Invest Like the Best with Patrick O'Shaughnessy - Daniel Ek - Enabling Creators Everywhere - [Invest Like the Best, EP. 242]

Episode Date: September 14, 2021

Today is a special episode because it marks five years since I released the first episode of Invest Like the Best. Over those years, I’ve learned so much from so many investors and builders, but today’s guest may have taught me the most.   Daniel Ek is the CEO and founder of Spotify, and I find him to be one of the most thoughtful business leaders in the world. Daniel is the perfect guest for this special occasion because he exemplifies the curiosity, humility, leadership, and dogged determination that I think characterizes the best investors and operators.   In our conversation, we discuss the differences between the world of bits and atoms, how Daniel gets up to speed in challenging new fields, and why Europe might be a sleeping giant about to wake. We then bring the discussion back to Spotify, the evolving creator ecosystem, and Daniel’s frameworks for leading the business into its next chapter of growth.   Over the past 5 years, we’ve produced more than 300 of these shows and reached nearly 30 million people. I am deeply thankful to the guests who’ve been willing to share their knowledge with us all and even more thankful to everyone who has taken the time to listen and learn alongside me. This has truly been the greatest pleasure of my career, and I don’t plan on ever stopping this journey.   Now, Please enjoy my conversation with a great friend, Daniel Ek.   For the full show notes, transcript, and links to the best content to learn more, check out the episode page here.   ------   Invest Like the Best is a property of Colossus, Inc. For more episodes of Invest Like the Best, visit joincolossus.com/episodes.    Past guests include Tobi Lutke, Kevin Systrom, Mike Krieger, John Collison, Kat Cole, Marc Andreessen, Matthew Ball, Bill Gurley, Anu Hariharan, and Ben Thompson.   Stay up to date on all our podcasts by signing up to Colossus Weekly, our quick dive every Sunday highlighting the top business and investing concepts from our podcasts and the best of what we read that week. Sign up here.   Follow us on Twitter: @patrick_oshag | @JoinColossus   Show Notes (00:03:37) - [First question] - Building atoms versus bits and if we’re destined to return to atoms (00:08:04) - What makes early-stage atoms companies more challenging to build (00:10:20) - Whether or not we’re starting to see cross-pollinating of infrastructure companies into other sectors (00:13:00) - His process for learning about new fields when he knows nothing (00:16:12) - Big and interesting problems that we will need to solve  (00:19:35) - The nature of healthcare’s technological adoption compared to other sectors (00:24:13) - Downstream unlocks of collecting and observing big pools of data (00:30:00) - What he has found effective about taking an idea from 0 to 1  (00:33:40) - Lessons learned about compounding change and staying patient (00:37:17) - History of European technology and its unique regional characteristics (00:42:40) - Cultural and continental traits that may make Europe a technological leader  (00:45:42) - Characterizing the major lessons learned from his time at Spotify  (00:50:31) - How artists are changing the ways they connect with their fans via Spotify (00:55:44) - What he would change about the legacy music industry given today’s tools (01:00:15) - The influence global exposure has on internet companies and creatives  (01:03:02) - Interesting observations about the recent explosion of podcast popularity (01:07:36) - Working with, carrying, spreading, and maintaining Spotify’s sacred source (01:12:37) - Ways we can improve and sharpen our decision-making skills

This episode of Invest Like the Best is sponsored by Canalyst. Canalyst is the leading destination for public company data and analysis. Founded by a former byside analyst to encounter friction sourcing, building, and updating models, Canalyst is now used by over 400 institutions, including the largest money managers globally, and by a number of guests on the show. With detailed company-specific models and data on virtually every public company, Canalist clients are able to ramp up faster, update models instantly, and incorporate the highest quality fundamental data into any workflow. If you're a professional equity investor and haven't talked

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different temperature. I was so impressed after using 8th Sleep that I became an investor. To embrace the future of sleep and get $150 off your new mattress, go to 8Sleep.com slash Patrick or use the code Patrick. Hello and welcome, everyone. I'm Patrick O'Shaughnessy and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. Invest like the best is part of the Colossus family of podcasts, and you can access all our podcasts, including edited transcripts, show notes, and other resources to keep learning at join colossus.com. Patrick O'Shaughnessy is the CEO of O'Shaughnessy Asset Management.

All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of O'Shaughnessy asset management. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of O'Shaunice asset management may maintain positions and the securities discussed in this podcast. Today is a special episode because it marks. five years since I released the first episode of Invest Like the Best.

Over those years, I've learned so much from so many investors and builders, but today's guest may have taught me the most. Daniel Eck is the CEO and founder of Spotify, and I find him to be one of the most thoughtful business leaders in the world. Daniel is the perfect guest for this special occasion because he exemplifies the curiosity, humility, leadership, and dogged determination that I think characterizes the best investors and operators. In our conversation, we discussed the differences between the world of Bits and Atom,

how Daniel gets up to speed in challenging new fields, and why Europe might be a sleeping giant about to wake. We then bring the discussion back to Spotify, the evolving creator ecosystem, and Daniels frameworks for leading the business into its next chapter of growth. Over the past five years, we've produced more than 300 of these shows

and reached nearly 30 million people. I'm deeply thankful to the guests who have been willing to share their knowledge with us all, and even more thankful to everyone who has taken the time to listen and learn alongside me. This has truly been the greatest pleasure of my career and I don't plan on ever stopping this journey. Now, please enjoy my conversation with a great friend, Daniel Eck. So Daniel, I was so excited that you agreed to do this with me. It's the

five-year anniversary of the show, which is totally nuts. It's led to all sorts of cool things in my life, including meeting and learning a lot from you. The reason that I hoped to do this with you is as a person interested in a lot of the same things, I would say you've taught me the most in the widest variety of areas. And because of that's how our kind of relationship has gone, I figured I'd structure this conversation in the same way, sort of like a topist style conversation, a lot of interesting different topics, not just Spotify. An odd and interesting place to begin is in the world of atoms. So the world has been obsessed with bits for a long time. And I know you personally, obviously, have done very well in that space and remain deeply interested in it, but have developed

this burgeoning interest in the world of atoms and harder technology problems. Maybe you could just begin by riffing on that concept, whether or not we're due for a return to focus on Adams versus Bits? First off, what a huge compliment you paid me there. I'm not sure I deserve it, but it's also a huge honor, obviously, to be here on the five-year anniversary. And I too have learned a ton from you and from listening to all your amazing podcasts with guests, so keep them coming. I think right now it's quite an interesting period of time that we live in. I mean, most of the focus today, I call it bits versus atoms. Most of the focus today in the world ends up on bits, meaning we talk about an internet company,

new digital companies. Most of them are entirely digital at this point. And it's been pretty clear. I think last time I was here, we talked about scale being redefined. And we now a few years later are looking at companies, more and more $100 billion plus companies have been created. You're seeing $10 billion plus companies being created almost. by the week now, which was kind of a unique milestone. I'm not even speculating whether that's

fair or unfair. Maybe it's a combination of both, but certainly scale has been reimagined and redefined, and people are now seeing that in a big way. But it's mostly been bits. And when I look at the world and I look out and I look at some of the largest problems in society that we're facing, almost all of them are atoms problems, or at least have a significant component, which is real atoms and not just entirely done by bits. So as I look at the opportunity sets and the problems and where I hope the next generation set of entrepreneurs will focus

is on some of these tougher problems, where you probably can leverage, of course, digital tools and products, etc., where you also have to unlock some real scientific breakthroughs in atoms. And climate change is an obvious one where we come into that. But healthcare is another one where we're dealing with an enormous hurdle as we have an aging population in most parts of the world, massive health issues, et cetera, that's now coming aboard. We're talking about enormous amount of broad technology that needs to be developed, whether it's

being infrastructure or transportation, et cetera. where we just have to move the world forward. And that is at least lately been catching my imagination because I think that much of what drove that bit revolution has been almost a standardization of sorts, these platforms we're all building on. Those are real technical platforms, but honestly also the just broad knowledge now that there is

on building digital companies. Everything from racing capital is now widely known, transparent truth on how you do it. It's widely established what a series A round looks like in B and C, which just created this enormous platform to allow a lot more experimentation. And the problem I feel with a lot of these Adams companies is the whole playbook on how to do them is completely different. And we're back to when I started digital companies, which is it was all opaque. Had to figure it out yourself. Yeah. And it wasn't obvious who to go to. from a capital point of view or even multiple sources to go to.

And it wasn't obvious what product market fit looks like or even the definition of that. And so it's just been enormously interesting for me and reminding myself almost of the beginning in that world. If you think about the early challenges where the playbooks are being written, they're not totally established. What do you see in common between some of these companies or entrepreneurs that you've talked to? What is harder for the Adams companies in the early days? Is it capital formation?

Is it harder to raise capital? Is it getting to first product? What are the interesting challenges that are much different than the digital side? There's a lot of them. And I think it's a whole ecosystem of things that needs to be built out in these Adams companies that are now well built out in the Bits companies that don't exist. So that's certainly one. But the second part is we've learned it's almost like the Bits companies, the general

formation strategies explore exploits. It is so cheap today to try out new experiments. The whole ecosystem basically does that. For any idea now on the internet, there's already today probably 100 different people that are trying to compete in that thing. And then on top of that, it creates enormous winner-takes-most dynamics where the succeeding company then creates economies of scale, It can go global, day one, and can, of course, scale hyper quickly based on all of these platforms that exist, like the stripes and so on and rails that the Internet is built on. If you go and send to the atom part, there isn't a minimum viable product oftentimes or that possibility. So you have to bet much more capital up front and in many case, many more years before you can come to market. So that whole formation on how you build a company is entirely different than a bit's kind of.

company. And then secondly, the same platforms that I spoke about, the Google and Facebook for marketing and promotion, the app stores, all these things that we now take for granted, the AWS, a lot of that infrastructure just don't exist for how you promote and market and distribute a Adams-based product. And let alone of these cases, it's not entirely clear that it's the consumer that you're marketing it to even. So you're looking like enterprise sales, or B2B the style sales on top of it too. So it's very, very different, certainly for a consumer person like myself to try to go in and learn and much more regulated, much more governments being involved in many of these fields too. Maybe we could pick an industry just as an example to sort of

dive into the specifics, whether that be steel or alloys or healthcare, you know, you can pick. But do you see some of the general purpose rails being built in this space? Like I think of GinkoBioWorks or something that seems to be a survey. like an AWS for medical research or something like this. Are you starting to see kernels of the infrastructure platform type companies in the Adams world? And what's one interesting example of your investigation so far? So in biotech for sure, you're definitely seeing that. I call it almost like the picks and shovels of being built into that field.

And there's a number of enormously impactful companies that are being built now that I think over the next few decades, you'll start seeing tremendous amount of progress in biotech. tech as an example that will stem from that just the number of experiments that a scientist will be able to do. We were talking before this about data scientists, but I remember the day when you had a data scientist work on an experiment for two weeks, and then you try it out in the market for two weeks, and then you go back to the drawing table and do it again. Then you could pretty much just do one single experiment at the time. And obviously today, the common norm is to run hundreds concurrent experiments. Some of them, the data scientists, aren't even aware of

because it was machine-generated experiments altogether to get every permutation of the answer. We are getting to that end in the bio world too, where we'll see some of that happening. But we're very much in the day where an experiment in many cases can take weeks, if not months, and it's done singularly, and we will be able to paralyze that, I think, over the next decade too.

So I think things like that will materially accelerate the progress of innovation, that we're seeing. But there are also a lot of structural inhibitors, maybe more so than the technology in itself, that makes some of that not happening. Like, for instance, how you commercialize research from institutions, it is a fairly opaque process to begin with. And a lot of those types of technology transfer needs to be solved, which is also hugely interesting things. Like, we are the equivalent of today for seed startups, we have safes and all of these things that are super easy standardized contracts. It's not the way at all in these Adams-based companies. But that's

part of what's fun. I think the good news is a lot of those things are lessons learned in the bits world that I and others hopefully can transfer over and try to use those to make sure we get a meaningful change in the slope of acceleration of innovation. What is your strategy when you're tackling one of these new spaces? And I know you've done this for a number of different verticals in the atom space, when you're trying to learn in day zero, don't know anything, need to know a lot and are interested in making an impact, whether that's with your dollars or with your time. What is your process? Like, is it mostly people-based? I know you're famous for him going on a listening tour for Spotify with a bunch of other CEOs and see how they ran their

businesses. What has been your process? How has that been refined for this latest interest in the Adams world? So I think the process has evolved pretty much over the years. Mostly, honestly, because we now have way more efficient tools to gather information. You and I are now speaking on a podcast. Ten years ago, it certainly existed, but not the wealth of podcasts that are now available to people. In my case, I find it's great because I can listen to podcasts at two times to speed, so twice as fast as a normal conversation. And I have amazing curators like yourself that are asking many of the questions that I would have wanted to ask.

and I now get the chance to do that and some that I may not even contemplated asking. So that's certainly been augmenting my fact gathering and experience gathering. But I think the unique thing for me is today I think most people can do that. And that's amazing just to erase the overall bar. But the unique thing for me is, and this will sound odd in this day and time that we live in with COVID, but I've always been willing to travel. It has been a unique thing. I will travel.

I will meet people. I will show up. I will spend the time necessary to get to the real insights. And it is a very time-consuming and very cumbersome things because you will go from pretty much being the dumbest person in the room for a very, very, very long time. And I don't think human psychology is geared towards that. We don't think it's fun.

I keep on doing that and I keep putting myself in very uncomfortable situations up until the point when it doesn't feel that uncomfortable anymore. And then, honestly, many years ago, was reading this book. I can't remember what it was called, but it was basically about how you learn. And it was talking about various famous people through history, U.S. presidents, et cetera, speaking about whether they learn from reading, whether they learn from listening, whether they learn from writing, et cetera. And my process has always been talking ironically.

So I'm one of those that learn by repeating the knowledge and have to explain it to other people in oral terms. Truthfully, what I also do is I surround myself with people who don't mind listening to me, trying to explain these concepts. And as I'm doing that, I realize I have holes that I don't know anything about. And when they ask these questions, I realized, holy shit, I forgot to ask this thing. And then I go back to the rabbit hole and dive deeper up until the point where I feel like it can answer most of the, the questions that people are asking me, and I can myself make sense, I invert it by basically creating an antithesis. So if I can invert whatever I know and explain why the opposite is not true, I usually have grasped the subject well enough. I love the idea of the best way to

learning something being getting to the point that you can teach it to somebody else and respond to their questions. It's kind of a cool challenge for everyone to do on some topic. As you've done this tour of talking and learning in the world of technology and atoms, what, What are the biggest problems in your view? Like, there's lots of different categories. We've kind of listed some of them already in the big fields like healthcare or specifics like steel. What are the biggest, most interesting problems that you've encountered that you think

will be really important to solve? So I think that they're highly different for each vertical, I would say. But if we take climate as an example, one of the unique things is we keep talking about technology. I would say that in climate, there's two groups of people, generalized speaking. So one would be the group that think we have to change how we behave. And the only way we can succeed in doing that is if we radically change our lifestyles and get to a more sustainable lifestyle.

And then you have the techno optimists that basically believe that all of solving a climate change needs to come from technology innovation. And we just need to invest more in that technology innovation. The reality is not very surprisingly that the truth is probably somewhere in between. We do have to change some of our practices, and we do have to innovate in some areas in order to achieve progress. Notwithstanding both of those things, I think the most interesting thing when it comes to climate change overall is the vast majority of the technology we need to drastically reduce our carbon footprint exists. It's not about innovating, and it's actually not even about changing our lifestyles either. It is a massive coordination problem.

it's simply too expensive for society as we know it right now as an incentive to scale these things fast enough. So as I look at steel as an example, it isn't that you can't make steel green. It is that it's very expensive to do so in a fast enough matter for it to have enough of an impact on our society. But the technology has been around since mostly the 60s and 70s for how to do that. It's never been tried on a massive amount of scale, but kind of reasoning from first principle, you would easily see that there's no major inhibitance from allowing it to do that. The hard thing, though, is to, given all of the other opportunities, how do you create a coordination of a bold enough ambition, the best possible talent in the world, and a sheep enough and long-term

enough capital source that could provide the funding necessary for a project that if we're going to succeed with it is probably $100 billion plus. The flip side of that would obviously be that you're talking about 7 or 8% of the world's admission in one though that's totally possible to change. And you can even as an output create it at pretty much the same price as the current steel when it's at scale too. So it's not even a matter of, hey, this needs to be much more expensive than current steel. You need automation. You need electric art furnaces. You need a bunch of other things that are real cool technology, but it's been done before. What do you think about the world of healthcare where it seems like if we were to

apply that same idea, has the technology to solve the problem been around a long time or not? It seems like healthcare is kind of a mix. Like there's some things that we've known about for a really long time. There's something that are just completely brand new and feel very sci-fi, whether that's gene editing or the MRNA stuff with COVID or whatever. And I know you spent a lot of time here too. How does healthcare feel relative to something like climate, which may be about improving efficiency of existing technologies versus completely new de novo technologies? Again, very different. The whole stack of healthcare looks very different. And by the way, both of these, when we're talking about climate and when we're talking about that, the reason why

they're different when people would say, well, tech isn't that kind of the same? We're talking about industries that are in the trillions of dollars, if not tens of trillions. So obviously, these are enormous industries. Healthcare, if I'm not mistaking, in the U.S. is the number one employer of people. And it's projected to overtake the entire working population if the growth of healthcare keeps going as it's going. So it's going to be the only employer in the future, basically, which obviously isn't sustainable. So, I mean, again, there's a lot of myths around healthcare that I think is quite

interesting. So there's been a lot of debates about where's the cost, is it the drugs? And people try to go after that. It turns out that it's not really drugs that is the major cost impediment in healthcare in the U.S. Instead, to cut to the chase, it's really all about all the amount of people that's needed in order to deliver care. But you can imagine that maybe perhaps the right solution is some sort of automation of all that and some sort of automation of just creating more efficiency, kind of like we have done for transportation and so on, the Uber for healthcare, et cetera. And that's certainly plausible. And there's a bunch of other people that's trying that. And we have doctor on demand. And we have equivalent businesses doing some of that stuff too.

But I personally believe that the real solution is go back to first principles and ask, why do people get sick to begin with? And where in the funnel of all of this does the cost occur? And when does it become expensive and when this become hard to treat the patients? And you realize that the actual solution to healthcare in the end has to be that we have to go from reactive, which is the whole system, to proactive. Many more of the issues has to be solved ahead of there being a problem, not after, because the cost will be dramatic. higher to fix the ones the problems there. But the whole industry and the whole healthcare system is built on discovering the problem when you have the symptom. The problem is when you have the

symptom is usually quite late in the cycle. And to do that then needs a whole new diagnostic system that probably don't exist today that would generate a lot more data that would allow us to understand a lot more and predict what kind of possible diseases you may get in the future. And then obviously invent entirely new therapies for how to deal with those things and protocols. And then on top of that, we have entirely new alignment problems in the healthcare industry. Who's supposed to pay for that if someone doesn't even get sick? Because in many countries, the whole system is about being reimbursed when, based on hospital visits, based on when someone actually does something. So then you need to reimagine how the whole

healthcare system works and so on and so forth. I keep coming back to where it's similar is that it's a coordination problem again if you want to tackle the real issue and that the minimum viable product in both of these categories is not particularly minimum, right? Like not by bit standard. And that requires a very, very different mindset for how you go about it and how you think about risk and how you think about how long term you are and how you think about all of that. And then we come into the venture ecosystem. And if they're even set up to succeed with this, given how their model works today with fund cycles going from three year to one year and making more and more bets, here you may have to make much larger bets in a much longer time scale than

before. And if so, is that really congruent with the incentives of that system too? So lots and lots of different things that probably not inhibits. these things from happening, but at least slows them down materially. This has got to be one of the most interesting topics in the entire world. We just released a breakdown of Data Dog, and I'm obsessed with this idea of streaming data and observability of systems. I'm wearing one of these levels, Blue Coast Monitor's patches right now. I talked to the founder this week, and he made such a good point, which is like,

we know more about what's going on inside every system in our lives than our bodies. Do you think that that fundamentally this is an observability problem? And if so, like you're in a unique position where we can tie this back to Spotify finally. Like you get to watch what's going on inside of a big system with lots of data. And maybe you can help us understand how powerful that can be to then do better things downstream of the observability of the system. Yeah, I think you're entirely right. But I just think we need to increase the data inputs to begin with. I think my big realization over Spotify is I remember we used to talk early in the days of Spotify,

what data we needed to keep. And I fought pretty hard for us not throwing away any data, which today seems like a pretty ordinary decision. But back then, the reality was we thought of data mostly as, yeah, we don't need all this data. It's completely not necessary. And now the standard playbook, obviously, the more data you have is going to be better because we will assume that eventually we'll be able to infer something quite interesting

about that in this complex system. Where I think we are with healthcare is if you look at it, most of what's happening today, the analogy I would give to people about healthcare and the state of it is think about the car industry and think about a car, if you owned a car in the 80s or 90s, and let's say you were driving down the road and you started hearing some weird noise from your engine, et cetera. What would normally happen is nothing would show on your dashboard, et cetera, most likely, but you would hear the weird noise and you would take it then to the car mechanic. The car mechanic would start by asking you a bunch of questions, right? What type of noise you're talking about? When did it happen? How long have you been having it? Like all these

types of things, right? The car mechanic would probably then walk around the car, just do a quick inspection, officially inspected. Maybe, maybe then would they sort of pull the trunk, shake the oil, do the standard stuff. And then if none of that worked, then they would get really deep under the hood and start looking around to try to see what the answer was. And you now think about a doctor day. That's pretty much what they do. You go in, they ask you a bunch of questions. They will look at you to try to determine if you had some weird coloration or if your pupils are dilated or not. And then they'll try to figure out if they need some more extensive data, usually by blood or saliva or whatever they need to do. But that's kind of the

standard path. Because again, the feedback cycle of asking for the blood, et cetera, it's just going to take a while to get that answer anyway. So most things you can just use visual indicators to determine this. But then contrast that to a car today. So you're driving down the road, most likely, if there were an engine problem, the car would tell you ahead of there being a real problem. Even if they started being a problem and a noise, they would then tell you straight away, go to the car repair shop. As you would go to the car repair shop, the car mechanics today wouldn't ask you a single question. They're not interested. All they do is to take the cable, plug it into your car, and suck out of all the data, and they know exactly what to do.

and they go cranking at it. That's where we are. It's actually, it turns out, more complicated to fix the car now because it's so full of electronics and all that other stuff. But the diagnostics is way simpler. That is what we have to turn healthcare to.

And it's so obvious when you say it like that, but then the question is obviously what kind of data will be usable, and there we have a whole other problem because they're just in the grand scheme of things just don't exist that much data. in the healthcare systems that's real, tangible data. But we have to build the systems that collect that data.

We have to build real ways for us to process that and obviously be cross-referencing that later on with symptoms and so on in order to make real predictions. And to type that back to Spotify too, I mean, again, the first step was create an engine that collects the data, find a reasonable proxy for how to structure that data,

and only much later you would make simple inferments. I remember in the early days of Spotify, everyone thought we went straight to personalization, but we didn't do that. We actually had the same homepage for everyone in the single world. And then we switched it to per country,

and then we switched it to a demo as an approximation of making a good infirmament. And then we made some personal items on the list before we went to it all. And it wasn't even that long ago that most of our playlists were completely static, even though we would show you a playlist that might be a good fit for you, it wasn't really personalized for you. And now we have this cool experience where even a playlist,

like one of our bigger ones, if you look at it and if I look at that playlist, we'll see very different things based on our musical preferences. But it fits that same brand. So we'll still think about it the same way. But we've gone all that way now to personalization where pretty much every element the Spotify experience is tailored and personalized. And that type of infirmance is what needs to happen in healthcare too, where the individual drug in the end that you'll have the specific therapy that targets whatever you may have should be completely personalized. I love the idea that we get the Spotify experience today as a payoff from a data collection

exercise that started more than 10 years ago. These things take time. And step one is get the information. and it can take a long time. You have to be patient. It brings up one of my favorite topics to think about. You mentioned in many ways these big Adams problems are coordination problems. And part of that is sequencing too. So there's coordination and they're sequencing. Capital formation is different. Maybe you need a lot more capital of the people I know. You have this interesting way or instinct to just get going with things. Meaning like when you're interested in a project, something new in Spotify, something like one of these things we've talked about, something even more small, you're just very good at, doing the listening tour, building that ability to teach, but then doing something with it, I think everyone wants to do that. More people seem to be interested in entrepreneurship, starting things, being creators, etc.

What can you teach us about just getting going in the early days? Starting from zero, what has been effective in your life at getting good at that process of going kind of from zero to one in anything? I think it's a realization to know that already starting, you're probably in the top 1%. when I speak to new entrepreneurs, I say to them when they're talking about their idea, most of them start out of not wanting to share their idea, right? Because they feel like their idea is the most unique idea in the world. And you then start saying, well, the truth of the matters, the idea isn't that important. The second thing they try to do is even as they're sharing

it, they're trying to get me to critique their idea. I tell them about all the things that I missed, like missing the Instagram early on, missing the Uber and Skype and all of those things as an investor, which I missed. By the way, I'm probably the most terrible investor in the world, which is ironic that we're going to invest like the best here. Because I missed a lot of these things. And my point with all of that is actually that in all of those, we're a question of falling in love with the idea or not. And what I should have realized in all of those examples is that there were highly unique people that were learned. learning machines and incredibly driven that were behind all of these businesses.

And many of them, ironically, all the Kevin Sistram, Nicholas, et cetera, and Travis had all done things before. So the pattern recognition, you haven't even been that hard if you look back at it. And so the idea isn't that important. What's really important, 97% of it is really all about how you execute against that idea. And by even starting to execute, you're in the top 1%, because 99% will just talk about the idea. but actually don't do it about it. And if you frame the problem like that,

I've found that that makes a pretty good impression because you do realize that by even starting doing this thing, by not attaching yourself too much to the idea, but start to think about how you can execute against that idea that really, really will set you apart already there. And the rest is just a journey about persevering because you'll have these constant tension point where there will people that will drag you in all directions

trying to get you not to focus on that or trying to get you to pivot to do something else and tell you all the reasons why this is a terrible idea, et cetera. And the key trick where you need to persevere, which is the hard thing is you need to be stubborn enough to not pay too much attention to them, but wise enough to really listen to what they're saying and iterate and improve upon your idea.

Because again, as we talked about, the idea isn't that important. It's how you execute against that idea. And usually, there is, very valuable, valid feedback that comes from people if you truly listen to what they mean and not just the word that they're saying. If you extend the problem even a little bit further, I think you and I both suffer from the same affliction of just being interested in everything. And I think that sounds good, but what it can cost is focus. What you've done extremely well,

I think is, yes, sometimes be interested in stuff outside of just your core business of Spotify, but also take some of that curiosity, learning machine energy that you have and plow it back into the compounding of Spotify, the platform. What lesson have you learned there? Some of you and I have talked a lot about making sure to let compounding do its thing and not get too distracted and always refocus your energies back into the central thing that's so hard and valuable that you've built? How have you done that? What is that big lesson? It's very, very hard, I would say as an entrepreneur, because I think the mindset is, You want change to happen overnight, but no change happens overnight.

It does take a tremendous amount of time. The single biggest virtue that I probably have, if you ask anyone, it's not that I'm smarter than anyone, it's not that I'm more driven than anyone, but I have one super trait, and that is that I'm insanely patient. That trait of being able to sit there and just watch and watch. And yes, work on it for sure, but just let that play out. And to know that there's more to it than what most people see, the classical, I think it was Bill Gates who said it, in the short term people tend to overestimate the impact and in the long run they tend to underestimate it.

I've seen that so many times. And I completely do that mistake myself. I mean, again, going back to our conversation a few years ago on this podcast when I said the scale has been redefined. I think even I didn't understand what I meant. I am looking at the world now and centacorns and the decagorns and all these things that we're talking about it like, holy shit. It is pretty wicked crazy how much progress we're seeing on so many dimensions right now in the world.

It's hard to argue there are certainly cases, I'm sure, is overvalued. But there's also some astounding companies among the mix too that are growing faster than probably we've ever seen companies grow before. too. That is this macro macro tailwind of digitalization playing out and a globalization in full force. If you'd ask me, I'd probably thought that would start leveling off. But my view now is maybe we're looking at another decade or two where that has some more profound runway left in it than probably I would have even realized just a few years ago. And the point being is that, again, I was probably too short-term focused on just thinking, well, it's kind of obvious.

But then if you think about the overall economy, how much of that is digital, it's still very, very small. That is still very early days. Ironic, given that I talked about Adams, but if I'm going to talk about bits for a period, that too, is having a massive, massive runway. And I'm super excited about that, too. And I think those things are just, if you know you're serving a mission, and if that mission is worthwhile doing, you can look at almost any problem in the world and you can see improvements to be made day by day. And I focus on that. And if you focus on that, you realize that the value of what you're building is the sum of all the problems that you solve. That is the thing that grounds me and gets me to keep building the things that I'm doing and still think we're early days with Spotify.

There's so many problems left to be solved. I've got a long list of Spotify-related questions that I'm going to say, before we close the chapter on our conversation around Adams and some of the long runways and technology, I want to talk a little bit about Europe. A lot of the talk software bits U.S. has sort of been the narrative of if you just use market cap as the thing to determine kind of where the energy has been. And I'm fascinated by what's going on in Europe, what makes it unique and distinct. maybe there's aspects of it to me, even some of the people you've introduced me to that have this feeling of almost like a sleeping giant that could reemerge with unique advantages. We could even touch on Primo Materia and the project that you've got going there here. Give us a little lesson on European technology and the history here and why it's exciting.

Let's start with sort of the macro macro perspective. We're talking about depending on how you define Europe, it's somewhere north of a half a billion people, maybe as many as six, seven hundred million people. It's got roughly the same GDP as the US, so relatively well developed as a region as a whole. If you look at density of science, scientists, et cetera, it's doing pretty well. If you look at publications, if you look at sort of institutions of top 20 highest rating universities, et cetera, Europe does pretty well across the board. But yet, as you and I have discussing many times, when you look at the last two decades in particular, it's just been underperforming. There's probably a lot of reasons why that's

the case. But for me, one of the single largest problems have been that, which is kind of an obvious statement, but Europe is not one. It's many different things. And it's very decentralized and spread out. And the most interesting thing, there's actually been two sort of insights I've had recently, which is if you take away San Francisco and Seattle out of the U.S. And you start comparing now the US versus Europe, you would see that US actually is not in a great shape. So it just happens to be highly concentrated on those two clusters in particular.

And I'm obviously well aware that there are other clusters now, like LA, New York, and Austin, and so on that's growing. And I think that's amazing for the US. And it's going to be super important. But really, the past two decades has been focused on these two dense places where Europe is a lot more decentralized to be in, which probably created some of that friction.

But the second thing, even within Europe, it is a bunch of mini clusters in itself, even within a country. Conversations I had, I remember pretty vividly, is a friend of mine visited Singapore, and he got a chance to meet the leadership in Singapore, and he's from London, and he commended them about how well-run the country was, et cetera, and the leaders sort of thanked them but wasn't too enthusiastic about the compliment. And so he said, well, I don't understand. Like, clearly Singapore is more well run.

And he said, well, in all honesty, Singapore is kind of like London. And if you compare the two of them, kind of equal. I thought that was kind of interesting too, because even as you look at a country, London is obviously highly different to the rest of England, not to speak of the rest of the UK as well. So we're looking at these sort of mini-centres across Europe. And they're all at different maturity stages. And we just didn't have one of these super clusters for London. lot of different reasons in the bits world. That's just not happen. Instead, we had a lot of

decentralized clusters like Stockholm, even though it's not a very big city. It's disproportionately punching above its weights. I hope some of that may be because of the success of the Spotify's and clarinous of the world. But maybe even prior to that, we had a bunch of dot-com businesses that failed and crashed and burned that I know certainly inspired me and a bunch of other entrepreneurs too. And you're seeing that ecosystem development now happening across the rest of Europe too. So there's lots of structural reasons why I think Europe was behind. But I feel much like what's happening in the U.S. now, the talents is being spread out. And because of these playbooks are now universally known and capital is now more widely dispersed too,

you're starting to see those ecosystems in Europe now very, very quickly and rapidly growing up. And I think a lot of U.S. investors are seeing that there's great opportunity. now in Europe too, which is just phenomenal to see. But my prediction is, as interesting as that is, that's not where Europe will have a leadership position. It's just going to play catch-up to the U.S. and China. And it'll be good. It'll be great. But I feel like the next frontiers for me are these gigantic societal problems, like climate, like health care and others. And there, I look at Europe and there's just an amazing degree of innovation that's happening across the board. And because these are coordination problems and unknown playbooks, Europe is now, in my point

of view, from what I've seen, in many cases I had where the rest of the world is. And it's just completely being overlooked because all we're focusing on right now is this bit part of the world. But I'm super excited about that. And I do believe over the next decade that Europe, as those industries, will start mattering more. Europe has a real, real big role to play in the global landscape. What about Europe makes that true? Is it its history? Is it, it's very longstanding history and industry, for example, a lot of this stuff started in Europe way back when? What features of Europe,

if some of those things you mentioned maybe are reasons why it hasn't done as well in the last, say, two decades relative to San Francisco and Seattle, what are some of the reasons embedded in the continent or in the culture or in the resources that make it possible that they're going to be the leaders in some of these new problems. I've thought a lot about this. I'm not sure I have an answer truthfully. This is kind of like asking why did Silicon Valley become what it is today? So I'm not sure you should probably ask one of the Collison brothers about that. I'm sure they know more about it than I do. But my view would be that some of these topics have created more of the a Grantswold debate for a longer period of time. It's just been higher up on the list of public

interest for a longer period of time. So just concrete Swedish example, sustainability. The Swedish government, I believe, more than a decade ago, mandated that if you were over a certain amount of number of employees, you had to have a sustainability report as part of what you did. And that sustainability report wasn't just about climate, but it was about diversity. It was gender pay gap, like a bunch of other of those topics. That was a top-down driven thing by the government that created a lot of debate and created a lot of focus and transparency. And you started looking at what are best practices.

You started comparing between companies because obviously this is public data. You started seeing that being a big thing. You now are in the period where you have basically decades of that experience. And then in climate specifically, you can look at the EU being very, very, forthcoming around creating a carbon tax system that now people can trade in and so on. It's just very fascinating, I would say, how much government specifically in these sectors have played a role. I don't know if that's in any shape or form, a parallel to DARPA and all that work that went back in the U.S. government playing an important role in the Internet and all that

part too. Not sure if there's any corollary to it, but I think at least in these fields, government has been very involved, at least in putting the discussion on the agenda many decades ago, and we're starting to see some of that benefits now. Just like we're seeing Cambridge and Oxford right now is on fire because of initiatives that the UK took, I believe, in the 80s and 90s. And it's only really now that we're starting to see the number of breakthroughs coming for those institutions being remarkable. It's very, very long-term investments. Again, And you can look at Silicon Valley, whether it was coordinator or not, with Syracke's Park and all these institutions that were there, HP, all of those things that then laid the ground for much of what we're seeing today. I'd love to ask now a whole bunch of questions on what you've learned in Spotify, the ecosystem specifically since we last talked.

We talked about a lot of like my favorite topics in tech last time, platform versus aggregator, the idea of core platform versus like a constellation system, maybe more like what Facebook has done with different apps and different apps and different. different brands, all these things. And we've had a few years now between then and now. I love how you frame this as even you underestimated the potential scale differences and how things can change in a couple of years. How would you characterize the most major lessons that you've learned relative to expectations within Spotify since 2019? And as a frame of reference for those listening, this was kind of just when you were beginning to acquire and build some businesses that were more like creator platform-like tools, get into podcasting with a lot more intent. and with some big bangs.

So that was all just beginning at that time. So since then, what has been the progression? What have you learned? I think the central tenant is just, this is all playing out. And it is just a gigantic opportunity. I come into work every day, just rediscovering and resetting the expectation for some of those things. So let me give you some example. Today, we're about 8 million craters.

I believe when you and I did this, we were about three. and I think in the next few years will be about 50 million creators or so. And even that in itself doesn't feel like a huge stretch. There could easily be that I could be wrong, not maybe by an order of magnitude, but there's probably 5x. It could be 5x more, which again just seems crazy to think about. But then the sub-problem of that is you think about them as a homogenous group. That couldn't be further apart from the truth.

And I think the realization that we have seen now, even during COVID, is you've seen many more permutations up until very recently. Ad support it was the primary mean through how many of these platforms were able to stain themselves. But during the pandemic, we started seeing real innovation on many more types of business models and ability like everything from Patreon and taking off live audio shats, rooms, etc. paid memberships to various rooms and podcasts, et cetera, started making sort of big waves, just to name a few of the developments. And as I think about that is we're moving from this sort of emergent creator class where it's pretty obvious that there are more and more people building entire businesses being creators.

I honestly think even you is a great experience. Just example in all this. Sure, you had a business before you started a podcast, but I'm not sure which one is the sort of major part of what drives one anymore. Yeah, it's kind of this virtual feedback loop. And you see that with many of the most successful creators too. They have their own media businesses where they're speaking to their audience and building that. And then in many cases, they have other businesses as well that help monetize parts of that audience in different forms.

Put another way, I think most the common perception has been that this platform evolution has mostly played out. But I think what's evident to me at least is that that's very far from the truth. We may actually be just in the beginning of these platforms playing out. Just look no further than a few years ago, the common view was that there wouldn't be any new platforms. The Instagram and Facebooks of the world had already won. And then out of China comes bite dance with TikTok and had a meteoric growth. You can look at that and say that's a lot. one-off where you can say that just proves the point that there's going to be a lot more innovation

in this space. I'm overall excited about this creator economy concept and how early we are in that journey. And then specifically to Spotify, when you think about video versus audio, audio is in even more nascent formats than video is. Like there are even fewer minutes that have moved online as of right now than there has been digital video minutes that have moved. online. And that for me is super exciting and just shows that there's going to be a lot of innovation there too. And you've seen it with Clubhouse and other things too that's been emerging that for me again proves to me that there's going to be a lot more innovation in the space. Whether a specific format works or not is a really different question. But just creators are

experimenting at a much higher degree than what we've seen in the past. And I think consumers are are willing to dive deeper and experiments as well and want to be authentic and they want to connect with creators that are authentic to what they believe too. I think there's two dimensions that are really interesting and all that. One is back to this aggregator platform concept. Everyone always uses Shopify versus Amazon comparison as like the examples of those. But like you said, the truth might be somewhere in the middle. So I'm curious how you think about the aggregator versus bring the demand versus don't

bring the demand, just enable, arm the rebels, as Shopify says. And then specifically in kind of three categories. So you've got music. Just fascinating to hear how you think that is or may change the way in which artists interact with their audience. You've got podcasts. And then you've got interactive audio. You mentioned Clubhouse or just new modalities of audio. I don't even know where the hell I'm going with this question. That's kind of the big picture that I'm visualizing here. And I'm just curious maybe we could tackle them one of the time through that lens. What you're seeing. We could start with music. How is this changing? What are the ways we could even talk about crypto? Like, how do you think artists, musical artists, are changing the ways in which they

interact with fans? And how do you see that through the lens of Spotify? The macro trend remains the same, but the ways that's showing up is obviously slightly different. So the macro trends are that there are more artists now than ever before that's coming out there, creating music and putting their music out there. And it's very much a global thing now. You're seeing artists obviously from Korea that's breaking through on a global stage. You're seeing the most listened to artists as of last year was Bad Bunny, which is a Latin artist in the globally world. So it's becoming global in a big way. And that's changing. For most of the time, we're in an Anglo-American type culture where The only thing that can make it on the global stage was an Anglo-American artist.

And now you're seeing many of these really, really cool cultures make it onto a global stage resonating with huge audiences. That is a metric trend that's clearly there still, the globalization of that and the reduction of cost of creation and the reduction of the cost of distribution. So those things are still playing out. And we're still moving minutes online. the car is still mostly not connected. It'll still take a long period of time before it is. And there's still a lot of stereos that aren't connected to the internet and being personalized in any shape or form.

So we have a tremendous amount of runway just there. But I think broader speaking on music, I also think that the way music is showing up, for most of the time, music was a relatively unlicensed experience on the internet. So there were very few places where music would show up. I think over the last few years, music is now becoming part of most experiences on the Internet. Again, we talked about TikTok previously, but music is a very big part of the expression for creators there. But it's not even the center of what the creator is saying, but it's almost like a remix culture where you have average people now promoting someone's music through them dancing or them expressing themselves.

itself, et cetera, which again is actually kind of an analog thing. That's kind of how we used to relate to each other, but people are now doing it digitally enriching a sort of a global audience too. And so I think music is becoming even more ubiquitous than what anyone could have imagined, but it's still tremendously difficult to do. It's a lot of patchwork for these platforms to try to enable those experiences, and it's still not an entirely clean experience. Like if I would take one of those videos and try to share it on the other platform. In many cases, you just can't for copyright reasons and other things. And then we get into the whole creator experience.

And while it's been true that creation is easier than ever for in distribution, monetization of that content is now probably even more opaque and weird than it's been before because it's now showing up in all these different places all over the Internet. There you have now technology like blockchain and other things, which are relatively early in its sort of maturity curve, but I think could play a very important role in enabling more of that remix culture and that global experimentation of making music more widely available.

And then not to speak of more ways to give control back to craters and labels and others on how that music should show up without this arbitrary processes. My way of looking at blockchain is, what's interesting is what problems would be greatly enhanced if you could scale business development. So rather than thinking about it as a one-size-fits-all,

but if you imagine problems that would require lots of business developments, effort-like, what are some of those problems that are of huge scale? One of them turns out to be creation and IP and content, all those things, which is probably why people are excited about it. The hard part, again, is that there's a lot of different stakeholders in that value exchange, And it's going to be tricky to try to find a way to make it work for everyone in that value chain. Not the least, of course, obviously all the artists and songwriters as well. There's examples in Spotify specifically.

I know this because I have a new podcast where if you build in that ecosystem, it almost becomes like a simple API to just access and pull music and insert it into some other experience. And it sounds like what you're saying is that that opportunity will be written much larger, that any sort of creative experience via platform without violating any rules and actually probably flowing back to the original creator and the IP that they've created, the content they've created, that this will just become literally a soundtrack to our lives. Like to everything that we're doing, music will become more accessible. There's more creators of it than ever.

And there's more opportunities to insert those creations into other experiences. And that's just really cool and incredibly exciting. I'll ask sort of a radical question, which is, if you think about the legacy music system, If you were the CEO of the world's largest record label tomorrow, what would you do? Would you be trying to get things onto a blockchain? Would you be trying to push IP more into the hands of the creator so it gets used more often? There's more velocity behind it. How would you think about position of a legacy power structure like a record label if this vision of the future of music is true?

I think the smartest labels already do a lot of what I will say. But I think the model has been a controlled. the environment, and it's been all about controlling how their IP is being used and monetized and having as much control as possible around that. And by the way, control over the artist's relationship, control over all of these things too. But if you think about it today, a record label, it didn't dictate what the artist did, but it pretty much controlled when the artist would speak about the record, like which press outlets. They ran the marketing, PR, like all of that was coordinated by the label. And then you look at it today. It's

It's not a coordinated effort. Most artists run their own social media are very much involved themselves and they're speaking to their mind and expressing themselves and they're very savvy on how to engage with their audience too. The point being is the best labels

have realized that they are in service of the creator. Their job is almost to try to enable the creator to do as much of what's authentic to the creator to try to do. The smartest ones would be very service-centered and try to create more

enablement rather than sort of more control. And so if I ran one of them, I would probably try to take that to an extreme somewhere and try to see how much could we improve? Because it seems to me like if you look across the Internet, much of that really has been, the more you can enable of it, it tends to be a really good thing. I mean, take gaming as an example. You and I talked about this. I'm not a huge gamer, but gaming started off.

You paid for the game. Now we're talking mobile games. And then they tried to create these free games, add supported games. And now what they've realized is maybe the best thing is to just give away as much of the game as possible. And then there are certain mechanics inside of the game that if you really enjoy the game, you'll probably want to pay for that thing. It'll be just a better experience overall. But there's nothing that that forces you to do it.

You can probably get away without paying anything at all if you want to put the hours in. But if you want to get to the next level quicker, then you might buy that. looster that gets you through that boss, that level, et cetera. And put another way, it's like that is that sort of enablement too. That would have been very scary 20 years ago to say, hey, we're going to give away our game for free. And they will just trust that people enjoy the game so much that they're going to want to pay for all these things inside of the game.

But that's kind of where we end up with gaming. And I suspect that what's going to happen, not just with music, by the way, but most sorts of artists that we can enable so much more by enabling more of these things, usually will pay out better. Not to say, by the way, there are some artists that will probably benefit from scarcity, too. We tend to think that it has to be a certain way, and that's all to it. I actually believe that what's so fascinating is all things will work, and there will be a place for pretty much everything.

Like, we've talked about this many times before, but it's like the centralized aggregator model works. But what is blockchain? It's certainly not a centralized aggregator model, and that seems to work, too. It's a highly decentralized bottle. And those two things will both serve a place in the world. And Apple's quite locked system is obviously highly revered by a lot of customers, but so is Android and this open ecosystem as well. So basically, I think the theory of the future is we just get to run experiments at all ends of the spectrum.

And that they probably all, especially in the world of bits, have good outcomes. Because we can run experiments very cheaply. Cool things can happen. content can go from a source of revenue to sort of more of a top of funnel to drive fewer people towards maybe more expensive experiences, whether that's a concert or something even more intimate or whatever in the case of music. I just think that's a very cool thing that sounds like what Spotify's focus is just to push more, even for free, down onto the creators and grow the ecosystem versus grow the take rate. Is that a fair kind of summary of the idea? Mostly, but I would say

The caveat is, I think the reason why this exists now is because we're playing on a global stage. I'm not saying Spotify specifically, but I'm saying all Internet companies are dealing with potentially billions and billions of consumers. By that definition, you're really dealing with the whole world and every possible permutation of every possible thing too. So just like, as I said, you might go towards free in some cases and hope you'll make it back. That may be a successful strategy, but I also said the opposite could be true too. charging $1,000 for something will also be a viable strategy.

And so I think the Spotify-specific strategies, we want to enable more power back to the creator. And if anything, this one-size-fits-all that's been the sort of motto of these platforms. And by the way, I think we had to build it that way because we had to get the users to come on and have a way of interacting with these services where it was reliably and understandably. I feel like the next permutation of the internet is one where every single thing will exist. And I think consumers will understand that every single thing will exist. It's like when we talked about news, the common view a few years ago is that news had to be free.

It was impossible to monetize. I'm not saying I think the paywall experience is great, by the way. It's very frustrating sometimes as a consumer when you run into these constant paywalls, even as we're trying to read one article. So I think that there's a lot of innovation that needs to happen there too. But the paid model turned out that it worked too. I'm confident that we'll see another evolution

of journalism and news as well, where there will be other business models that will unlock even more consumption and more journalism as well. It's really about moving for one-size-fits-all to this ecosystem approach where there will be more control ultimately to whoever creates the content to interact with their audiences on their terms.

That audience, by the way, may be a listener in one way, a fan in another way, and a super fan in a third way. Yeah, it's fascinating that it's all about enablement and that what you're basically saying is let the creator pick their business model and be there to serve them however they want to do it. And I know that Spotify has built a lot of tools in that area. What has surprised you so far about the foray into podcasting? Three years ago, this was not a big focus of Spotify's. Today, many of the biggest, most well-known

podcasts are on Spotify, some that you've purchased, some that you've built and originated, but also just the overall podcast experience has been a focus. What have you learned here? What's been interesting in a couple of years since this began? A tremendous amount of lesson learned. But again, on the consumption side, I think the real interesting things is just how much of a different discovery problem podcast is versus music. And this, by the way, is probably one of our biggest sort of improvement areas that we're working really hard on solving. I still think today, I mean, and it's kind of obvious. If you think about a podcast, it's a pretty big time commitment, especially if it's by someone you've never heard before.

In many cases, maybe 20, 30, even an hour's worth of your time. So you're going to pick that very carefully. If you think about that compared to a music song, it's a three-minute commitment. It's not the entire world to just go in. But a podcast requires you to listen at least for a few minutes before you kind of switch to something. And yeah, we've made some progress with trailers and all the things too. But I think you're going to see in the next few years just amazing progress on us being able to merchandise and contextualize podcast to people so that you start seeing people dive into the rabbit hole in a big way. in as usual with the internet.

It's just been fascinating in this new area because we've seen it in music before, but we haven't seen it. Obviously, we didn't see it in podcast until recently, but it's this common thing. It's like you can see the behavior happening. You see people hacking their own tools and doing exactly what we're going to do. But what happens if you can automate that and make it easy for people list, it's not like you're 2xing the discovery rate. You're looking at a 10 or 20x.

And then the question ends up being if you're, 10xing or 20xing and any metric, what is the second order consequence of doing that? That is insanely cool things. We're seeing people use Spotify at entirely different times during the day than they were previously. So we're winning moments and we're starting to see music being played in moments that it wasn't before it too. I couldn't figure it out because I started seeing like there were genres of music where

it's never been big on the platform and I kind of mostly written it off as, yeah, it's not going to be a big thing. But because we were winning in some of these podcast moments, we're starting to see some of those musical genres then coming up to too, because it turned out that with the podcast next to the music, people were then starting to listen to music too as they were finishing the podcast or whatever they were doing. So just, again, you're dealing with complex systems,

and you're dealing with every permutation that you can possibly imagine. You've seen the Facebooks and of the world deal with political content and so on. It didn't take as long. It was actually several years ago that we had the president of New Mexico that every week started publishing their national sort of address on Spotify and so on and so forth. So there's just a lot of things that happened probably way quicker than I would have expected. But this is the amazing thing about enabling a platform too. There's tremendous amount of progress on it, just on a personal basis.

I just acknowledge that is now available to people. I fundamentally believe podcasts, our common friend, Shere talks about this framework being nutritious versus delicious. It's what you're doing, nutritious or is it delicious? But I think podcast is one of those things that's mostly errs on the side of being more nutritious than perhaps being delicious. Not that it's not delicious too, but you know what I mean. It's just a great way, I think, for getting into the rabbit hole of going very deep on lots of experts talking about various, too. And I wonder what the implication is, in our case, of exposing this to such a huge part of our audience that many of them never listened to podcast prior. What is going to be the impact?

Like, what new subjects will come from this that people will learn about that we had no idea about what is the second order consequence of that. There's just a tremendous amount of cool stuff that we're just in the early days of seeing. It feels like it's bootstrapping like the next library of Alexandria into existence that because conversation, if you put our text on this conversation, it's book length. Like an hour and a half is like the length of a book. You do it an hour and a half. It takes years to write a book. And so it just feels like podcasting is bootstrapping the world's deep knowledge, not just like service level knowledge, but deep siloed knowledge into very accessible format. And we know that that creates leverage. Like that means you can learn faster. That means you can build on top of that knowledge base faster. It's like this cool version of open source that's knowledge instead of source code. I mean, it's just so. cool to see primary audio platform embrace this because I think it could fuel as much as anything else that's happening out there. It begs kind of a fun closing question or two about how you foster the culture and what I'll call like the sacred flame of the business in this coming

chapter. So you're at the point that you're at. You went zero to one. You've scaled up. Now everything's personalized. It's been this incredible journey. And now you have this platform. There's this interesting concept, our friend Graham Duncan calls working with Source. And Source is described as carried by the founder that sort of takes the first risk to create something new. In many ways, you as the founder is sort of the carrier of that flame. What have you learned about spreading that around, both carrying it and maintaining it, but also making it extensible so that you yourself aren't a bottleneck in all of these cool new things that Spotify is doing and that others can sort of take that flame what makes Spotify special and allow the next chapter.

to your point, make the scale that we're at today seem silly in hindsight five years from now? I think right now, we are in this world where founders can do no wrong. They are the one you need to empower and it's only that. And as a founder myself, I can say it's probably going to be a little bit hypocritical, but I don't think founders are always the right thing. It creates a lot of strain to be a founder too. And having them involved in the business, just generally speaking. But I think the more important lesson learned is that what it often brings is this clarity of purpose with a founder. Because not only did this person start the company, they're typically a big owner in the business and can corral all the other owners across this one narrative mission. So to speak for the owners.

They're typically on the board too and maybe a very powerful voice on the board. And they're on the management team. and they're perhaps on the product team that's building the product too. So you just have crystallized this force that's all pointing in one direction. That is the magic when it's done right with having founder-led businesses. So I say that, but it's not the only way you can create that too. You can get that in other permutations as well. And the downside in often case is most founders, myself included, are highly impatient,

which something happened yesterday and don't want to take no for an answer. And we're not 100% right on a lot of things. So we jump into problems that we shouldn't jump into because we have some sort of pattern recognition that we think we're more right than not, and that leads to hubris, and that's not a great thing.

And my point being is that I think the most important thing I have done is probably try to create an environment where it's okay to fail. I'm not sure I can stretch more of those founder powers, but if I can lend the founder powers in that, hey, it's okay to fail, and we can try things. Not everything has to be successful. I think when Spotify works really well, it is when we do those types of things when we're not afraid of failing. We may even know that it's a high degree of likelihood that we will, and then we kind of pivot around that. We're constantly doing it with a concentrated power behind it, the concentrated

power of the whole firm being aligned that this is the right thing to test. So we spent a lot of time debating, is this the right thing to do? And we spend a lot of time teaching people how to think about making decisions in order to do that. And I think some of the greatest cultures that we have today are the ones that have created a great decision culture that both allows people to make mistakes but also improves the decision making drastically so that those mistakes don't need to risk the entire business as you're doing it because the easy off answer to that would have been just a controlled environment where everything has to go through one setter that's my view but again going back to the whole founder thing I would say this is almost like a different thing it's both good and bad

And it's important to realize in which circumstances is not always great. And then surround yourself with people who dare to push against you. And they're also to come with other suggestions and come together as a team. That's the most important thing. I think in closing, my last question for you ties it all up nicely in a bow. I've lived this five-year journey by the mantra, learn, build, share, repeat. I just really like that loop. And maybe the most important in that because it's the hardest is the built concept,

that everyone knows learning's great, everyone wants to learn and read and listen and blah, blah, blah. When you go to teach something like you said, that's when you really, really rubber meets the road and things get hard, building things is hard, teaching is hard. And this concept you just said, I think, is the perfect place to close our conversation, which is around decision making, getting better at making decisions. How do you do that? In what ways can you teach that to other people or show that to other people? And in what ways have you gotten better as a decision maker? Because ultimately building is about decisions. It's about moving through decisions quickly and never operating with perfect information and being comfortable with that. So maybe just as a five-year caper, we've done a lot

of learning, but I think building and decision-making is maybe the even more important superpower. What have you learned there? As you said, certainly is an executive. Your tool to build is usually decision-making. That is a skill to hone, and it's an important tool. There are many frameworks. realize that it's not one thing. It's about having a number of different tools in your toolbox and choosing wisely when to apply which tools. But if I try to summarize it, I would probably take three things. So the first thing is to realize whether something is a one-way door or two-way door decisions. Most people cannot make the distinction of what's what. So they'll either treat everything as a one-way door decision or treat everything as a two-way door decision. Both are

incredibly dangerous. For everyone who don't know, the concept, I think it was Amazon back in the day they popularized it and there are many variants of the same idea, but basically one-way-door decision is very hard to reverse, if not impossible. Two-way door decisions are easy to go in and out of and you can easily reverse it. It's important to know when you can experiment and when you can't teach people that and that there ought to be different decision-making processes based on if it's a one-way door or two-way door, I think is important. The second thing that I've found to be very important in decision-making is decreasing the number of variables. So the distribution curve of outcomes tend to be drastically problems that my team can't easily

solve are multivariable problems. And it's tricky not because one of the variables is unknown, but usually because two or three are unknown. Because we all want to be very data-driven and data-informed, it's very frustrating when you don't know what the distribution outcome of each variable can be. And more importantly, you want to be exact on a few of these variables. And so what I typically end up doing is I invert down to the minimal amount of variables that you can imagine. So just remove the other ones and make numbers up, even if they're not true, just to make the problem a lot simpler. And I say, well, if it was this,

what would the decision be? And if it was this on these two other variables, what would the decision B. What you've actually then created is basically you created a number of different decision outcomes depending on the decision tree. And if neither one of these outcomes are particularly expensive, you can just pick one. If it turns out that one or two of these are very, very painful, you might want to go back and research and try to see if you can limit the probability of it being one of the two other options that you ended up with. That's been a very powerful thing. either it's not even in this case whether it's a one-way door decision or two-way door decision but just overall as you think about the impact of a decision whether it's be a one or two-way door

that's been very helpful and then lastly to use the inversion tools all together so i think charlie munger very famously talks about this but he says i think he was in the u.s. military at some point as a meteorologist and his job he realized after a while was to keep u.s. fighter pilots safe, rather than what everyone else was trying to do, which was to try to figure out all the stuff that they could do around the weather and all these things. He kind of inverted the problem and said, what will kill the pilots? And how can I avoid that from happening? So he only bothered about finding the things that might really be catastrophic and not bothering about what the average weather was for that day, et cetera, because it wasn't that interesting to send that

back to the pilots. The only thing that matters was really keeping them safe. And that was void of snowstorm and a few of the other things too. That's just been some tools that have been very helpful. But there are many others. And I would just highly encourage everyone that works, whether you're an investor or an executive, is just to spend a lot of time in all fields and disciplines. Again, even someone like Elon Musk, reason from first principle, if you ask people 15, 20 years, that wasn't in physics, that was not a known concept. And most people didn't think about it. I hear every investor or entrepreneur these days talking about it, myself included. It's just a great concept. But again, it wasn't Hila Musk that invented. It was a very common thing

in the field and discipline of physics. And there are many, many others as well in pretty much every major discipline that you can go learn from and pick. And I tried as a discipline to learn a number of these frameworks per year, just as a pure learning thing in order to improve by decision-making. because that is my primary craft these days, is prioritizing and making better decisions. I absolutely love all three, maybe even especially the second one. It reminds me of Frank Sloopman,

that snowflakes concept of narrow the focus, increase the quality, basically reduce the variance down to almost a binary, if you can, to make better and better decisions and create better outcomes. Daniel, I'm so lucky to have learned so much from you over the last many years. You're the perfect person to celebrate five-year anniversary

of the show with. Thank you so much for your time. Well, thank you so much for having me. And congrats on five years and cheers to another five. Many more than that. Cheers, my friend. Thanks. This episode was brought to you by Canalist.

In this three-part miniseries, I sit down with Brandon Weir, founder and portfolio manager of BWCP, a fundamental-oriented TMT consumer hedge fund manager based in Dallas, Texas. Here, Brandon's biggest lessons from launching his fund, their unique, blended investment strategy and how BWCP has integrated Canalyst into the investment process since day one. In this week's episode, Brandon and I discuss his investment roots and how he attempted to blend the Tiger and Citadel strategies at BWCP. So Brandon, the best place to begin is with your personal origin story and background. What were you doing prior to BWCP and then we'll start to talk about how that experience led to the founding of the firm? We can take it all the way back.

I got into investing in a strange way. I'm from Kansas City. Middle class background. My parents made me have jobs and the only one I could stomach at the time was mowing yards. And I started a business when I was probably 14. It turned into a passion for investing. And the reason that was, is I noticed early on when I was able to drive, you should drive to the nicest areas you can find. They had the best profit margins on mowing. And I got to know some of my clients that I was mowing yards for. And they were young guys that were obviously doing very well. And I asked them a couple times what they did and they told me they worked for American Century. And I didn't know what American Century was. I'd never heard of it. They put me on to some books. And it was simple.

This was 94, 95. It was Peter Lynch, one up on Wall Street. They said, find things you're passionate about, what products people are passionate about and do that and make it your own. And that's what we do. We figure out how the world works. So I started investing in 1996. I opened these accounts. and what I saw then was phones. Phones were starting. It was the beginning of the cell phone era. And so the first three stocks I bought, which really kind of ingrained a passion for investing,

were things that were involved with cell phones. And so I go to college and I'm basically wondering if I ever going to have a job. These are 10 bagger-type stocks at the time and it was the late 90s. And I really wanted to figure out how to turn this into a real career, not just the day trading stuff. And I was lucky enough in college to have a great financial, professor. My finance professor helped me get a job with Goldman Sachs. So I went and spent a couple years in New York doing investment banking. And I was really fortunate. My first job came with a firm

called Highside Capital. Highside, this is why BWCP's roots are in Dallas now. Highside was a Tiger Cubs spinoff. I guess it spun out of Maverick, so it was a Tiger Grand Cove. I spent eight years there doing technology, media, and telecom. Phenomenal firm. We were a few billion dollars. I got an opportunity. I was actually kind of thinking of forming this exact firm back in 2012, but Citadel came along. And Citadel was expanding into Dallas under the name of Surveyor Capital. And they hired me. And I ran a portfolio for Citadel for six years. And it was a wonderful thing. And I tell you, what Citadel does so well is risk management and portfolio construction. What Tiger does so well is how do you find great ideas and uncover things that people aren't really thinking about and use time as your advantage.

What I wanted to do, and this is what BWCP is, is kind of a bringing together of those two things. How do you use great fundamental stock picking? But understand that the world's different. When I started in 2004, 70% of the dollars traded were done so every day by fundamental managers. When you fast forward that to today, it's kind of the opposite. It's the inverse. And today, only 30 or 40% of the dollars are traded by fundamental managers. And so you need to be aware of what's going on. And so we use some risk tools, some of the factor awareness, some of the things that were from Citadel, but really just doing it around that framework of the Tiger Cup style of stock picking. I love the fusing of those two disciplines of the rigorous portfolio construction quantitative that

Citadel obviously is famous for with the deeper fundamental insight on businesses, which is a great bridge into the key things that you found setting up a new investment firm. There's a lot you need to do. It's a lot of effort. I've seen it done. I've done it myself. I know that it's difficult. And I think companies and research is one aspect that gets talked about less. Like most of the focus on legal and systems and team and all this kind of stuff. How was Candlest a part of that early setup? What did the company models allow for relative to your prior experience that let BWCP get up and going faster and sort of how are they used in the early days? Let's make a picture. You're running a two plus billion dollar hedge fund inside of Citadel.

you have a team of six. You don't even know what back office means because every single thing is taken care of. And you have a lot of resources. And you have a lot of young analysts that need to spend a lot of time doing the Citadel way or whatever that is. Roll that forward. I have a couple analysts, myself, small back office, friends and family capital and my money, basically, our internal capital. And we've got to figure out how do we divvy up resources. Because right now there's two things.

that are our most limited thing, time and money. And we have to find across the board, where can we use our analysts' time to do the things that are most impactful to the research process and where can we outsource with great partners to leverage both that time and money? And that's where Candlest came in. And we used some of our friends. We asked them about best you know, practices, how they utilize their limited resources up front, and panelists came up time and time again. So what Canadaists does for us, think about the amount of time that it takes to set up a model, to build a proper model, to update that model each quarter. We probably, with the number of stocks that we look at, we're saving one and a half to two analysts a year. It sounds like a

huge number, but that's probably only looking at, you know, maybe 100 to 200 companies. But to do that right, that's probably what it would take from a manpower point of view. Now, if you think about the research process, what is it about the model that's so important? Models are the output of a lot of inputs. And the value add that we need to spend our time with our team on is what are the inputs? What do the numbers mean? It's not necessarily the building blocks of the nuts and bolts of the model, but it's what it really comes down to is what are your assumptions, how good are your assumptions and what do your assumptions mean? So whether or not you're a super long-term investor and you're going to make a decision once every 10 years, you still need to know, then what are the

cash flows over those 10 years? If you're a super short-term investor, where you want to know everything about every margin, about every top line item, about every revenue trigger, you obviously need to make those assumptions somewhere and put them in a model. So it's a basic building block and it's the foundation of everything that we do, but it's not something that we want to spend all of our time doing the things that other people can do so we can then turn around and use our time more valuably. And that has been a huge, huge help in how we allocate our resources. If you enjoy this episode, check out join colossus.com. There you'll find every episode of this podcast complete with transcripts, show notes, and resources to keep learning. You can also sign up

for our newsletter, Colossus Weekly, where we condense episodes to the big ideas, quotations, and more, as well as share the best content we find on the internet every week. Thank you.