yeah, core Ruby on Rails team.”

Q How do you think about employees in terms of process versus, or process and bureaucracy, uh, in terms of being adoptable and nimble and the organization that you want to run?

A Yeah, I mean, that's, I have lots of thoughts on process. I actually think, um, process is probably one of those things that, uh, the business world of right now will be most embarrassed about, um, uh, when, when we look back, it's, um, it is amazing how little, what's, what I refer to as good process exists in most businesses, right? Because, um, um, so, so you can, you can actually Like, there's three kinds of process. Um, there's a kind of process that, um, makes things that were previously impossible to do possible. That's good. And there's a kind of process that makes something that was previously possible significantly simpler, which is also good. Like make it 10 times better. Ideally make a process that makes an entire thing that previously took like days, make, make, make this light white. Um, uh, that's, that's good. And then there's everything else. And I, I bet you 99.9% of all process that exists in corporate America is the third category. Where, which is actually just telling people to behave slightly different from what common sense tells them to do, right? Um, so we have lots and lots and lots of examples where we, um, where we just avoided having to create process by just changing the environment in which we all spend our time in. Um, like changing the way the offices work, change, you know, um, It's, it's, it's, it's, well, it's interesting, I don't know, it's …

AI assessment note: “I have lots of thoughts on process. I actually think... there's three kinds of process.”

Q Would you say you're lowering the friction of starting an online business and giving people the tools that they can use to compete against bigger, more well-funded infrastructures like Walmart or Amazon or?

A Yeah, exactly. I mean, look, um, again, I grew up in the nineties, right? So, um, my, uh, um, view of what the internet should be is very much, uh, inspired by sort of what happened when the internet sort of first came around. Like I remember when the internet came to my My city, right, which sounds hilarious now. The amazing thing about that was, um, before that point, if I wanted to somehow talk to many people at the same time, I had to either be a ham radio operator, or I had to, like, call into some radio show or game show or something like this, and that was the only way how you could really communicate, unless you knew someone's phone number with people who aren't right next to you. And so then, um, Um, the internet came to town, suddenly everyone couldn't participate. You know, like, you could put your own thing there. You, I made my own website, and I probably talked about video games. And, um, uh, that just felt super liberating, uh, to me, and to me, that's what the internet does. Now, this sort of gets into the problem of the internet right now. Um, What happens, and what always happened, um, if you're a small village somewhere, or medium-sized city, um, and you have this thriving community of different stores, merchants, people, like everyone, like this collision of ideas which cities are, um, and a Walmart starts in your city, A couple, a couple of people will stil…

AI assessment note: “Yeah, exactly. I mean, look, um, again, I grew up in the nineties”

Q What are the other mental models that you use to either run Shopify or interact with other people?

A As you know, like I, uh, I, I read lots of books. I'm fascinated with the concept of mental models. I, I, I, you, you've listed, um, hundreds of, uh, over a hundred on your, on your page. I know you're working on a book on the topic. Um, uh, I, there are so many more. There are so many metaphors that come from, uh, different fields. Um, you know, like I sometimes feel like I learn more about, uh, um, how to build a great team from, from learning To play an instrument than from, you know, any kind of managerial kind of, uh, training or something like this, you know. So, um, I, I just think this is the way we become better at anything. We, like, there's a, um, one of the, when I, when I sit down with, um, especially sort of younger, um, engineers, designers, and so on in a company, and they ask me, like, how to get better, um, Everyone is always really quite, like, like, people know how to get better at their craft, but it's actually, I, I think most cases the best way to get better at what you do is actually go broader, like, just learn, add the other skills. Like, we, we have a, um, we have a reading, like, a library, like, essentially a book club across Shopify. I, I, uh, curate the books that are in it, and, um, like, there are books that you have absolutely nothing to do with business, like, drawing on the right side of the brain, Understanding exposure, you know, like, um, …

AI assessment note: “learn more about, uh, um, how to build a great team from, from learning To play an instrument”

Q I want to come back to something you said earlier in that answer, which was you studied how great companies are made. Give us some of the lessons. You got to expand on that. What does that, what happens?

A This is a big topic, um, you know, because it's, it's usually, it's actually tricky to, to, to get these pieces of information. My, my best, my, my absolutely favorite way of doing it is, like, I, I tend to go backwards in history, and then try to build my own picture from multiple viewpoints, right? So, um, I got fascinated with, for instance, the industrial revolution, and sort of the time of a railroad, so, so, so you start reading the various autobiographies by the major players, and, Even though those tend to be very sanitized, they usually are very accurate explaining sort of a situation that existed, um, that in which they were solving problems. And, um, uh, then you can sort of rebuild this saying, okay, why did that work? Like, like, how did, why, um, like, how did it happen that only Rockefeller saw that, um, the money in oil was in the refineries, not in the wells, right? Like that, that seems, um, Like obvious, but it was only one person who figured it out, right, during this time. Um, and so, um, you, you're trying to reconstruct these kind of situations, and then you see, look at them from multiple angles, and you realize, okay, here was the, the, the science, and, um, you know, that's a lesson, and that's something to, to, to, to, to take, and next time you analyze the situation that you come across yourself, this is, uh, something, a new model you can compare, u…

AI assessment note: “only Rockefeller saw that, um, the money in oil was in the refineries”

Q I want to talk with you about two ideas that have left an impression on you. The first one is Paul Graham's essay on conformism. Can you talk to me about what insights you drew from that?

A Okay, so let me see if Enver reviews this. Um, I mean, I have to say, like, Paul's essays are Like, they're, they're kind of this wonderful, like, I find they're always insightful, like, they're always gems, and, and, and, and, um, I, I find even sometimes the same essay actually, like, this valuable reading at multiple stations. Like, I, I think, like, so, so, so, so, so his writing is brilliant. Um, very often he, um, Does this thing where, um, again, he does the thing that language is best at for, like, putting a couple of labels to things that are being observed in general, but, like, afterwards they make them easier to reason about. And he always, like, builds up these pretty arguments around them which can serve as almost onboarding to the idea. Like, it's, it's like, I mean, mental bottle faking, that's what I'm saying. Um, I, I find, um, Um, so in, in this, he, uh, draws, if I remember this right, um, uh, like, uh, one of those, uh, four panel grids where one axis is, um, um, um, how independent, um, minded you are and, or how conformist you are on the other side, and then sort of a passive-aggressive, um, standard separation. And, and, and, um, you know, I think this is, it's valuable because I think, um, uh, you, you can, you can sort of put a relation density crowd, um, like over this, and you would sort of, I think he makes the argument, um, that, that most people a…

AI assessment note: “in this, he, uh, draws, if I remember this right, um, uh, like, uh, one of those, uh, four panel grids”

Q So you've gone from like two to 4000. What, what kind of lessons have you learned from growing the company? Um, how did you scale it?

A Yeah. I mean, it's interesting. Um, so, so Shopify is now a larger company than, you know, the city I grew up in, right? Like, so it's, it's, it's the largest community I've ever been part of. Um, and, um, it is an incredible, uh, it is really an incredible journey. I think this is the one time these kind of sort of hyperbolistic words actually are appropriate. Um, but, Um, from my perspective, it kind of didn't feel that different, um, all along, um, in the, in the different steps. Like a company that grows really fast feels entirely different every year. So I just gotten really comfortable, um, having essentially a new job, um, every year. And, um, to me, the most important thing was to make sure that every new version of Shopify was slightly better than the one before. And so, um, you know, and ideally across all the kind of things, like better at the things that we were good at, and fewer of our weaknesses we had before. And, um, there was, there's great purpose that comes from, um, uh, just having like a mission that is kind of like, kind of good, right? Like this is, this might get into It's, it's, it's an interesting topic, but, you know, one thing which really helps about building Shopify is if Shopify succeeds, no one loses. Right? It's, it's like there's zero.

AI assessment note: “I just gotten really comfortable, um, having essentially a new job, um, every year.”

Q You're known for running, uh, Shopify is known, I guess, for being a very resilient organization. Uh, one of the stories that we, we talked about the first time we ever had a conversation was about you moving buildings. Can you tell us that story and what happened and why it happened the way it did?

A Yeah, um, I, I, I've always been a fan of, I mean, this is called, Nassim Taleb finally gave this concept a name with his book Anti-Fragile, right? I firmly believe that if you want an organization that lasts, you need to be okay with, um, bad things happening. And in fact, I think the quality of an organization is not how much it, how, how good it is at preventing, um, bad things from happening. Um, although that's, it's a useful skill, but I don't think that's necessarily the quality of organization. The quality of organization is how quickly it does react to bad things happening. So, um, uh, this started very early with, uh, you know, long before it It, it, it became cool.

AI assessment note: “I've always been a fan of, I mean, this is called, Nassim Taleb”

Q But this is one where it's super important that we find a way to rerun, or get rid of, or change. How do we do that?

A Yeah, I, I mean, I, I mean, we, we actually, um, so, talking about secondary effects, sometimes we use, very often secondary effects are really like the opposite of the primary effects, right? Like, um, a lot of our carbon issue in the world comes from, uh, the environmentalists convincing the world that even though we're building a Um, economy that required nuclear power, we could somehow do it with coal instead, and, um, um, and oil. Now, I think we got the scorecard for that. This really worked very poorly, um, and I don't, I still think it's an expense that Planet Earth needed to run, but, like, we did. And, um, um, until maybe a year ago, it seemed like we actually were really not looking at this, um, because, so this, this, I mean, Well, I should make this explicit. The secondary effect of us not building nuclear power plants is that now we have climate change, right? So, um, primary effect is environmental movement. Secondary effect is climate change. Like, chew on this for a bit. Um, ah, again, everyone in the, this movement wanted to do what's best, um, the best of their information, but like the secondary matter. Now, take another one. Russia invites Ukraine, which seems to be a recurring topic here. Everything in primary is bad. Secondary effects. Many, many, many, many of them are bad. Like, there's a secondary effect of everyone having to look at their energy polic…

AI assessment note: “talking about secondary effects, sometimes we use, very often secondary effects are really”