Gustav Söderström

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

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.

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.

There 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.

There 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.

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.

One 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.

One 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. She did her taxes in Cursor.

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. She 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 has tons of infrastructure. You have the database with play history going 15 years back.

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 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. Some of them are open source. So basically for free, you get what is getting close to AI.

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. Some 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.

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. Now 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.

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. Now 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.