Cursor.so: The AI-first Code Editor — with Aman Sanger of Anysphere

**Alessio** (0:10)
Hey, everyone. Welcome to the Latent Space Podcast. This is Alessio, partner and CTO and resident of Decibel Partners, and I'm joined by my co-host, the Swix, writer and editor of Latent Space.

**Swyx** (0:20)
Hey, and today we're back in the studio again after a little break, and we have Aman Sanger in the house. Hey, Aman. Thanks for coming.

**Aman Sanger** (0:27)
Thanks for having me.

**Swyx** (0:28)
So we'd like to introduce a guest and then have you fill in the blanks. So you worked at Gamelon, Bridgewater, McKenzie, Google and u.com, all on sort of kind of AI-related things and some finance-related things. You also ran your own consultancy, Abelian AI, and you graduated in CS and Math from MIT recently, worked on a few projects, including Instill, which I think we'll cover a little bit later, and most recently, Cursor.so, which we'll cover for the vast majority of the podcast. But just on the personal side, what's one thing that people should know about you that might not be so obvious on LinkedIn?

**Aman Sanger** (1:00)
Oh, interesting. In a previous life, I played a lot of squash.

**Swyx** (1:05)
You were a top seed?

**Aman Sanger** (1:06)
Yeah, so in high school, I kind of competed in tournaments. And most people probably don't really know what squash is. It's like tennis in many ways. It's like a racket sport, but it's indoors. You play against a wall. I guess now pickleball is all the rage with racket sports. It's a lot of squash.
Yeah, the story is I used to play tennis. And then I moved to a building that had a squash court in it.
And then I picked it up. I loved it. And I've been playing ever since. So I competed a lot in high school, played a bunch at MIT, have not had the chance to play much here. In San Francisco, there aren't too many courts.

**Swyx** (1:38)
We can organize a squash tournament.
And then you'll crush it, of course. Is there anything about the athlete mentality that you take with you as a founder?

**Aman Sanger** (1:47)
Yeah, I think it can be at times a bit too much, but I'm very competitive. I really hate losing. Like now I think I'll go on runs. And if someone tries passing me, I won't let it happen.
I'll just kick it into overdrive and maybe I'll turn the corner if I know they're going to beat me. But I can't let someone pass me when I'm running. And I think the same is true with starters where the competitive nature, I think, in general, helps motivate me and makes me, I guess, just work harder.

**Alessio** (2:17)
Yeah.

**Swyx** (2:18)
OK. Well, we'll have a bunch of competitive questions later. But we'll go over the timeline.

**Alessio** (2:22)
Yeah, let's jump into how you got to Cursor. So in August 2022, you launched something called Instill.
Can you talk a little bit about that?

**Aman Sanger** (2:31)
Yeah. And maybe before I go into Instill, I should talk about what I was even doing before that. Because Instill is actually a very brief array from what I was doing with my original co-founder, Michael. So we had both actually gone to the same high school together, gone to MIT together. And then after graduating, we knew we wanted to start something.
And in June, what we were working on was also called Cursor, but very different. We basically were very, very fanatical users of Copilot. We loved it. And we had a little bit of experience with computer-aided design or CAD software. A lot of our friends, in fact, were mechanical engineers.
And we'd heard a lot about how tedious it was just to design these parts and software like SolidWorks and whatnot. And it was pretty obvious to us that if you could train a transformer on the task of predicting the next token, not just for code, but for CAD, then you could get a really useful product that could speed up mechanical engineering. So that's actually what we'd worked on up until and still even a little bit after and still.
And yeah, I can go into more detail about that. It was pretty interesting. That's probably how, despite these days doing less stuff with model training than in the past, for that it was all just kind of rolling our own models from scratch, a lot of training, a lot of inference.

**Alessio** (3:47)
I'm always curious to hear about what made you interested in that, you know? Obviously you've been at the forefront of a lot of this AI work.
Why was that the most interesting thing to you? Did you think there were not as many people going after that? Did you think you had a unique insight into it? Because we got a lot of people listening that wanna be founders and wanna figure out how to make that decision.