The Exchanges

Q So many questions about process. The first is how that three hour meeting on Tuesday works. Like what is the structure of that meeting?

A It's called the E-team execution team. So it's very focused on execution of the company. And the idea is that, you know, if you have five, uh, five day working weeks, there's never on average more than two and a half days before you, if you're, if you're blocked on something can escalate to me. Alex and all the other VPs. So the idea is you should never be blocked more than max two and a half days because we run this synchronized ship. If you're blocked, it gets very expensive because everyone else is downstream of you. So if you're running a synchronized operation, the way we're doing, Um, escalation processes are very important and resolution is very important. So a big part of that meeting is people say, you know, we're, we're off track here. I'm, um, dependent on this, um, man or woman over there who hasn't done what they said. And the, the beautiful thing about being able to have all the VPs in the same room is, you know, I met so many meetings that I'm sure you've been in. People say like, okay, we'll take that offline. I'll talk later. And what we said is you're not allowed to say the word offline or later. Because that person is in the room. Yeah. So it's like, you know, I'm dependent on maybe Anna over there for this, but then Anna is actually there. And then Anna can say, you know, okay, I didn't know that, or I'm going to solve that. So it's like real time resolution…

AI assessment note: “It's called the E-team execution team. So it's very focused on execution”

Q we could use these models to make better products, better features, whatever. Can you imagine like a 10 times better, you know, another couple orders of magnitude, better models opening up lots of features that you can't currently do? Like, is that a, is, is that a thing or, or do you think we kind of have what we need and therefore inference we could expect to be really cheap?

A 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 Product ship that look amazing for several years before we exhausted, uh, what we have. So I subscribe to that, but I also subscribe to that. There is no limit for, for compute. Eventually you get to computronium, but if you look at this, the physics of computronium, it's the smallest, it's the most computation a universe could do, you know, theoretically. Um, we're very far from that limit. Uh, So I think we're going to go all the way there before we stop. And I think we're going to be very inventive of it's, um, there is a nice analogy that I think, uh, 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, the idea was the same, you know, now all accountants are gonna sort of go out of business. What happened was we could just not imagine if, if computation, if, if calculation or, or basically, you know, yeah, if calculation, cost of calculation went to zero, what's gonna happen is you, you could imagine that the value of doing that is gonna go to zero because there were so many accountants in the world. So what happened was we just started doing massively more accounting. When, when there's no cost to spreadsheeting, you're gonna start, uh, You're going to start to models to …

AI assessment note: “So I both subscribe to the product overhang idea that there's a huge product overhang.”

Q What role has and will Spotify play in all this? And just like, what do you think about podcasting and, and, and its importance?

A So the, the reason we went into podcasting, one thing that I'm very precious about when it comes to Spotify. And, um, so is Daniel and, and, uh, the other co-person Alex is my closest partner is that, uh, there are many ways we could go, um, 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. Um, so 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 don't, we're not as steered towards engagement at any cost. So having been at Spotify, you know, 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, I pushed quite hard for podcasts in the company was that I was using it myself and a lot of our developers were using it. And I saw it being hacked into the product at Hack Week every year. It's like people wanted them there. And we just said like our developers is like a small sample of the world. What if they're, what if they're a good sample of the world? So, so that w…

AI assessment note: “the reason we went into podcasting... One of the reasons I really pushed”

Q going there expecting to write a lot of stuff, you're copy pasting prompts from Twitter or whatever. In an app like Spotify, how willing are people to get not lazy and really descriptive about what they actually want? What have you learned about like the nature of People's laziness versus willing to put a lot of work in to get the thing that they want via that more rich uplink.

A Yeah. So that's. That's probably the most exciting thing for us of this, uh, generative AI age and the, and the dual uplink paradigm. So previously we mostly relied on some explicit input when you playlist, that's like high value information. You are sitting there thinking like this song goes really well with this song and that song. So it's, if you think about it as labeling, even though you're playlisting for yourself, you're sort of labeling these tracks in terms, at least in relation to each other, and you're putting a lot of effort in it. And that, that was our Was and is our big advantage in music recommendations, even though generative recommendation systems are starting to take over from these more old school collaborative systems. So we had some really strong signal like that where you quite seldomly invested a lot of time in producing a data set that described you by play listing. But most of the time we just had skips and the challenge for us is the phone is in the pocket. So even if we had like a thumbs up down You're not going to take out the phone every time and say like, I didn't like this because of that, or even do a thumbs up, thumbs down requires you to take up your phone, unlock it, open Spotify. What you can do from your earphone is to skip. So we have the skip signal, but that is a very blunt signal. So we play your song and you skip it. That could be beca…

AI assessment note: “you quite seldomly invested a lot of time in producing a data set”

Q What's the key to a good bundle? And, and I'm also curious, you know, you said you experimented with exclusive Content that was only available on platform and less of that now, you know, what drives a decision like that? And how do you think about other people that might want to create a bundle somewhere else?

A When we looked at podcasts. You know, you, you look at something like Netflix and this beautiful business model and, and insanely good execution as well on top of that. And it looked to us like, that could be interesting. You know what? I think when you're a product company that works with commodity content, you always had this envy of like, what if we could differentiate through content, you know, 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 like very hard to do the other thing. So we tried exclusivity in podcasts as a way to differentiate the surface 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. Joe Rogan was initially sitting in his trailer, like the production cost was low and then go in and do exclusivities on top of that. It's kind of counter purpose in a way. The 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 have to, you gotta be right. You gotta be a content picker. And that's a very hard skill that Netflix does extremely well, right? But we had this opportunity. We didn't have to pick content. We just get all of it and use machine learning to se…

AI assessment note: “we tried exclusivity in podcasts as a way to differentiate the surface service, but”

Q 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. Like what would be the world in which as a result of this technology, Spotify's whole business model needs to change? And how do you, how do you go about evaluating something like that?

A It's a great question. And we've seen a few of those examples of business models, and I tend to tell my product teams that And everyone says that, you know, 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, as a side note, they will, they were called car companies, but it was a technology companies or, or, you know, pharmaceutical, that, that was a state-of-the-art technology right then. But because these microwaves came so far apart, they called themselves a car company. They never became Uh, ubiquitous technology companies. It kind of overfitted to that. I think somewhere in the nineties around Google, Amazon, et cetera, these macros started coming so fast that people try to pin them down as a, you know, Amazon is a books company. And they were like, nah, not really. We're doing books, but here's other stuff we're selling. And then like, okay, you're the everything store company. It's like, nah, not really. Now we're selling, uh, you know, Amazon web services over here. So I think these companies are the first set o…

AI assessment note: “these companies are the first set of companies. To have technology as the strategy”