Lessons from scaling Spotify: The science of product, taking risky bets, and how AI is already impacting the future of music | Gustav Söderström (Co-President, CPO, and CTO at Spotify)

25:59But I think I think we haven't seen the second part yet. What is a model where this could be a benefit? What actually happened after piracy is that the music industry got bigger than ever, not just as big, but bigger than ever. And I think that could happen with this technology as well. But we're right in the beginning. So along the same lines, something else you teach is this idea of all truly great products have to pull some kind of magic trick. This comes up in your podcast a lot. And I think you mentioned this other places. And thinking about all the stuff you're talking about here feels like in a sense, everything's going to feel like magic because AI is kind of big into it.

26:38I think when we did the the DJ, we did a small version of that when people first listened to it, we could see that reaction in use of testing. When they wondered like, so the magic trick there was that how could they record this person saying so many different things because it's talking about my music. So the magic trick was obviously didn't record a person saying it's generated. And then that magic trick wears off. You hear it all the time now and so forth, but it was one of those magic tricks. So I still think that concept is important. It seems to correlate with products sort of going viral and taking off.

27:15And I think it was the same using something like a Dalai or stable diffusion of mid -journey the first time. It completely seemed like a magic trick. And obviously there is no magic. It's just data and statistics. But I think getting to that point and iterating a product to the point where it feels like magic the first time is very helpful. And it's often a question of just getting the performance to certain levels, scoping down, removing things. There's a lot of fine tuning I think that makes you cross that line from his cool and impressive, but not magic. It feels like magic. I don't understand how this could be done.

28:00Yeah, it reminds me of the launcher GPT, which ended up being the biggest, most fastest -going product in history. And it's like the epitome of a magic trick. It feels like acro magic. Absolutely. Absolutely. And to most people, it is still very mad actually to a lot of us and to even the researchers. It's a little bit magical. No one really understands fully. So I guess there's maybe some magic left in the world. Absolutely. And I think a lot of people are worried about not understanding what's going on there. Shifting to the way you all build product that Spotify. So Spotify is kind of famous for popularizing this idea of squads and tribes.

28:35And correct me from wrong, but you guys have kind of moved away from that approach. Yeah, that's right. Okay. So I love to understand just like why you shifted and what you kind of learned from that approach to building product. And then just like how do you organize the teams now? What do you do now? This was something that we focused a lot on early. And it turned out to be smart of us to name these things into squads and chapters and so forth. It wasn't really, well, maybe it was sort of deliberately branding. But it wasn't for purposes of branding that we made it up. We made it up because we thought it was a good structure to use.

29:11And we needed names for things. And this was the early internet era. So you were allowed to like make things up. And so it was very good for where we were at the time. And it certainly helped us in recruiting. It's become a little bit of a cost to us because people still think that we organized that way. And it's not a very efficient way of being organized at this scale or maybe even if you started over right now. And it's not a big topic, so you've learned more. But I think the big difference is, is the idea with the squads specifically was twofold. They were supposed to be small and sort of full stacks with squads.

29:46About seven people and it should have, you know, front and back and mobile, QA, agile coaches and so forth. And it should be a very autonomous was the idea. And that's really what we shifted. So first of all, as you grow the company, scaling in increments of seven engineers, just creates a ton of overhead. So obviously our teams now tend to be much bigger. Maybe maybe two, three times that at least. Per like manager to maybe have like 14 or something instead of seven. And just less, less overhead rolls. And so that's one. It looks more traditional as you learn more. And it's reasonable as you scale.

30:25The second big thing I think we struggle with was back then when I joined the average age at Spotify was. I mean, I was the oldest and this, this was 14 years ago. So I think the average age was probably under 30 or something. And it was in most tech companies. And so we had coming from Sweden, which is a, it's a different culture than, than the US. And I love a lot of things about Swedish culture. I think we might as to keep the best parts. But Sweden is a very sort of bottoms up autonomous culture. There's this famous drawing on how you make decisions in Sweden and in the US. I think it's just a hierarchy and Sweden.

31:09It's kind of a circle. It's a new circle. No one is in the middle. There is no leader and so forth. Interesting. So I think by sort of culture, we're very inspired by this super autonomous thing. And I think the idea with autonomy is, is very reasonable and the right one, which is we, we were and we are hiring the smartest people we can find. And we pay high salaries for that. So if you're hiring smart people, one way to think about it is you're renting your renting brain power. So if you're renting all of this expensive brain power and then you give them no room to think for themselves, that doesn't sound smart.

31:45Then you should actually hire less smart people and like keep your costs down or something. So I think you have to give a bunch of autonomy to actually maximize the value of the investment you're making. So that's very reasonable. You would give a lot of space for people to use as much of their talent and capacity as possible. But the problem with that is if you put autonomy very far towards the leaves of the organization. And then also if you combine that with having a very junior organization, which we did back then, there's a fair chance that you just going to produce heat. You're going to have 100 squads with 100 strategies running in a hundred directions.

32:25And you know, Spotify has been there in that camp. I mean, we managed to get somewhere for sure in spite of this. But I just struggle to say we were like efficient in doing that. So we've done a few things. The team structure is more traditional, larger teams less overhead. And we've been specifically working with where in the org do we put the autonomy? Because the extremes are at the leaves and we were there. The other extreme may be at the top. Let's say maybe something like Twitter. There's one person. Both have problems. If you have it at the leaves, you're going to produce a lot of heat.

33:02If you have it at the top, you need someone with a lot of capacity. And Elon has a lot of capacity. But you are by definition going to bottleneck. All decisions have to go through there. And Daniel just, it's not his personality that he even wants to make all the decisions. He wants to maximize throughput rather than to bottleneck the throughput. So the question is, if it's not at the top and not at the very bottom, where do you put it? And what we've found, which I don't think is very contrary and at all, I think this is the case in most companies, is around sort of the VP level. So if you have Daniel, then you have to see level myself and others, then you have sort of the VP level.

33:42That is a good mix of, instead of having one person in the company think, so only Daniel and the rest just do, you have on the VP level in a company like this. Many tens to maybe hundreds of people that have a lot of autonomy to think. So you get a good amount of freedom of thought and people think in different directions. But it's not like 8 ,000 people. Right? And these people on the VP level are both quite a lot of them, but they're also usually quite senior. They have a lot of pattern recognition. So I think that solves for, it's like a good, if you think of it as a, has an optimization problem, it's kind of a good optimization space.

34:25So the autonomy level in Spotify now tends to be quite high at the VP level, and then lower around those levels. And when you say autonomy, what does that actually mean? Is it the VP of say the podcasting product has a lot of saver? What happens? And there's not a ton of, I don't know, like how involved are people above? And I know Maya is the VP of product, I believe, for the podcast product. I think is going to come on the podcast someday. What does that mean in terms of Tommy for her, what practically? So it means that I would ask Maya to define a strategy for what we do in podcasting. How are we going to be different?

35:05Why would a podcast I want to be here? Whereas another company, I will make that strategy, or another company, Daniel, would make that strategy. Same with the AI DJ, for example, came from one of my, from my personalization team. And so that was a bet that they made. So they have autonomy to make those kinds of bets and define strategies. Same with the user interface, we have an experience team, can talk about the org structure later. But I put a lot of autonomy on the VP of experience to define and suggest what it is that we want to do. And in other companies, I would define all of that myself for example.

35:44Just go even a little bit further here. I know you have just like strong opinions on the way to organize teams and how the organization kind of helps you optimize for specific things. What are your kind of just thoughts along those lines and what do you have you learned about how the impact of organization and what you're optimizing for? Yes, so I talk about sort of an idealized spectrum or maybe not idealized, but exaggerated spectrum. It's not really, nothing is really true, but you create extremes to make a point right. So on one spectrum, you have something like Amazon, which is known for two pizza teams.

36:26No dependencies, you try to minimize the penance, so you can run in parallel. Teams compete with each other, even on the same project and so forth. But they have direct access to the user. And so the benefit here is if you have an idea, the time to get to user is very low. And it has worked for them. It's produced, you know, it's produced a kindle, it produced a Lexus, it's produced a lot of very novel things. There are a few interesting downsides here. One downside that I'm extremely impressed with Jeff Bezos for seeing is if you have teams that compete with each other, the incentives are to hide your results, hide your code.

37:08And that should make for an organization that gets no platform leverage, because no one is cooperating. And I think this either he had that insight or because he saw this, he had to do this, but he's well known for pushing extremely hard on hard APIs. Like if you don't create hard APIs to your technology, you're out. And if you think about it, it has to be that way, because otherwise no one would do it. And a hard API is essentially up. Like everyone knows how to use the API and connect to this team to interface. Exactly. You have to expose your technology to others, you have to maintain those APIs and they have to be very structured, because otherwise the whole thing would collapse as everyone's supposed to compete because they're no incentives.

37:47You have to centrally force that. And interestingly, even though theoretically then they're the worst position to have a structure platform. I think because they forced it so hard, they were the ones who did Amazon Web Services, because they had such hard defined APIs because of this rule that it was easier for them to turn it into a new system. So you can go inside out and expose it to the rest of the world. Whereas if you look at something like Google, I think they struggled more with externalizing their APIs. Maybe because it is so friendly and soft, so they didn't need as hard APIs on the inside.

38:15Because there was no competition, people could just go into each other's code. So it's interesting anecdote around it, but the main point is you're faster there, but it's going to be hard to cooperate. And so you will see something like maybe exaggerating a bit. Sometimes you'll see multiple search boxes on the same page from different teams. And this has been through in Spotify, by the way, as well. You've seen like multiple toasters on the now playing view coming up from different teams because they're working when we were in the autonomous mode, everyone running. And then so you get the benefit of speed, but you get the drawback of kind of shipping your org chart and shipping complexity to the end user.

38:57But clearly that's been the right choice for Amazon because they're a trillion dollar company. But then on the other spectrum, you have something like Apple, who's also a trillion dollar company. So clearly both models work where you would never see two search boxes from the same team popping up on an iPhone. That shit is centrally organized, but you know, something that is close to single individual. So they they are instead in what probably was biggest largest functional word. They're doing as much if you think about what goes into that bullets mean they certainly do everything we do. They have a music service, podcast service, hoody books, and they have a billion other services.

39:37So it's not like they have an easier problem. And yet they built something that feels more like was built by a single developer for single user. So they centralized and they have this bottlenecking function that everything has to go through and be decided how it fits with everything else. And so that has the benefit of the user experience being simpler and not shipping the org chart and increasing complexity. But it also has to draw back all of speed without having facts on it. I've heard people working at Apple said like yeah, seven years to get that thing to market because you just had to wait in the pipeline.

40:16So you have these extremes and I think the most interesting example I think to think about is. When you double click the power button, I found the Apple pay comes up with that decision. How did that happen? You can imagine that all the services team would like to pop up when you double click that button. And so someone had to decide should should music come up should have payments come up should something else come up. And so they have a different structure there and on that spectrum of centralized versus decentralized. Because of our strategy, which is where single application. Trying to add or not trying to we have added multiple types of content with actually very different business models on the back end.

41:02You know rev shares and roll out this and book deals and so forth into single user experience that is our strategy we think the user experience and keeping that simple is the most important thing. So we've chosen more of the central centralized model. Where these different sort of vertical businesses if you think about it the music business podcast already books business. They have to go through a single recommendation organization. That's another problem. You know which one do you recommend to which user should be a book or podcast or music and how do you weigh them against each other. And also the user interface could easily get incredibly complicated if everyone built their own UI.

41:38The music team built their UI and then someone added features on top. So that's how we chose to optimize. But it is based on our strategy and I think both models work. This episode is brought to you by ECO. Last month ECO users earn an average of $84 in cashback rewards. How with ECO the future of personal finance. ECO is the update to a misaligned financial system providing an app that works just like your bank but removes almost all of the middleman. Helping even the best money optimizers optimize in less time automatically. What if you earn rewards for paying your rent. Or got rewarded for ordering food and shopping online.

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42:58Learn more at eco .com slashlennie. That's ECO .com slashlennie. It's interesting these two examples you gave Apple and Amazon their two of the biggest companies in the world. And they're like at the extremes of these two. Yeah. Into the spectrum. And it's interesting most companies are somewhere in the middle. I wonder if there's just like a benefit to being at an extreme and that ends up being really important. I think so. And in almost all industries you have this smiling curve concept right. Or you want to be at the extremes of the smiling curve. And that's what big business opportunities are but not in the middle.

43:30So it's probably true terms of organizational moments as well. Speaking of extremes, I want to talk a bit about taking big bets. So you guys had this big launch event recently where you basically redesigned the whole primary feed of Spotify to make it feel more like we're kind of apps are going. It's like TikTok reels feel of just you know, a stream and you start hearing videos and music starts playing. And some people loved it. Some people did not. And I'm curious as a product leader, how you think about thinking long term and dealing with people that are just like what the hell's chain. I hate change stop changing things.

44:04How do you think about that? Who do you listen to? Who do you ignore? How do you know to stay the course? How do you approach that? Yeah. You're being very kind though. There was a lot of negative feedback on Twitter on on some of that. So let me actually kind of dig into some detail because I think this is really for product. People listening to this. This is an interesting lesson that I think few people. Few companies talk about because you don't really want to talk about. You want to talk about everything that went exactly as you thought they would. And you don't want to talk about the things that didn't go exactly as you thought they would.

44:39So I'll go through kind of what we are trying to achieve and what we learned. So Spotify is mainly a background application. And for a long time we've been considered very good at background music and podcast recommendation when the phone is in your pocket and you're listening to like an EDM playlist or you know pop playlist or something. We're really good at inserting another EDM track there or another pop track there or something like that in the background. What we hear from users again and again though is that. You know they say that they get trapped in a taste bubble. So you know I love my Spotify.

45:18I love this. But I am a little bit bored with EDM now and Spotify is not suggesting something completely new. And if you think about that problem. It may sound similar to the recommendation. It's just another recommendation problem. But it's actually fundamentally different. Because when you're recommending another EDM track inside the EDM playlist. You have a lot of signal from that user that they like EDM. But if you're going to recommend a completely new genre by definition. You have no idea. Because if you had an idea it wasn't new to them. So you can't know anything. So back to hit rate your hit rate is going to be incredibly low when you suggest something completely new to the user.

46:03So this problem of helping people get out of the taste bubble is not easy as it sounds. And we can't really take some you know some genre that maybe isn't typical. So I'm a big fan of reggaeton for example. It's not typically. It's not that common in Sweden. And if you would look the rest of my profiles kind of EDM have this you probably wouldn't have guessed it. And it's part of I wouldn't have guessed it. So if I'm listening to my favorite EDM playlist in the background. Or maybe my metal playlist metal is very big in Sweden. It's really hard for us to just insert a reggaeton track in the middle of that.

46:37You know most people are going to think Spotify's broken. What the hell are they thinking right? So that doesn't really work. So in order to help people break out of their taste bubbles you need something different. You need something where your hit ratio can be very low. And you need people to expect it to be very low. So when we recommend things in the background or hit ratio needs to be at least nine out of ten. Maybe one dot is okay. But if you get five dots you're going to think we broke your playlist in your session. We need something where one out of ten is a success. If you find one jam out of ten tries you're very happy.

47:20So you need a completely different paradigm. And you also need to be able to go through many candidates quickly. Because the hit rate is so low. You can't take three minutes per item. It's like okay I didn't like this. And it's still like two minutes left before the next one comes on. You need to quickly say no no no. So the always candidates for this are these feed type experience. We can go through lots of content. You're expecting the hit ratio to be much lower. And if you don't like it the cost is very low. You just swipe. And then this is the reason why people have been when they want to break out of their of their taste bubbles.

47:57Or when they come into Spotify and listen to something completely new. It is usually because they found it on one of these services like a tiktok or YouTube or something. Where they get exposed to lots of new content. So people were asking us for these tools. And so that's what we wanted to solve for. And so we built a bunch of features feed like structures where you can go through either a new genre with many tracks. Or a podcast genre with which on with many episodes or even full playlists. And we implemented those and we put them in something called sub feeds. So in the current experience and this is rollout worldwide.

48:36If you click the podcast sub feed you get a feed of podcast episodes. Click the music sub feeds you get a feed of of playlists. Where you can quickly you know you can go through many playlists. And if you don't understand the name you can quickly hear what they sound like and check out a few tracks and understand if this is for you. And if you go to the search and browse page page you can find completely new genres that you can quickly go through. And so those are working as we intended people go through them go to them when they want to find new music. They browse through them and they save new songs.

49:08So they're working as we intended. The thing that didn't work as we intended was when users asked us for this again and again. We took sort of some of these things and we put it on home because people ask so much about discovery and we can see clearly how how correlate to discover is with retention on Spotify and so forth. But what we what we missed judged or failed to to or rather learned about our own home page is that the way it works right now. And this is what you can see in the Twitter comments if you if you remove the angry voices and sort of try to see what they're saying. They're saying the following which is actually quite clear in the quanta did date as well.

49:51That if you look at what people do on Spotify's home page account one. It is almost 90 % what we call recall. So it is either getting to a session that you're already in. Or a specific playlist that you know you want to get to or at least a specific use case you come in with a high intent. They actually knew what you wanted. And maybe only 10 % of the time as a true discovery like I don't know what I want. So if you think about that is 90 % recall and 10 % discovery. When we tested the design so the sub feeds were working and all working but we tested the some of them on home. We kind of switched it from 90 10 to 10 90.

50:30So 10 % recall 90 % discovery. And while people want discovery they don't they probably don't want 90 % discovery. Instead of 90 % recall. So if you then look at the comments on Twitter what they're saying is like hey I can't find my playlist anymore. Like where are these things? They're not really complaining about the discovery. They're complaining about the things they don't get anymore. And we can see this in the quanta as well. Then you can see traffic shifting from home into search and into library which is a clear sign people are trying to find. Find the things they can't find anymore. And you can even see people then trying to use these discovery tools which are optimized for understand quickly understanding new things.

51:09To do the recall like where is that work up playlist I know I want. And it's actually very bad UI for recall. It's kind of like a slot machine. Very unpredictable if you ever get to that work up playlist. It was optimized for finding new things not for recall of existing things. When you do recall you want to dance UI with many items on screen because you know what it is you're looking for. You don't need a lot of real estate. When you do discover new things you want a lot you want a lot of user interface a lot of pixels. And you probably won't sound because you don't know what it is. So what kind of what we learn about our UI and I think there's maybe maybe a little bit of you know product jealousy here.

51:47You always look at other experiences. And if you look around it could be forgiven for thinking that most other products if you look at something like YouTube for example. Their homepage is exactly that it's a huge single item discovery feed with only new items. And people don't seem to tweet angrily about how angry they are due to say they love you to be in it's a big product. And I think what we discovered was that we actually did something really well on our homepage which was supporting you being inside a multiple sessions at the same time. So you could be in the middle of two podcasts and an audio book and also them actually I just want to get to that work out playlist.

52:29I don't remember the name of it but I know it's workout. We actually did that part really well. I would venture to say much better than the other experiences where you literally have to go to your to some tab and into library and start browsing to get back to where you were. And so maybe it's path dependent if we had you know because we have done recall pretty well. People got I think reasonably upset when they couldn't find their when they couldn't do the recall anymore. And we really don't want we didn't want to lose that because it was one of the things we did well and underestimated and my takeaway is actually we do it better than other experiences.

53:06And so we certainly want to keep that. So what we did was now we're just updating the hypothesis to achieve the same goal which is these things are working and when people want to discover the use them and they seem to work they can they can also get better you know you're on this like. Hill climbing journey from machine learning point of view. But the question is how do you make sure that whenever people feel that they are in that I'm trapped in my taste bubble. They understand that these things are there and they're easy to use. So now we have a version of of home that that we're also testing obviously where these things are very available but voluntary and you can still do all of the recall.

53:47And so from my point of view this is the reason we A B test because you know you want to be scientific about it and you know you want to learn as much as possible about your own product and your users. And now I'm sharing a lot of the learnings maybe you should keep them to ourselves but my hunch is that it's going to make it a much better product. But what I told my teams when we went into this because I've done this a few times I agree with signing I think there is a. There are two fundamentally different types of product development one is designing a new feature. It is hard to make it but it's.

54:26But it's voluntary for people to use so you do the a DJ some people love it as far if you don't like it it didn't make it worse for you. But when you redesign it is much more tricky because it's not voluntary to participate in the redesign so there's there's a cost even you know work for people who don't like it. You have a very tricky problem here which is. They're going to be two types of feedback one is. You did something and it was right. But people are upset because you changed stuff. The other is you did something and it wasn't right and people are also upset. But for good reasons and so how do you separate these two because I think I explained this to when we talk through this with my my teams I think the analogy to think about is you have your desk top your physical desktop you have a computer in one place you have a pencil over here.

55:23You have your notebook over there and I come in and I just rearrange all of it. And you have spent in our case maybe 12 years with that setup it doesn't matter if I have a lot of of quantitative data that my new setup is better you're going to get upset because you are effective in this old setup. And it's hard to tell those apart the most classic use cases the Facebook newsfeed which people are very upset about when it became a single newsfeed but it turned out to solve a lot of use of problems that you didn't have to run around all the Facebook collecting events yourself. So there are some ways of of understanding if if you made it better but people's habits are broken or if it's not better and one thing is for example to look at new user cohorts that don't have that behavior versus all use the cohorts and so forth.

56:12So we went through all of this with the teams before we did it I said this is going to be painful probably going to be a lot of tweets because chances that we get exactly right are very low. So for that reason it hasn't been you know very hard on the team. It is hard you know you want to respond to people but the right way to do it is to listen understand try new hypothesis to really figure out what's going on. So I think I've done it maybe three or four times now one three maybe one unsuccessful to successfully kind of knew what I was getting into. So it's almost like you punish yourself very painful but also the most exciting things and I think any product person knows that the the easiest and most straightforward thing to do is to iterate around where you are.

57:00There's no risk you're not going to get fired your user is going to get angry but everyone also knows that eventually if you don't adopt new technologies new paradigms etc you're going to get replaced you have to find this balance of try new things. And that's you know when you work in software you have this tool of a b testing and being scientific about it when you when you build hardware it's worse if you're if you're wrong you're wrong you can't update. I love this story so appreciate you sharing it. I imagine also with a big launch like this you can't actually a b test it ahead of time because the press season they're like oh my god look what spotifies doing and so you're kind of limited there imagine right you couldn't really test this ahead of time.

57:40The hardest thing about this is if you're trying something complete than you. The MVP needs to be very big so you can build a new UI but if you didn't do algorithms for single item feed you can't tell if it was the right idea but but poor machine learning right you are poor machine learning or the other you have to build a lot I guess quite expensive that's actually. The biggest why it's painful is not really the feedback from the outside it is the cost you have to take on the inside you know you incur a lot of cost as you're really hoping you're right and in our cases the the changes on the homepage aren't that hard for us to do the important thing is that the underlying hypothesis of can we help you break out of your taste bubble actually works and then you know you update the the acquisition funnel into that experience.

58:32But I think the problem is that you need to get so many things in place to be able to say if you get you know you might get a false negative just because like you didn't do it well enough that's the biggest chance I think with these big rewrites where everyone has to update everything before you can know if you're right or wrong. What was the process like of helping understand what is not working and what is working and what you wanted to change like imagine there's like a bunch of data you're looking at some tweets things like that like what was kind of like the tactical. Oh shoot something's not going the way we expected here is what we should do well that feeds we tested but the home feed.

59:12We roll out and test it afterwards and we tested it on users few different variants of it and then we got the data back. And we looked more at the quantitative data and we do a lot of user research where people said in use the feeds to understand and and build like our own. The remind of what is working and what is not working and then obviously you you look at you look at. User feedback of course and some users are very good at expressing what is that that isn't working others are not as good as expressing what isn't working so it can be hard to parse that. But certainly that's a factor as well.

59:51And so then what once you do that then you have quantitative data to look at and then you sit in recent through. What do you think is right and wrong what a different hypothesis what is working was not working and then just update and test again and again until you find. Until you prove or sort of this prove your hypothesis trying to be a scientific as possible about it and also I think the biggest risk. Also when you've invested so much time in something is you you know getting precious about things you have to just be brutal. You have to believe in things 100 % until the data says no and then you believe in something else 100 % that that sounds easy it's very hard to do it to the extent that people get upset when you do it because for some reason.

1:00:38And people don't like when people change their mind it is what we should one from everyone I would love a politician who said I looked at the data and I realized actually this is right and I believe this but we hate politicians to do that. You know they feel untrustworthy and like we ridicule them so I think that's the biggest risk with anyone you just have to be like unemotional and just just look at the proof in the data. And then you know if you do that just move on and then you get to where you want to be and you solve the same problem but you adapt. I really like that philosophy essentially it's the idea of strong opinions loosely held right is that exactly exactly what it is and it sounds so easy but it's hard.

1:01:23Right because to your point people don't like don't respect someone changing their mind like oh I see they were wrong the whole time and they're so confident about being wrong. Yeah exactly and it's unclear why this what we should want but I think it's I think it has something to do with human human psychology. We actually tend to love profits and people who hold very strong opinions with very little data those are the people will make people look at a lot of data and actually that we don't like. Not sure why. We're flawed lot creatures for sure is there something that you've recently changed your mind about along these same lines that maybe comes to mind and like oh yeah.

1:02:06Now I think these learnings about the what our home. The scientists man homepage does really well. Maybe better than others that we don't sort of want to wash out with the bathwater or whatever the everything expression is. I think that's the biggest current learning I'm actually very happy about. Yeah I love learning that we're doing some really well that we didn't really realize necessarily and maybe we should lead into that more. Exactly. Going in a somewhat different direction Shashir Morotra suggested asking something he's on your board I believe and she suggested ask you about your 10 % planning time what is what is that about.

1:02:45This is a concept that thinks Shashir has used for a long time ever since he worked at YouTube. And the idea is that roughly you shouldn't be spending more than 10 % of your time planning versus executing or building. Which means that if you're working quarterly sort of 10 weeks you just spend one week planning. This week we work in in sort of six month increment. So we try to spend two weeks planning and roughly successful and this is actually when we talk about org models give a shout out to to Brian Chesky at Airbnb. Who is who is actually one of the first I think to have these more contrarian org models.

1:03:27He's much more Apple less than most of Silicon Valley. He also works in six month increments. So he has a lot of experience in that as well. So that's what the 10 % planning time is. And I think if you find yourself planning much more than that you're either planning too much or your execution period is just too short. For that amount of planning it's a rule of thumb but I find that it works. I asked a few pms what I should ask you pms the work that Spotify actually that I've been told to you and so and pointed out the you you always bring a lot of energy and clarity to a room. That's something they see you as really strong at.

1:04:05What have you learned about just the importance of that or just how to do that well as a as a leader. Well, that's great to hear. I didn't know that so I'm trying to figure out what's the answer. I think that the energy I don't know I guess I'm just excited about what I do. I've always been excited about technology. I love seeing new things at my core drive is still this notion of you know you see something which I think you're you're all empathized with but doesn't exist yet. And you're like wow I wonder if that could exist that would be so cool. And then in order to get people to do it you try to share that excitement.

1:04:47So I don't think I can be bring a lot of energy for something I'm not excited about. So I kind of have to work on things actually believe in and that I'm excited about. So maybe then the energy comes more naturally. Fortunately for me so far Spotify has been in this phase where a lot of innovation is allowed and I'm even asked to try to do new cool things. Maybe I would have less energy for pure optimization phase. On the clarity I've always liked trying to explain things. It's a well known fact that the best way to understand something is to try to explain to someone else. So I go around explaining things to people who didn't ask for it and not just on smart but to see if I actually understood it.

1:05:31And so maybe it's that practice and on that note I actually do ask my leaders that work for me and I ask them to ask their leaders to always explain themselves. And I think when we talked a little bit about autonomy and so forth I don't think we don't promise everyone that they have to agree. But I think the promise we should make to all employees is that even if they don't agree they should be entitled to understand why you're making the decision. What I don't think is acceptable is to say no we're going to do this way because I'm a more senior. I've seen this a bunch of times you're not smart enough like all of those things.

1:06:18I think you have to explain yourself so you own explanation and I find that valuable back to like the only way to understand something is to explain it because it usually turns out that if you can't explain it to yourself you probably don't really even understand it. Sometimes I think it's possible that you can have product instincts that are good but you can't express them. But most often when people say there's something there but they can't explain it they actually don't understand themselves and many times there actually isn't anything there. And also if you can explain it as a product person that knowledge is now shared so it just becomes much more effective for the organization.

1:07:04Sometimes I try to provoke people a little bit and say you know then people ask like how much is art versus science. I say it's 0 % art, 0 % magic and 100 % science. And that's because I want to force people to try to explain it. I think we use the word art and magic. We have historically used the word art and magic for anything that we couldn't yet explain. You know genetics was with magic and art until it was science. And you know quantum physics with magic until the science and most recently actually intelligence and creativity was art and magic until it was statistics in an LLM. So I think I try to push people to say are you sure you can't explain this because that forces people to think through.

1:07:58So that's maybe I like it and I try to force it on people so maybe that's why people think I sometimes bring clarity. I love that question along those lines. Is there a system or an approach to explaining the recommend is it just like write it out in a document? Is it explain in a certain style or is it just like however is natural to the person? I used to write everything and then write and rewrite and make it more and more condensed. So that worked for me. I don't write as much anymore. Now I tend to like walk and talk in my head myself. What I actually do is I am and I found it different for different people and a lot of people want to bounce something with someone else.

1:08:43That's how they think. You kind of repeat the same thing again and again and you get some feedback on it. And so I used to write a lot. I sometimes do when it's an idea I want to understand better. And at some point in my life I would love to write something real like a book or something. But what I do increasingly now is I do my one -on -ones with peers or people who report to me or something. And I just put on airpods and do like a distributed walk and talk. Both people are walking but in different locations. I use spend an hour discussing something. That has actually turned out to be very, very fruitful.

1:09:21So then you get the power of you're not alone. So you get more brain power than your own. And I think, you know, I don't think there is strong evolutionary proof for this. But there's certainly indications that you're thinking better when you're walking. Whether it's because you're oxygenating your brain or because it's evolutionary for some other reason. I'm not sure. But I found that walking, talking and thinking. Actually, even if you're not in person just over airpods, it's super effective. It was the pandemic that kind of forced us. I thought we would get less creative and that strategizing was suffered during the pandemic.

1:10:01And I found the opposite. We had more of this in the end and I started thinking about why. And I think it's all of these walking talks that we did. You kind of throw out there that you want to write a book someday. What do you think your book would be about? I have no idea. No idea. Statistically, it's probably going to be about something that it did a lot. So it has to be about something with technology or product or something. But I would love to write something fictional. That would be a lot of fun. Oh, boy. I'll preorder soon as that's up. Another concept I wanted to touch on that another PM suggested, which is he called it the P in the pants analogy.

1:10:37Does that ring a bell? And is that interesting to talk about? I don't know exactly which occasion this person is referring to, but I know I've used that analogy a few times. Okay. Promising. I don't know if it's like a Swedish analogy because I thought it was more widely known. But the idea is that you do something. So the saying is that's like being in your pants in cold weather. It feels really warm and nice to begin with. And then after a while, you start to regret it. It's about being short term, basically. So now I just say that I just say that's like being in the pants inside because people know what I mean.

1:11:19It's short term thing. That's a hilarious way of communicating that idea must be a Swedish thing. Yes, I think Swedish people do it for some reason. Apparently others don't. Maybe because it's cold a lot of time here. Yes, that's probably it. This is a saying in cold climate in the warm. It doesn't it doesn't know. No one understands what you mean. Speaking of Sweden, do you have succession? Yes, I do. Okay, so Sweden is become a big part of the show, specifically the company China. I guess I don't want to spoil, but there's a character that's really important. Yes, exactly. That is Swedish. And so here is just what do you think of the way they portray the Swedish culture and Swedish business dealing?

1:11:59It's super fun to see this as a Sweden. And I guess for first and foremost, like anyone or any person or any country that gets represented by a super tall, well, they'll great looking Alex on the score. It should probably be pretty happy. So that's good. Then I think this is episode where they are in Norway, not giving away too much. Yeah, it's it's there are elements that are authentic. There's a lot of of I think paid brand positioning from a Swedish brand named L11, something means Arctic or Arctic Fox, which is actually very popular outdoor brand in Sweden. So that's kind of that's kind of authentic.

1:12:44The the son of things and so forth are authentic. So it's like it's real, but it's it's exaggerated. Actually, the thing that isn't very authentic is his negotiation style. As Swedish people tend to be serious, cautious, and this guy's more of a player. So it's he's not the typical Swedish businessman from a negotiation tactic. Point of view, I think. Yeah, it doesn't make me think of the way you described it. We're in Sweden. People sit in a circle and no one's in the center. No, exactly. He's very much in the center. And then when people go son is there just like a chance on a son. Exactly. The last episode is a great show.

1:13:26I love it. I love it. The season is insane. I am so curious where it all goes. Maybe just the last question before very exciting lightning round. Spotify is at this point the biggest podcasting platform for me specifically. And I think globally and I love using it. It works great. I'm curious just what's next for Spotify and specifically Spotify podcasting. There are two sides to it. It's for Spotify creators and for Spotify listeners. For Spotify creators. There are two things. One is and this is what we talked about at stream on. We talked about it also from music, music discovery. But the same problem.

1:14:04It's the same problem and even harder for podcasts. So we're still focused very heavily on helping spot on helping podcast creators find more audience. And this is like I said, it's even a bigger problem to break out of your habits and your bubbles and podcasting. Such a big investment to find a new podcast. So that is something I think we could and should do really well. So we keep investing a lot there. And as I said, you'll see more as we roll up more features now. The other big need for for creators is monetization. And you know, you can monetize today in many ways with the DAI and so Spotify, SDI and so forth.

1:14:49But we work in hard to expand that and make it better because the industry is starting to mature. And I think this is one of the biggest needs and the biggest things we could do for creators to help them monetize better. Actually, both free and paid. We also paid podcasts. So that's on the creator side. On the consumer side, I don't want to share too much. We've shown that we're investing a lot in discovery. I want to keep some secrets for when they roll out. But we are investing a lot in the user experience itself. I think it's far from optimally yet. What it could be. One thing that I can share that we're investing a lot in is just the ubiquity and playback across different devices and in cars and all these things that we've done well for from usage.

1:15:37But I think the listening experience can get a lot more seamless. I think search can get better. The data about podcasts and I don't want to say too much. But looking at AI and general technology, there's a lot that can be done. All right. I'll take what I can get. With that, we've reached our very exciting lightning round. I've got six questions for you, Gustav. Are you ready? I think I am. Let's do it. Let's find out. What are two or three books that you've recommended most to other people? This is why I try to squeeze in seven into two and three. If we start with the own product, I think it's well known, but one that I would recommend probably people to read is seven powers by Hamilton Humber, which Netflix has used a lot.

1:16:23If you're starting out, it's great to have a strategy framework. No strategy framework is right, but having one is better than not. Another, instead of the space of mental models and frameworks, I think is the complete investor by Charlie Munger. Yes, it's about investment, but really it's a bunch of mental models that he uses. I think the key takeaway is you have a problem. You should always apply three different models to it because what models do is they simplify and reduce dimensionality. The world has infinite dimensions and reduces to maybe three or four. The risk with that is you happen to get rid of a really important dimension, like maybe pandemic decisions or something.

1:17:08But if you use three models that have different dimensions and was reduced in different ways, statistically, and it comes the same conclusion, even the second model you apply vastly increases your chances that you're right. That was a good book to read. Then I think if we go outside of product, I'm very interested in just science and mathematics. A few quick ones. The mystery of the A -Leaf, an amazing book. Something deeply hidden by Sean Carroll on the Everettian interpretation of quantum mechanics. Helgo Land by Colin Rovella on the relational interpretation of quantum mechanics. The beginning of infinity and the fabric of reality by David Deutsch.

1:17:54The case against reality by Donald Hoffman on evolution versus truth and that evolution does not optimize for seeing the truth just for fitness. Gerdel's proof, I think is an amazing book on his incompleteness, the R .M. That in any axiomatic systems, there will be true statements that can never be proven. Which is a weird thing to think about. And then maybe one of my favorites is the demon in the machine by Paul Davis. That I think is lesser known on how information is really just entropy and this concept of information engines. That you can power something by just information and exhaust this also information.

1:18:36That was not a quick list. No, but I was just going to say you've set the record for the most number of books, but it also shows how you've become so insightful and wise is just reading books like these. And so I think if people are looking to get to a place that you're at now, I think there's the lesson. I'll keep the others much shorter. I promise. That's all good. We got time. Okay, next question. What's a favorite recent movie or TV show? So we talked about succession and it is a reason favorite. So I'll just previously take something that isn't reason, but isn't absolute favorite. Which is holding catch fire.

1:19:13Which I think is on effects. Amazing show. If you ever worked in technology, it kind of starts out in the Silicon prairie in the 80s and follows up to present day. Amazing show. Holding catch fire. I watched some of it actually fell off of it, but I'm going to get a reminder to go check it out. I'm going to go back. What's a favorite recent interview question you like to ask? I don't ask it, but my favorite question is like, Friedman's small ending question that is usually something like, so what's the meaning of it all? I like that. It's a tough question to get. I'm so tempted to ask you, but no, don't.

1:19:49Okay. Let's move on. That'll be another part. That'll be our second second take at this. What is what are some favorite products you recently discovered that you love? The obvious one is as Chatchy Petit G4 and just playing around with that trying to create books for yourself that do different things for you and so forth. But I don't think that's That's probably true for everyone. The other really favorite is something you've written about and talked about, which is Duolingo, which I think is both very impressive from a product point of view, the execution and what they've done. It is also insanely used in my family.

1:20:26We have a family account and everyone is, you know, using it and competing every day. So I'm both impressed by the product and also used the product quite a lot. What languages are folks learning within your family? In my family, it's Spanish right now. How's it going? Bien. You get a goal start. I only have like a few thousand XP. I'm not that good yet. I don't know if that's good. That sounds pretty good. Next question. What's something relatively minor you've changed in your product development process? That's how to tremendous impact on your team's ability to execute. I'm not sure I've done anything minor that had a tremendous impact.

1:21:08Usually it takes something bigger to get big impact. I think maybe one thing that I've tried to do back to like cloud and so forth is this thing I mentioned about. I'm trying to push a lot for what is called theocratic debate where the idea is obviously that the best idea wins, not the most senior idea and so forth. And trying to push for this notion of having people explain themselves. Not saying like I think there's something there or I have a feeling or something like that. And apparently as you said, that has had some impact because people apparently say that about me so. That's probably the biggest thing.

1:21:52Final question. What is one fun ritual of the Spotify product team and is it son is? Spotify is big now that we don't... It's quite local actually. Different parts of Spotify, different product rituals. I accidentally created one ritual many years ago, maybe 12 years ago, when we talked about where a product, which face a product is in. We needed some definition. So I think sort of off the cuff, I said like, well, it's four faces. It's think it, build it, ship it, tweak it. And then the think it face, you should, it should be cheap. Not a lot of money spent in the build it face. You're going to start spending a lot of money.

1:22:36So then you must have reduced the risk in the think it face that you're right. Then you have the ship it face and then you go over and tweak it. And it was something that wasn't that thought through. But it's funny because I still hear it. Sometimes even from other companies say, oh, we're in the think it face or we're in the tweak it face. So it kind of stuck. I don't know, it's very good, but it stuck. It is catchy. I think that anything getting stuck in people's head is a success. Gustaf, thank you so much for being here. We are two for two for Swedish people. Gustaf with an F, Ulstermur, was on the podcast.

1:23:10Who is also an amazing person. Also an amazing person. I feel very jealous of people to get to work with you and for you. Thank you again for being here. Two final questions. Working folks finding online. If they want to learn more, maybe reach out, ask some questions. He says this at Gustav S. Okay. Say it again. At Gustav S. Awesome. And then final question is just how can listeners be useful to you? Just reach out. I do read feedback and I try to remove the angry comments and understand what they're actually thinking and why they're upset or what's not working. And then the reaching out with Jurek Amanda, an angry tweet at you or more of an email to that email address, you shared.

1:23:50Well, the at Gustav S is the Twitter handle. Just tweet at me. You can be nice as well. It's okay. Amazing. Gustaf, thank you so much for being here. Thank you for having me, Lenny. It's been a pleasure. Bye everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or a leaving review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at Lenny's Podcast dot com. See you in the next episode.