Gustav Söderström

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. So it's been so fun to do this with you.

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. So 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?

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.

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.

So 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.

So 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 re-emboldened to take more risk again?

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 re-emboldened 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. And now you would say that sounds almost like TikTok. This was before Musical.ly.

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. And 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.

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 back end, which just did not work at all. So 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.

You could just not get there. And we built this. It was called Moments, the UI. We used editors on the back end, which just did not work at all. So 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 OK, which is why we launched. Then we discovered there was a bug in the A-B test when it was live. And it actually underperformed drastically what we had. So we had to roll it back. And I had taken the entire organization on this excursion. I'd lost a year or something in a very competitive business. That was a good opportunity to get fired. And I didn't.

We had A-B tested it, and it looked OK, which is why we launched. Then we discovered there was a bug in the A-B test when it was live. And it actually underperformed drastically what we had. So we had to roll it back. And I had taken the entire organization on this excursion. I'd lost a year or something in a very competitive business. That was a good opportunity to get fired. And 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 time. swipes. And he was more like Jeff Bezos, matches the inputs, not the outputs. If the inputs are bad, if the ideas are fuzzy and stupid, that's a problem.

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 time. swipes. And he was more like Jeff Bezos, matches the inputs, not the outputs. If the inputs are bad, if the ideas are fuzzy and stupid, that's a problem.