Gustav Söderström - How Spotify Thinks - [Invest Like the Best, EP.424]

24:27And then Anna can say, okay, I didn't know that, or I'm going to solve that. So it's real-time resolution. Very simple in theory, but incredibly powerful in practice. Most companies don't do it. So this notion of no taking it offline, taking it later, real-time resolution. That's why it's three hours. So that's one thing of this meeting. Another principle we have in that meeting, except nothing goes offline, is you actually can't bring your direct reports for good and bad. The idea is that if you bring in a lot of direct reports, two things are going to happen. One is the VP is not going to get forced to know the details as much.

25:02So I'm trying to literally force the VPs to solve it themselves because I want them to be in the details. So you're not allowed to bring anyone else in to explain your thing. You have to be on top of it enough to explain it to yourself. The other benefit of that is over time, these groups get very tight because you don't switch people out all the time. So you build strong rapport. People can be honest. No one is afraid. It's a very strong and high functioning team. So that's a lot of what we do. The other part is strategy and looking forward. So let's say that something we've been working on for some time now that is public, we wanted to introduce music videos and the team goes off and says, what does that take in terms of licensing product?

25:38What is the cost implications for the company, for the P &L? They come and present to the team, this is what we want to do. This is how long we think it should take. So it's a combination of keeping the engine running and never stopping and also planning for the future. But we don't really plan in that. It's too big to have detailed planning. That happens in focus rooms with smaller groups, with experts. And then they come and present to that team. We're not the only company that does this. I know Airbnb does something similar. I spoke a lot to Branceski about it. I think Netflix may have had something similar at a time, but they're now divided into content, the business and product.

26:13What I think is important about this, it's both the business and the product side. And we talk a lot of product there. So the business people in Spotify, they know an awful lot about AI, about what a monorepo is. They're there for the prioritization of technology, but on the flip side, all my product people and engineers, they know exactly what the P &L looks like. They know our goals. They know what gross margin is. They know everything. So that's quite unique. And that gives them a CEO perspective that I think disappears in many companies because we put on these roles of you're a product person, so you're not supposed to understand finance.

26:45That's not true. If you're the CEO, you have to understand all of it. If people are listening and are curious about this Bets Board process where you can submit projects and it seems like a really elegant way to allocate capital, what advice would you give them about the pros and cons of this process? And I know you've been doing it a long time. How it's changed over time to reflect the learnings of what makes it work or fail? So the concept itself is actually really straightforward. It comes from the Kanban board. It comes from the developer community, which actually comes from car manufacturing eventually.

27:18It's really the concept of stack ranking, which is very easy in theory and very hard in practice. Very few people manage to say, this is actually more important than that. They're just saying these things are very important, both of them. And when you press them, they say, no, they're equally important, but then they're not ranked. So the real secret is to stack rank and say, you have your two darlings, but if you have to kill one of them, which do kill first in reverse order. So very easy, but hard to do across the entire company to agree on that. but once you have it it gives so much clarity to the org because what happens when you say these three things are equally important but they're not really they never are you're going to have to choose is you just push the decision down the org and this vp is on the hook for that thing it's going to start fighting this vp is on the hook for the other thing and if you as a leader don't bring clarity you're going to set your org up for fighting and people are very nice are going to think that they don't like each other so just the stack ranking and being completely transparent across the entire company means that if I come to you and I say, I need you to do this.

28:15And you say, yeah, but I'm doing this. We look at the board and say, oh, right, we should do this. It's very simple, but very effective. And when you do that, there are a bunch of things you run into, theoretical questions of, okay, once you have this best board done, do you resource it globally? Do you go through every developer and say, oh, let's just try to get as far as we can? That planning process is hell if everyone is up for grabs. None of my VPs have any estimate of what resources they will have, you basically disempower your entire VP. It's effective in a sense because you do perfect resourcing, but it's incredibly inefficient to do the planning.

28:48So then the question is, how do you divide it into blocks? The structure we have is we have a platform organization. They work with GSP and the cloud and the developer tools and so forth and security and all of that. Then we have an experienced organization who's responsible for the entire consumer product across mobile, car, desktop, et cetera. Then a personalization organization, because that's so important to us, that does all the AI and the recommendations and balances between books, music, podcasts, video, etc. And then we have three business verticals, music, podcasts, and books. So they have their own resources.

29:23And what we do is we start by asking them to resource as far as they can with the resources they have without stealing from each other. And then we get as far as we can, because you need to give them predictability for them to be able to plan their own work. And then at the end of that process, you may move some people around globally to make sure that you don't have something really important and there are two people missing. That's not optimal for the companies. You may move some people around, but largely we try to let people keep the resourcing. So lots of those problems that you run into.

29:52But I would say the biggest risk with this model, it sounds nice if you're perfectly synchronized. The drawback of that model is that the planning is very expensive. so you have to be really good at planning and we've had to build our own tooling we tried some external tooling for planning that wasn't good enough and if the planning doesn't work the overhead just grows very quickly versus execution we execute for six months in order for the overhead to not get too big but we can't go to a year then you can't react a quarter is too short it's too much planning overhead versus execution so the planning is the thing that you have to get really good at.

30:28And I'm not going to say we're really good, but we're getting better all the time. It's the thing that I care the most about, making sure that the planning is reasonably big. If you can do it, for us, it's critical because the whole of Spotify's product strategy is that we have large distribution closing in on 700 million MEUs for a single application. And our entire strategy is basically, we decided this many years ago before it was popular, but you saw the Chinese starting to build super apps, whereas the Western world built one app per use case. We've adopted the Chinese super app idea and said, the hardest thing is going to be to get installs.

31:04You can see the average number of installs from the app store dropping below one on average. So distribution became the most important thing. And then we chose when we did podcasts and later books and videos, we're going to build it in the same application because then we can leverage our own distribution. But that has drawbacks. You have to have an organization because then everything is dependent on each other. You're going to ship one app to the app store and everyone is a stakeholder. So you cannot divide and conquer. You cannot say, well, the book team, you can run ahead or the music team, you do this.

31:32No, everyone has to wait for everyone. So because of our consumer strategy, the company needed to be synchronized. And because it needed to be synchronized, we needed a really strong planning process. So it's an outcome of our consumer strategy. And what I would say is it's not the right one. It's the right one for us. We're good at doing global changes, like changing the entire UI because we're synchronized. But we're probably much slower than other companies at trying something because it needs to go through a lot of planning. I don't think you can win in planning. The best you can hope for is to be quite good at the important things and not so good at the less important things.

32:05I want to come back to something very interesting you said around the adoption of some of the tooling that's at the most cutting edge. So let's take Cursor as an example of a company that now everyone's familiar with$10 billion valuation. It seems like every software engineer is using Cursor to make themselves better. But the way you framed it is so cool that, yeah, sure, but that's new code primarily. That's a fraction of one eighth of their time. In the pie chart, it's a very small sliver that's being addressed by Cursor at big companies. Can you describe how you think this will play out? Because it feels like the public markets, especially, I guess private markets too, are very curious about how AI companies and products and tools will address this much bigger part of the pie that sounds like really hasn't been hit too directly yet.

32:50There are a couple of things that are interesting that I don't think are super obvious. One is, it used to be that every developer started using Cursor. But now, I'm starting to see a lot more non-developers using Cursor. And that's partially because the industry is starting to agree on this protocol called MCP, Model Context Protocol, which means that if you take your internal services and you wrap them in an MCP, you can speak English to your infrastructure. So if you're a developer now, or if you're a designer, for example, or a product person, let's say you want to prototype a feature in Spotify.

33:25One workflow is you take the existing Spotify, you double click and screenshot it, you upload that into Cursor and say, wire this up, clickable in HTML. And then if your services are wrapped in MCP, you could theoretically say, now wire this up to my like songs feed or something. And you can prototype even though you're not a developer because the infrastructure is wrapped in English language now through MCP. I think that's an important thing. So I think you're going to see many more people using Cursor than just developers. I'm starting to see, I had one of my PMs who is in Sweden. She's from New Zealand, doesn't speak Swedish.

33:58She did her taxes in Cursor, managed to wrap the Swedish tax authority in an MCP, not a developer. So I think It's going to grow outside of developers. But I think this points to what is actually happening in many of these big companies, which is why the startups can move faster. So if you think of a company like Spotify, it has tons of infrastructure. You have the database with play history going 15 years back. You have who was in the family plan. That's one server. This is one data set somewhere. Your taste graph is a data set and so forth. Now here comes the big AI companies and they give you this reasoning engine.

34:31Some of them are open source. So basically for free, you get what is getting close to AI. So now you have this thing that you thought would be incredibly expensive and you'll get it almost for free. It's a gift. You start using it. What is the first problem you run into? You say, how has my music listening changed over the last year? That's not exposed as an API because in the previous machine learning world, that data, the listening data 15 years back, it's on cold storage somewhere. And an engineer would have had to do an SQL job that may have taken a week to pull it up. Then you would have trained a model, then you put it back in cold storage.

35:04Now you want to be able to reason over that in real time. You need to expose all your data as APIs in real time. So actually, my biggest job to enable AI is not AI engineering. It's old school engineering, exposing all this data that we have so that you can have a reasoning engine reason for you as a product person, or actually for me as a consumer potential over my own data in real time. So I think that's what's happening. So the combination of another standard MCPs that you can wrap these APIs in, and many of these companies, at least us, trying to expose all of this data, means that a business person, a lawyer, a product person, a designer will be able to use Cursor without having to code.

35:46And they can actually at least prototype or talk to real services. That, I think, is the journey that we're on. It started with developers, but I think as you expose the infrastructure and wrap it in APIs, I think it's going to have to go outside. Is a way to say that and lose a lot, but summarize it, that what we've seen happen with developers is going to happen. I'm surprised that it's cursor that they're using. That's quite interesting. But with other similar tools and that just more of our work is going to feel like we're working with a team, speaking to a team, using natural language to prototype things, to try things.

36:19And that will diffuse slowly through the entire, not only just the hours of the software developer, but the hours of each of the other functional areas. Yeah, I think so. So it's hard to see where it's going to land because you're somewhere right now, but we're pretty certain that that somewhere is on this curve. So you can be pretty certain that the workflows you see right now are not going to be the same. And that's actually one of the problems. How much are we going to build for what we see right now? When you know the models are going to be more capable, there are going to be different tooling very soon.

36:49So you don't want to overfit too much to the moment. But a reasonable view of a modern company is that all of its data is exposed in real time and you have some tool on top like Kershaw or something else, maybe different tools for different skills, maybe a tool more. The licensing team at Spotify may have a different tool to reason over all the contracts and quickly say, do we think we can do this in that market and what do we need to license to do this? But also the product team could ask that licensing engine. We have 15 years of contracts, both current and previous. So this AI has a lot of insight into what music licensing looks like more than any single person in Spotify, if you train it that way.

37:28There will probably be slightly custom interfaces for different skills. I'm not sure which is going to win out, but I think it's going to look something like that. Right now, what we see people doing is they're sharing examples of prompts they use for the workflows and then prototypes that they've used. And that feels like very much a point in time. It's kind of hacky and different things. If you were to calibrate the world out there, so few people have the inside view that you do, where you're excited by this technology, you're trying to embrace it, you're only able to embrace it so fast in the ways that we've described.

38:00On a one to 10 point scale or something like this, what score would you give how much this is impacting you so far and how crazy this might get? People are very excited that this is gonna literally change everything. And there's some people that are actually worried about how much, how powerful it might be. From a practical real-world standpoint, could you calibrate us a little bit as one of the few people that actually is both excited about it and also faces reality on a daily basis? If you want to be as realistic as possible about it, you take the developer use case. I've seen studies from other big companies that if you actually measure out of a developer's time, the speed up is 7 % or something, which sounds very disappointing because of all these things.

38:43Coding is a small part, NetNew is a small part of that, and so forth. So I think right now it's a bit overhyped in terms of actual impact, at least for these big companies. But I think it's going to turn it into the opposite. And I think right now people are overexcited versus the actual impact. But I think the opposite is going to happen. I think it's going to have tremendous impact over the longer term. What I see people doing right now, it depends. I mean, I use it a lot personally. I see a lot of my developers and product people and designers use it all the time for just productivity purposes.

39:16putting things into an engine, asking it for the summary and so forth. Those things happen all the time. It's hard for me to estimate how much that speeds them up already. It certainly does. But I think the really big impact comes as you reshape these companies from this technology. Right now, we're just tacking it on top. But as I said, you have to reshape it and rebuild it for this work, where a reasoning engine can reason in real time over the entire company's data. But that requires actually a lot of retooling. That's why startups are ahead. They don't have to rebuild. They don't have 15 years of data.

39:46So they're probably in the future, which is why they feel like, no, no, good stuff is wrong. The impact is really big already. And I think it is for a startup. I think it takes a bit longer for big companies. And big companies like us, we have to shape up and accelerate in order to not be behind. I'm sure they would all like to have 700 million monthly active users to experiment with, though. On that topic, you mentioned going through mobile and the experience of not only was everything was changing as a result of mobile, but actually the business model also needed to change. We've really talked about product so far, and there's more to ask about product, but talk about business model.

40:22What would be the world in which, as a result of this technology, Spotify's whole business model needs to change, and how do you go about evaluating something like that? We've seen a few of those examples of business models, and I tend to tell my product teams, and everyone says that the world is disrupted and changed by technology, and I think that's true in the sense that the underlying force is technology itself. and it's this gift that keeps on giving it gives you computers internet smartphones ml ai quantum computing and these gifts keep coming almost on a schedule and they actually come closer and closer previously technology companies were not called technology companies as a side note they were called car companies but it was a technology companies or pharmaceutical that was the state of the art technology right then but because these microwaves came so far apart they call themselves a car company they never became ubiquitous technology companies it overfitted to that I think somewhere in the 90s around Google, Amazon, etc.

41:17These macroeuvres started coming so fast that people try to pin them down. Amazon is a books company. And they were like, no, not really. We're doing books, but here's other stuff we're selling. And then, okay, you're the everything store company. It's like, no, not really. Now we're selling Amazon web services over here. So I think these companies are the first set of companies to have technology as the strategy. The previous ones took one wave as the strategy. and IBM comes along and does computers as a strategy or first memory and so forth. I think this is the first wave of general technology companies, which interestingly might mean that they could be, I mean, companies almost always die after a while.

41:53These could be the first companies that never die because they're ubiquitous technology companies. Whatever the technology gift is, just try to have a company that can quickly wrap around it, figure out the product and business model. So I think that's interesting. And that's how I think about Spotify. Yes, we're a music company and then a podcast company and a book company and a video company. But it's really about trying to anticipate technology, figure out what it can do, and then adapt the product and often the business model. So I said mobile was one of these things where we need to change the business model.

42:22And I think what happens when one of these technology gifts comes along is there is a big change when the technology happens. Piracy, big havoc. But the real change happens when someone also figures out the business model. So I tell my product teams, technology can do good things and a new business model can really change the world. But without a business model, there's seldom like large scale change. You can destroy a lot of things, but you never really create value. So mobile was the first where we need to figure out a free tier on mobile without cannibalizing our pay tier. And what we did there was we looked at our data and saw that 50 % of premium users were listening in shuffle mode.

42:58So we said, what if we take shuffle as a feature, give that away for free? It should be 50 % of premium consumptions are very valuable, but it's not going to be 100 % of anyone's premium consumptions, no cannibalization. And we managed to create a tier where you could playlist all your favorite songs in a playlist, press play, put the phone in your pocket and listen forever for free in the background. So that was a business model innovation along with technology. The most previous one was audiobooks where there were audiobooks in the US a la carte. And sure, we did some nice innovation around being able to stream that book.

43:31But the real thing is not stream a book. You've been able to stream audio for a long time. The real innovation there was the business model to be able to bundle audiobooks into Spotify Premium. It's almost like music. Music was also a la carte and quite niche. And once we made it an access model with no marginal cost, it got way larger. And that's what we think about audiobooks as well. So we've seen a few of those and managed to adopt them. To your question, is AI going to do that? Do we need to change the business model? i'm not sure i think there is one glaring thing that is different which is the previous vc model coming all the way back from chips and silicon was you make a big upfront investment and then you amortize and you get to almost zero marginal cost that's how software worked it's not how ai worked the marginal cost is high and you need to cover it so you could say that that should change everyone's business model you're going to need to somehow either monetize very effectively through ads or charge users.

44:25And you see OpenAI being a subscription product. And I think you're going to see more of those. So the marginal cost is a net new thing. For Spotify, it's interesting because we're like the one technology company that always had a marginal cost. One more stream was a marginal cost to labels. So we grew up in a world where if we were too successful on the free tier, we could go bankrupt overnight, which was never true for Twitter or Facebook, which is why VCs said, just go crazy, worry about monetization later. Spotify could never do that because we could go bankrupt overnight. So we always had to worry about monetization and the balance between free tier and pay tier conversion and free tier monetization.

45:02So the good thing for us is we're fairly used to marginal cost in our business model. I think you're going to see those things. It's very likely that some consumers are going to want tons and tons of inference. And because that's a marginal cost, you're probably going to have to pay somehow for that as a consumer. So I think you're going to see more tiering of consumer products based on how much inference you want. But for us, that's not that new. We've had several tiers already. I'm curious because I'm an investor in a company called Etch that's going to be one of these companies that pushes down that inference cost.

45:31Like the history of compute, you're going to see this incredible consumer surplus and consumer benefit that comes from cheaper and cheaper unit by unit inference cost. But the countervailing force is that we would just use more of it, more reasoning tokens, more whatever. So it makes me wonder how much more you can imagine better models being useful to you. It seems like if we just froze reasoning and model capabilities today, we probably still have decade plus of digestion to do of how we could use these models to make better products, better features, whatever. Can you imagine another couple orders of magnitude better models opening up lots of features that you can't currently do?

46:10Is that a thing? Or do you think we have what we need and therefore inference we could expect to be really cheap? so i both subscribe to the product overhang idea that there's a huge product overhang and if we froze i think we would see products shipped that look amazing for several years before we exhausted what we have so i subscribe to that but i also subscribe to that there is no limit for compute eventually you get to computronium but if you look at just the physics of computronium what's computronium it's the most computational universe could do theoretically yeah we're very far from that limit.

46:43So I think we're going to go all the way there before we stop. And I think we're going to be very inventive. There is a nice analogy. I don't know who came up with it, but I think Ben Evans talks about it quite often. You know, when the spreadsheet came along, the idea was the same. Now all accountants are going to go out of business. What happened was we could just not imagine if calculation cost went to zero. What's going to happen is you could imagine that the The value of doing that is going to go to zero because there were so many accountants in the world. So what happened was we just started doing massively more accounting.

47:17When there's no cost to spreadsheeting, you're going to start to do models to predict the futures of this asset or good or something into the future forever. We just came up with so much more spreadsheeting that you could do. And it's bigger than ever. I think from a financial point of view, when the cost of something drops, the demand usually increases more than the drop. And I think that's bound to happen with intelligence. It is the ultimate thing. And to say like, no, I have enough intelligence. It's not interesting. I think we're going to be ashamed of how mundane things we spend inference on.

47:50Could my coffee be one degree warmer tomorrow? If it's truly no cost to asking the questions, I think people will. Maybe now's the time to ask you about sitting in the back garden with David Deutsch and talking to him about this concept of the beginning of infinity. Computronium made me think of your interest in this topic and your answer there that there's no end point here. it's just going to keep going. We're going to keep learning, keep deploying our new technology. Can you talk about that book, why it influenced you, your conversation with him? Yeah. So David Deutsch has been a hero of mine since I read The Beginning of Infinity.

48:21And then he wrote another book called The Fabric of Reality. He's considered the father of quantum computing. Obviously, quantum computing is one of these gifts that technology is going to give us. And it's about to get very real, I think, very soon. So I've always been interested in because quantum mechanics is the most insane thing on this planet. We live in what we consider this reality, but if you go to the bottom layer, this is not reality. It's just some three-dimensional projection that we live in. The Fabric of Reality had a big impact on me. He's an Everettian, he believes, in multiple worlds scenario.

48:54I read that book and it blew my mind. Then Beginning of Infinity is maybe his most famous book, whereas Fabric of Reality is really about quantum computing and how quantum computer works. The beginning of infinity is very philosophical and he has a bunch of big ideas there. He's a very positive person. And now at 70 plus, I finally got to interview him in his garden in Oxford. He's not of great health, so it had to be outdoors, you know, distanced. And everyone is very negative on the future. There's so many problems. AI could go wrong and all things could go wrong, climate. He's actually very positive about the future.

49:28He's clear that there are risks, but he sees us going out there into the stars. I asked him, where do you think we are in a million years? And he's like, well, maybe we're this far outside of the solar system, but not quite there. He's very certain we're going to get there. He's a very positive person. And when I asked him about his life, he's very content with his life. He's very happy. So he's just an inspiring person still at this age. I wish I would be like him in that age. But this book has a few concepts that I've tried to apply at Spotify. And one of them is he talks about the power of explanations.

50:00And he thinks the human mind is infinitely scalable. He does not think there's a limit to what we can understand because of explanations. And I think this is something that a lot of people, I agree with that, but a lot of people disagree. Certainly there are things we could never understand. His view is no, there is no limit to what we can understand. We are the only species who broke that barrier because we have explanations. Other species have pattern recognition. They can do things and learn the pattern that this works. There's some cultural transfer maybe of looking at someone else doing that pattern.

50:30A bird can see another bird. Some species can teach their kids. But they never produce explanations. He has a definition of a good explanation. He's very inspired by Karl Popper as a philosopher. It's his house god. So he takes a bit from Popper. He takes a bit from science. So he says obviously that a good explanation has to be falsifiable. But he says a few other things that I think are obvious in retrospect, but not before. He says that a good explanation has to scale, has to have reach. What does he mean with that? He says that some explanations explain something quite locally. You can have an explanation about, for example, the sun revolving around the Earth, which explains a bunch of stuff, but it doesn't scale to other planets.

51:11It's a better explanation is to have the Earth revolving around the sun. It just scales better to different scales. So a good explanation has to scale up and down. A good explanation has to be compatible with all previous explanations. But most interestingly, he says that a good explanation has to be hard to vary. This I find very obvious, but also very non-obvious to people. So what does he mean with a good explanation has to be hard to vary? He means that, for example, if your explanation for the weather on the planet is that now Thor is angry, so there's thunder there. It's an explanation, but it's too easy to vary.

51:48You can say, well, now someone else is angry. They also had a hammer. It's too easy to vary and get the same result. A good explanation, if you move one of the parameters, the entire thing is not predictive anymore. Then you're probably close to the truth. I think this is so interesting because the problem with most conspiracy theories that people love is they're so easy to vary. You can just exchange that character from another crazy person and did something crazy and still going to produce the same thing. So if it's too easy to change people in a conspiracy theory, it's probably not true. So I think that's something very powerful.

52:17Good explanations need to be very hard to vary. So this is something I've tried to instill in my org. And I think there's an interesting meta point here, which is people ask me as a product person, how much of product development is magic and how much is science? And I try to be provocative in saying, I think it's exactly 100 % science and 0 % magic. And people get provoked because it implies that there's no skill. I say it to provoke. what I mean is that certainly people are going to have pattern recognition in this neural network they've seen a lot of examples that's what we call seniority and people have seen a lot of things they're going to get instinctively to the right conclusion faster than others so that is valuable and I want lots of seniority I don't discard seniority and it brings you a lot of value you can save a lot of time a lot of mistakes but the reason you call it magic is because that person can't explain it.

53:12It isn't actually magic. It's just science. It's just you are not smart enough to explain yourself. If you could think even further and explain it and come up with an explanation for what you see the way David Dodge does, it's so much more valuable for the company. If you have a theory, instead of saying, no, Patrick, my intuition is this, you're not smart enough to understand it. So I'm not going to tell you, just do what I say. Maybe I'm right. Maybe I'm wrong, but it's not very helpful for you. When I leave the company, you're going to take over. You're like, I have no idea why they did that.

53:39You have to develop your own intuition and your own pattern recognition. But if I come up with an explanation, which is, I think the psychological behavior of people, you know, it's like Kahneman's loss adversity or prospect theory. I think people value losing something one and a half times the value of getting it. So therefore we should not just launch feature and test it because it's 1.5 X hard, more expensive to remove it. Then you have a theory and it can spread across the company in a week. And now everyone has that. So I really want to force people in my company, even if we see something working in an A-B test, I try to tell them, I don't want to launch it until we at least have a theory of why it works.

54:14Even if it's super clear, there's a lot of pressure to launch it because there's engagement value and monetization. But I want you to at least have a theory because then over time, the company builds up a consumer theory. And if you have a strong consumer theory, then you can predict things that were very unlikely. What David Deutsch also says is that pattern recognition will iteratively get you more on the same path, but it's never going to jump all the way from the geocentric to the heliocentric model. Only an explanation can take you to quantum physics. Entirely unintuitive. No pattern recognition gets you to maybe it's a wave and a particle.

54:48What's an example internally of a great explanation that then led to the geo - to heliocentric type of jump? What's an example of how that actually played out? I think a good example that is public is the free tier that I told you about. We only had a paid mobile tier. You're actually paid to get mobility on Spotify. Now smartphones are scaling. users don't have a computer we need a free tier the competition that was youtube they were foreground on demand with video the patent recognition the obvious thing would have been to say let's do that it's proven but what we did instead and specifically attributed person named charlie hellman was to reason around it from first principles and say okay let's look at our usage of spotify if we limited our license to the same thing it only works in the foreground As soon as you look at the screen, the music stops.

55:36How much of the listening is in the foreground? Turns out back then it was 9 % or something. So you have 91 % of the use case being in the background. We probably want to get something else. The user need there is probably background listening. And then you look at the app store. Is there a way to listen to music for free in the background in the app store? The closest thing was Pandora, but that was radio. You could not listen to your favorite songs. So then we said, we would like a consumer product where you can listen to your favorite songs with your phone in the pocket forever for free. So the problem with that is that's almost a premium use case.

56:10If we just launch that, it's going to cannibalize our premium tier. So what do we do? Then we looked at the premium usage and we saw that premium users about 50 % of the time they were shuffling their playlist. They were using on-demand features, searching and clicking and playing specific songs 50 % of the time, but they were shuffling playlists 50%. So then we thought, what if we take this, that seems to be something that even when you have on demand, you voluntarily shuffle. It's a big use case. We give that away for free. That should mean that none of the premium users convert back to free because they still want their 50 % on demand, but you're giving a lot of value away for free.

56:45So we try to model a consumer need, reason around it, came up with this shuffle background here that was very, very, very unintuitive. Even the people inside the company say, that's a terrible idea. But we trusted the data. And I was even skeptical of it myself. I was like, look at this on demand. Shouldn't we try time caps? Or a lot of people just want us to try long free trials. But the problem with the free trial is even if Nokia, I think Nokia comes with music, they tried a year long free trial. But even then the user knew that if I start investing in playlists now, a year from now, my playlist investment is going to disappear.

57:17So they never started investing. So we went with this shuffle tier and this is what made growth explode. And to this day, that's our differentiation against the other services. It's the only way to listen to music for free forever with your phone in your pocket. So that's an example of theorizing and explaining rather than pattern recognition. I'd love to talk about the evolution of the relationship with the music industry. It's a company that unquestionably has wholesale changed music, which is so interesting and so cool. You've been here a long time. Thinking back to the early days, it's amazing the impact that it's had.

57:50And from an investor's perspective, one of the things that many were always keyed in on, And it's just the gross margin of the business. Just how much transfer pricing problem are you always going to have that no matter how big you get, the music industry that owns the IP is just going to always take their same cut of the meat. Talk about how you've thought about that change over time. It seems like it's been both a good relationship for them, but also a very patient path for Spotify. Maybe just give us the insight into how it's worked and how you think about it. Yeah, for sure. I grew up and Spotify grew up in the era of piracy.

58:24in Sweden, which was the worst market. And there's this famous quote from a UK label exec to a Swedish label exec around early 2000, where the Swedish label exec showed the P &L of one of these Swedish companies. And they said, that's not a business. That's a hobby. That's how broken it was. And that's actually why Spotify could happen because the music industry was prepared to take risk in Sweden. And I want to give a lot of credit to the music industry. They took a lot of risk with Spotify. Spotify took an enormous amount of risk, enormous amount of capital risk. We MG'd a lot. We ate a lot of the risk, but certainly they took a lot of risk.

58:58I think the music industry certainly deserves the success, as does Spotify. I joined in 2008, somewhere around 2012 or something. I started saying that my team, the R &D team, and all of Spotify, we are the R &D department of the music industry. And first people were like, what do you mean? And I'm like, well, look at it. It's an entire industry that doesn't have an R &D department. Mobile phones has an R &D department. It's called Apple or Google. everyone has a lot of R &D, but there's no R &D spend in the music industry. And I think that's turned out to be true. And if you look at the trajectory, this year is the first year of profitability for Spotify since its founding.

59:36People say that there's a lot of talk about Spotify sharing enough of the revenue. We share about 70%. But the truth is the other 30 % we haven't kept. We've invested all of that in the music industry and then more. So we were unprofitable for 15 years. We just invested, invested, and invested. So a ton of patience. And at the same time, actually, the music industry has been profitable. Spotify has been unprofitable. I think it's fair to say we are literally the R &D department of the music industry. We invested and have had losses for 15 years and the music industry has been gaining profit. Now that is not sustainable forever.

1:00:08We needed to get profitable. We can't beat the R &D department of the music industry unless we can have the best machine learning engineers, the best product people, developers, et cetera. For that, you need to be profitable. It turns out these people are expensive because they're sought after. We are very, very patient and long-term company and we invested for a long time, but it was just time. About two years ago, we decided now it's time for us to become profitable, to take control of our own fate in terms of being able to invest in ourselves. So yes, we're profitable, but we're actually investing almost all of that back into more people, more product, more AI.

1:00:42Now we just have our own investment vehicle instead of having to ask private investors initially or the street for more money. So that's how I think about it. Really as the R &D department of the music industry, I think we've done a good job. This year we paid out over 10 billion and that's up from 1 billion, I think. Almost 10 years ago, it's just steadily increased. The music industry is bigger than it ever was. People still talk about the heyday of the CD era. The truth is the music business is bigger than it was back then. So this is the best it's ever been. It is better than ever, more money than ever.

1:01:16The pie is both bigger and higher, but it's also getting sliced up. But that's because more people take a shot. And it feels very wrong for us to say, no, the creators up until 2020, they were good, but no one should be able to try after 2020. New creators should be able to try to do music. So that's the dynamic. And I think a way to think about this is people talk about the per stream payouts and so forth a lot and spotify should share more per stream there are two things that are happening when other companies say that they share more per stream the industry doesn't pay per stream they pay per subscriber we have more than twice the engagement of our competitive services so if you take the same ten dollars you listen twice as much as spotify the per stream is half so these other companies have higher per stream because they have a worse product we've learned from the labels that we We have twice the engagement and half the churn of competing services.

1:02:06So that's a curse where the per stream model is. The better we are as a product, the lower the per stream is going to look. But we're looking at the aggregate number and we're leading everyone else there. We're the vast majority of these payouts. So I think if you look overall, the model is working. We took a lot of investment and now the industry is getting a huge return. And Spotify also is profitable now. And the way to grow this pie is now we are closing in on 300 million paid subscribers, closing in on 700 million MAUs. It's about 500 million paid subscribers, I think, in the world. We're almost 300 of those.

1:02:40But that's half a billion out of the world's population. If you look at markets like Sweden, on average, you can just look at the public numbers, we convert about 40%. But if you look at the mature markets, it won't give you the exact number, but it is much higher. And if you look at the emerging, it's lower. So the average is 40. that's not the average across the world that's a blend of low and high converting and so far throughout our history everything starts to look more and more like sweet and the more time passes so the solution to this is just to scale it faster better free tier that gets more people on that converts to premium we think there should be billions of people paying for music and that's how you make the pie truly bigger the rev share is actually a red herring so let's say that we share 70 % today-ish, let's say two-thirds to make it easier, even if we were a charity and we paid out 100%, that would only be 1.5x what you get today.

1:03:31So if you think X pendants per stream is too little, even if we were a charity, it would be 1.5. The solution is not the rev share or giving away the vast majority. The solution is to quickly scale the amount of people paying for music. And if you just look at the numbers, you just have to keep going and it's going to get to billions of users paying, and then several billions. Then the music industry is absolutely massive. I just think the music industry is undervalued. Terminally, it's going to be much bigger than it looks. I'm curious how you're thinking about the podcasting world. This is something that we're sitting here doing right now.

1:04:04I've been doing for a long time. Now it seems we've entered this interesting new era where when I started doing this, I remember it was quite, I would call it low status. When I told people about it in 2016, they either didn't know what it was or thought it was silly. And now, especially in the U.S. with what happened around the election and the importance of podcasts in the election, it seems as though it's hit some tipping point where basically anybody that might make sense to have a podcast now has one or is launching one. And it's the corporate marketing strategies to get a podcast and it's the communication strategies to go on them.

1:04:39So it's really exploded in importance and visibility. What role has and will Spotify play in all this? And just what do you think about podcasting and its importance? The reason we went into podcasting, one thing that I'm very precious about when it comes to Spotify, and so is Daniel and the other co-president, Alex, who's my closest partner, is that there are many ways we could go as a company. And I think your business model to some extent steers you. If you're an advertising business model, mostly you're going to be steered towards any additional engagement. Fortunately for us, we're mostly a subscription-based business model.

1:05:16So we focus more on retention. And you're going to vote with your wallet every month if you want to keep paying for us. We're not as steered towards engagement at any cost. So having been at Spotify for a long time when this happened, one of the things that made me feel very good about Spotify was that when people used it, when they lost an hour on Spotify, they felt very good about it. If you lost an hour on music, you come out feeling like that was a good hour. One of the reasons I really pushed quite hard for podcasts in the company was that I was using it myself and a lot of our developers were using it.

1:05:45And I saw it being hacked into the product at Hack Week every year. People wanted them there. And we just said our developers is like a small sample of the world. What if they're a good sample of the world? So that was one push. We saw people using it internally and hacking it. But what made us decide on it was that it was this format. Everything in the world was getting more and more short form. People were bite-sized and attention spans were going down. And there was this counterforce, which was long form discussions, deep. People spoke in full sentences about quantum physics or whatever. And that just felt like something very important and good for the world.

1:06:20And so we looked at it. We saw that it seemed to be growing from a small base. We saw the biggest competitor being asleep at the wheel. We did basically the Peter Thiel idea of it's better to go after small markets early and bet on organic growth and try to take a small share of a mature market. It looks less risk in the mature market to get 1%. But the thing people miss is the customer acquisition cost in a mature market is just massive. Whereas the customer acquisition cost in a new market is usually small. So we decided to go for it because we thought it was something that was in line with music.

1:06:51If you lose an hour in a deep podcast, you come out feeling like you learned something. And this is the reason we also went into books because it's in line with that. We want to be this nutritious service. And there are two litmus tests for this. One is if you lose an hour on Spotify, how do you come out feeling versus if you lose an hour doom scrolling in the bathroom, how do you feel about that? In one case, you feel like you ate a lot of candy, like you had a lot of energy in you, but it's bad calories. In the case of Spotify, you feel like you learned something. The other litmus test that we have is see a lot of parents restricting screen time for their kids and saying, go to Spotify instead, which means that expresses how they feel about it and how we feel about it.

1:07:32So that was one of the reasons to go into podcast. It was part philosophical, but we also saw the market opportunity of a small market that was poised to grow. And we saw need in early adopters trying to hack it in. And then we did this bet on leveraging our own distribution, combining it with music, saying that the market is this big right now. But what if we could expose podcasts to people who listen to music? Could we grow the market? so that's the bet we did and the truth is audiobook is something similar in the u.s audiobooks was a very niche behavior 10 11 million or something people who paid for them a la carte and the idea was that's a limitation because of the business model when you pay a la carte you're not going to explore new books at 15 per book cost just as in music when you pay 99 cents per song you're not going to soundtrack your sleep it's too expensive at 99 cents per three minutes but what if we have no marginal cost model where you can just explore is audiobook much bigger than it looks is the business model that is wrong so again it was seeing a market that looked pretty small but you can see in the nordics where you have the access model that it's getting very mainstream so a bet on the market but it was the same philosophical discussion are these good calories is this nutritious is this in line with spotify's mission of being the place where you go when you want to feel good about yourself instead of when you want to feel bad about yourself.

1:08:52I remember the very first time I ever talked to Daniel walking along the West Side Highway here many years ago, he talked about this notion of Spotify needing to be better than free. It was a cool idea. If you think about podcasting, it's very different than music. When someone listens to this show on Spotify, you don't owe me anything. How do you think about the way that podcasting and then obviously books is a little bit maybe more like music and I'd like to hear how you think about it. How do you think about if that's the supply of the stuff that people are listening to on Spotify or watching on Spotify, the ways in which that affects your business model and the bundle?

1:09:26We didn't know before we started if podcasting and later audiobooks would be cannibalistic to the other media types or not, but it turns out it's not. So the easiest model to think about it is Spotify is a bundle now. You pay some price or you have the advertising based here and you get a bunch of value and our job is to try to increase the value you get so you value it more and then over time maybe we can capture some of that value by price raising we price raised a few times which is part of why we're profitable now but that's because we had user surplus in value that's because we kept just stacking value and value are two things value are features like personalization and just a really good product but the other value is different types of media.

1:10:09So what we see is that you have a user that uses music, they have a certain amount of consumption. When you add podcasts, it's just more, it's not more. It's an infinite game, it looks like, at least for now. We haven't run out of time in the background yet. Then when you add audiobooks, it's just more retention, more time spent, and more willingness to pay. So that's how we think about it as a business model. Then on the back end, they have very different business model. I think we may be one of the most complex companies in the world on the back end, because Music is a pool-based royalty model.

1:10:40Podcast, as you know, is advertising-based largely, but now we also have this Spotify partner program where you don't have Spotify ads in the premium tier if you're paying, so you get more uninterrupted. So that's another business model, which is part of the premium bundle. And then you have audiobooks, which the publishing industry works in a third way, very different, where we also have a certain amount of time included in the premium tier and then a top up if you run over that. One of the really complicated things about Spotify I don't think is appreciated is on the front end, it's one app, one consumer, just go between them.

1:11:14But there are very different implications of where you click in that UI in terms of triggering different business models and so forth. So to model a company financially, it's actually quite hard. We have to predict your user behavior where you click matters. And we have the personalization that has different impacts in terms of cost and so forth. so we've had to build a system we call it the spotify machine and that's why i said i have one experience organization and the job of this experience organization is to make sure that all of this complexity all of these teams who theoretically could be set up to compete with each other to fix their pnl that never ships to the user there's one person who is the responsible person for the consumer experience and that person's job is to make sure that as you go between mobile and desktop and car and speakers, the thing makes sense.

1:12:00It's like the gatekeeper against the org, holding them back from the user behind them, protecting the user. But it's also the same in personalization. I have a personalization organization because you have the same incentives of programming music versus podcast versus books. Everyone wants to take market share and so forth. So it's the same problem. We have to optimize for the user and sort of protect the user from the internal incentives of teams and business models. That makes Spotify a pretty unique company. We're like one thing on the front end and we're many different things on the back end with different products.

1:12:34If you think about, let's say five years from now, and you dream as big as you can possibly dream for where Spotify might go from where it is today to where it will be in five years, paint us that picture. Certainly, I hope we've cracked the billion user line, but as a subscription, I hope we're becoming one of the biggest media subscriptions in the world and we add more and more value to that. So hopefully music is bigger than any of us. I'm hoping that audiobooks is a mainstream phenomenon as it is in Scandinavia, where there's almost as many people who listen to music listen to audiobooks. I think that would be a net good for the world.

1:13:10But I also hope we've added a few more of these verticals. I can't say what they are. The subscription model, the bundling model that we didn't talk so much about, we can differentiate on product or on content, but largely we tend to license commodity content. We don't work with exclusivities, at least not anymore. we tried in podcasts for a while. So you can differentiate on the product and consumption of the commodity content, but you can also differentiate it on the offering. So for example, if you look at Spotify now versus other offerings, some other offerings have the same music, some other offerings have some of the same podcast.

1:13:43You can not really find the combination of music, podcasts, and audiobooks. That's a unique thing. So to use bundling theory to create more and more of a differentiated unique thing that is Spotify, I think it's very exciting. And I think you will see more innovation on the bundling business model in addition to the product. I'm the product guy, but I'm very interested in business models. I've been a CEO myself. So I think you will see a lot of innovation there. What's the key to a good bundle? And I'm also curious, you said you experimented with exclusive content that was only available on platform and less of that now.

1:14:16What drives a decision like that? And how do you think about other people that might want to create a bundle somewhere else? when we looked at podcasts you look at something like netflix and this beautiful business model and insanely good execution as well on top of that and it looked to us like that could be interesting i think when you're a product company that works with commodity content you always had this envy of what if we could differentiate through content then life is going to be super easy you always think the other thing that someone else is doing is easy and your thing is hard and it's usually very hard to do the other thing so we tried exclusivity in podcasts as a way to differentiate this service but i think it was ultimately a bad bet because the macro trend for the whole thing with podcasts was that the production cost was so low jorogan was initially sitting in his trailer the production cost was low and then go in and do exclusivities on top of that is kind of counter-purpose in a way.

1:15:13The whole point is more like YouTube in that this is very cheap content, so you can get a lot of it. You don't have to be right. As soon as you go into an exclusivity game, you got to be right. You got to be a content picker. And that's a very hard skill that Netflix does extremely well. But we had this opportunity. We didn't have to pick content. We just get all of it and use machine learning to serve you what you wanted and me what I wanted. And there wasn't this capital intensive need there that there is in producing costume dramas. It's a bad strategic decision that we did. We also betted a lot on celebrities and they are celebrities, but they're not always good podcast hosts.

1:15:46And the podcast hosts that were really good, they grew up through this organic system. So there are two ways to always be right. One is to always guess right. The other is to just change your mind whenever you're wrong. So we decided to change our mind and say, this looks like the age of syndication. Creators actually want to be everywhere. They create a video or they create music. They want to be everywhere. Okay, let's embrace that. In music, we were always a platform. We never played with exclusivity. We said, we want the maximum catalog. Books, we're doing maximum catalog. Let's just embrace that in podcasts as well.

1:16:18So we pivoted strategy. Save us a lot of cost, which is part of what we're doing well. And it's also improved the catalog greatly. And now we're on a really good trajectory with our podcast viewing. So it was an example of bad strategy. And I think the important thing is to admit it and change your mind. The real cost is when you try to defend your past decisions. Stick with a bad idea. What things do you do outside of Spotify in your life that most prepare you or make you capable to do the best job that you can in Spotify? I think the world is moving very fast. So a lot of my time is just trying to keep up with what is happening.

1:16:54I was on a vacation in Lisbon with my family recently. and I spent a lot of time with them seeing Lisbon which is a beautiful city but then I asked them for one day off from work and off from the family to just indulge myself this time I was going back to trying to code a bit use all these new tools stay on top of what's happening sometimes it's reading physics or math or something it's a combination of keeping up with what is happening which is hard because it's moving so fast but also stimulate myself mentally I have to have something that I'm excited about at any point in time. And it can be new things like AI and what it would mean, but it can be age old things that I just didn't know, like learning more about physics or math or something.

1:17:38I've read a lot of philosophy for a while because it's just an interesting area. You think through all the big questions of intelligence and consciousness and all of those things, and you can spend 10 years there just reading all of that. And now I feel capped out a little bit. When you start reading, you're like, yeah, I'm going to crack this. And And then turns out I didn't crack it. People have been trying to crack consciousness for a while, but it's so deeply interesting. It kept me excited about life for a very long time. I was never a big math person in school. I was okay, but not great.

1:18:06But I found myself getting very excited about math the older I got. As you start reading a bit of philosophy, you get into things like Gödel's incompleteness theorem and constructive mathematics and these things that they're loosely related to work. But they keep you energized. But they keep me energized. And actually, it turns out that a lot of my product people and engineers are deeply interested in these things. So I just have something very interesting to talk to people around me about. And then I do sports. I do Brazilian Jiu-Jitsu with my kids, which is very rewarding. What does that tell you?

1:18:37Humbleness. You come in and you think you do something and you get absolutely smashed by someone half your size. And they're not even sweating. And you're like, okay, technique matters. It's technique. It's leverage. Yeah. Yeah. The beautiful thing about Brazilian Jiu-Jitsu is that the belt thing is real. There's a long story behind it, but the net is that a Japanese person brought Jiu-Jitsu to a Brazilian family. There were a bunch of brothers there who fought a lot. There was one brother that was just underdeveloped versus the others. He was just not very strong. So he could not beat his brothers.

1:19:08So he started taking Japanese Jiu-Jitsu and figuring out how he could just use physics, just leverage. And slowly, slowly, he started beating all his brothers and that became Brazilian Jiu-Jitsu. So it was literally, he had to solve the problem. He could not use power. I didn't know that. And then this family put up all these competitions. I like it from an evolutionary product point of view. They said, okay, anyone come here, karate, kickboxing, just try it open. They fought in these basements, just evolving the sport, proving that it was real. A lot of martial arts, it's magic and secret, and they never test their skills.

1:19:41It works very well in practice. The other thing I like about it is that I've done a lot of other martial arts, boxing and Thai boxing and stuff. Those things are great as exercise, but for self-protection, it's not very good. You cannot punch someone in the face. You're going to get sued as protection. The beautiful thing about martial arts, which is called the gentle sport is you control people, you constrain them, and you can adapt to the level of violence. This is why police use jujitsu and not Thai boxing, because you can regulate the violence to the other person. You can control and without hurting them.

1:20:14So that's why I think everyone should use it and practice it. It's good both for self-discipline because you get humble. It's also actually useful and you can use it without harming other people. People probably don't know this because how would they? But Spotify, you and Daniel especially, have been probably the most influential people and certainly the company on me and how I've thought about building our businesses over time. And a lot of that comes back to the stuff that you don't see. I've purposefully talked about a bunch of it today with you, the bets board, the complexity that's hidden behind a beautiful consumer experience.

1:20:48You were the first person years ago to describe the bets board concept to me, and we've used that very effectively and so many lessons from Daniel on how to think about what matters to users. And I think Spotify is not only an incredible product, but it's also one where the product is a reflection of the company behind it. And I think it's one worth studying by listening to conversations like this one, because for me, what it's done is raised the bar of ambition and the standard for excellence of how a company should be constructed to mirror the needs that it has, its unique needs, but also just the character and the discipline of the people running it.

1:21:22So it's been so fun to do this with you. And thank you so much for all the lessons over the years. Well, you know, the closing question that I have for everyone, what is the kindest thing that anyone's ever done for you? The thing that made me really excel in my role was being allowed to take a lot of risk by Daniel. So I've actually screwed up a bunch of things in Spotify that didn't work. And I never felt that I was going to get fired for it. And he actually encouraged that. And I got a second chance. And that's what made me have the higher ambition instead of holding back for risk or failure.

1:21:55So I think it's a series of those things, being allowed to mess up things that has probably had the biggest impact on my professional career. Can you give an example of a bad mistake that you made and how he and the org made you feel through that process so that you could be reemboldened to take more risk again? I was interested in new user interfaces. Many years ago, I took the company very hard on a journey for an interface that at the time was very provocative. The idea was Spotify just starts playing things. You swipe up to get to the next genre and you swipe left or right to get other things within the same genre.

1:22:35And now you would say that sounds almost like TikTok. This was before Musical.ly. But two things happened. It was very provocative. It started playing things without you asking. So people were upset, but I pushed pretty hard because I was convinced that immediacy. The idea was you just sound your way to what you want to hear in a very low friction interface. And it was maybe a decent idea, but it was before machine learning. It just did not work at all. You could just not get there. And we built this. It was called Moments, the UI. We used editors on the backend, which just did not work at all.

1:23:06So the idea was far, far ahead of where the technology was. And it costed a lot of money. We actually announced it. There was a video of us presenting this user interface and so forth. People luckily forgot it, but it just didn't work. We had A-B tested it and it looked okay, which is why we launched. Then we discovered there was a bug in the A-B test. Oh my God. When it was live and it actually underperformed drastically what we had. So we'd had to roll it back. and I had taken the entire organization on this excursion that lost a year or something in a very competitive business. That was a good opportunity to get fired.

1:23:42And I didn't. Daniel was like, I understand. I agreed with the thoughts and the ideas. What was the mistake? And the mistake was the machine learning was not there. We were not good enough to get you there in enough swipes. And he was more like Jeff Bezos, measures the inputs, not the outputs. If the inputs are bad, if the ideas are fuzzy and stupid, that's a problem. but you're not going to be always right even with good ideas and i heard him say this jeff bezos quote i judge you by the inputs you had not the outputs because the problem with judging the outputs is you could just get lucky and you get promoted even though you're not very good just by luck whereas if you look at the inputs just give more chances if they're structured ideation and execution eventually you're going to get right so just got more chances and that made me actually take more risk instead of scaling down on the risk.

1:24:29But I felt very, very, very burned for a long time. There are jokes internally about moments. What a powerful story and mindset for us all to adopt. Such a great closing story, Gustav. Thanks so much for your time. Thanks for having me. If you enjoyed this episode, visit joincolossus.com where you'll find every episode of this podcast complete with hand edited transcripts. You can also subscribe to Colossus Review, our quarterly print, digital, and private audio publication featuring in-depth profiles of the founders, investors, and companies that we admire most. Learn more at joincolossus.com slash subscribe.