The Exchanges

Q ask you this question that I've been asking everyone that comes on that is building a Product that helps engineers build products and product managers build products and designers. So you could sit next to every single new user that, uh, opens up windsurf and whisper a couple of tips in their ear to help them be successful with the product. What would be a couple of tips you'd share?

A Tip number one is just be a little bit patient and both patient and explicit, right? Uh, when you ask the application to go out and make some changes, it could actually go out and make many Irrelevant changes, right? And one of the things that I think prevents this the most is just be really, really explicit or as explicit as possible. And one of the things I, I sort of ask people to do is in the beginning, start by making smaller changes, right? If there's a very large directory, don't go out and make it refactor the entire directory, right? Uh, because then if it's wrong, it's gonna like basically destroy 20 files. And I think from there, one of the key pieces I think that comes from the users that use the product is they sort of learn what the hills and valleys of the product are. And the analogy I like to give are kind of similar to autocomplete, right? When you use a product like autocomplete, you would think a product that is suggesting things, but only getting accepted. 30% of the time would be really, really annoying. But the reason why it's not very annoying is actually because you've actually learned that, Hey, 70% of the time, I don't need to accept this or, or, uh, and the times that I do, I know how to get value from it.

AI assessment note: “Tip number one is just be a little bit patient and both patient and explicit”

Q That's so empowering. Makes me think about, uh, Ori Levine was on the podcast, co-founder of Waze, and he has this phrase that he, he wears on his shirt. His book is called, this fall in love with the problem, not the solution. And that feels like that's exactly what you're describing. Okay. So let's talk about windsurf. Uh, what's the simplest way for people to understand what is windsurf?

A Yeah. So Windsurf is an IDE, right? It's an application to go out and, and build software and build applications. Um, the, the, you know, the crazy thing is a lot of people who use the product don't even probably know what an IDE is, uh, which is, which is crazy. And we'll get in, we'll get into that in a second, but why did we go out and build Windsurf and what is Windsurf maybe? Why couldn't we have just done this on top of conventional IDs like Visual Studio code? So maybe just to get into this a little bit, as we saw that AI was getting more and more powerful, the way people go out and build technology, we thought the interface for that was going to change remarkably. It was not going to be a conventional pure text editor where you, the user's writing a handful of lines of code or most of the code. And the IDE provides, uh, like maybe some basic feedback on what the user is doing right or wrong. And the basic feedback to be, Hey, there's a bug in your software, a compiler error in your software. It could do much more.

AI assessment note: “Windsurf is an IDE, right? It's an application to go out and, and build software”

Q This may be getting too technical, but just, is there anything interesting around what you train on? Yeah.

A So one of the, one of the interesting things that we have from our users, and this is like where we try to think, like, why would we be any better? It's that actually every hour we get probably tens of millions of pieces of feedback from our users. We get a lot of feedback on what they like and what they don't like. For something like autocomplete, we get a lot of preference data, a lot of preference data. And the preference data is weird. It doesn't look like data that you find on the internet. It's like data as the user is typing, right? Imagine you're typing, typing, um, some code in a code base. Uh, the code's gonna be incomplete as you're typing it, right? It's not gonna be in a full fledged form. It's not like it is on GitHub, but we have a lot of data that looks like this. So we are uniquely well positioned to actually build a good model that can complete code, even when it's in an incomplete state, when the models that are out there, the frontier models have consumed very little code that looks like this. So for that case, we're like, Hey, we can go out and do a much better job potentially.

AI assessment note: “we get a lot of preference data... It's like data as the user is typing”

Q which is definitely not an overnight success, but I feel like I've been hearing about Windsurf more and more as people's favorite AI tool. And I just don't think people know the story behind Windsurf, behind Codium, the company that you built. So I thought it'd be good to maybe just start there. And have you just briefly shared the history of Codium and how Windsurf emerged out of Codium?

A Yeah. So the company was actually started close to four years ago. Uh, as you, as you know, AI coding was not a thing four years ago. ChatGPT was not out four years ago. At the time, we actually started out building GPU virtualization and compiler software, right? Uh, before this, I worked in autonomous vehicles. My co-founder who I've known since middle school, uh, worked on AR VR at Meta. And for us, we believe deep learning would touch many, many industries, right? It wouldn't just touch, uh, like sort of autonomous vehicles. It would touch financial services, defense. Uh, healthcare. And we believe these applications were hard to build these deep learning applications. So we made it possible for you to effectively run these complex applications on computers without GPUs. And we would handle all the complexity of being able to actually run the workload on the GPUs for you.

AI assessment note: “So the company was actually started close to four years ago.”

Q Here's a question that I've been hearing more and more is just how do you do interviews these days with tools like Windsurf out there that solve all your problems?

A We're okay with people using the tools because I think one of the worst things is like, if someone comes here and doesn't like using these tools, like we believe they're massive productivity improvements. We do bring people like into the company, like on site so we can actually like See how they think through problems on a, on a whiteboard and all these other pieces. So, so we do want to see how they think on their feet and hopefully they're not just like taking what we're saying, putting it in a voice translator and sticking it in the chat to PT and getting the answer out. So there is a way to do this. My viewpoint on this is, is, uh, the tools are really, really important, but I do think we still look for some problem solving ability, right? Like if the only way you can solve a hard problem is like put it into chat to PT. I think, I think that's like a concern to us.

AI assessment note: “We do bring people like into the company, like on site so we can actually”

Q Okay, I have one more question. I apologize. What's one thing that you wish you had known before starting Codium?

A Honestly, I wish I had maybe humility is like the wrong term, but this idea of just being okay with being wrong faster. Um, like I always think about things on like when we make decisions, me and my co-founder, uh, we always talk about it. We're almost like, Hey, I wish we had made the decision to do this a couple months earlier. We always talk about this and The weird thing is outside looking and everyone's like, wow, like actually, you know, the decision was made at the right time, but in my head, I'm always banging my head being like, what if we had made it a couple months earlier? And I think part of that is, you know, I waxed poetically about like, oh, you need to be irrationally, uh, sort of optimistic and uncompromisingly realistic, but it's very hard to do this in practice, right? Cause you drink your own Kool-Aid too. It's very, cause if you're not drinking your own Kool-Aid, you, you won't get up out of bed, right? The answer is already solved. It's not actually any of these startups. The answer is, Microsoft is going to be the, be the winner in any software category, right? Isn't that, isn't that the answer? Uh, just because of distribution resources and capital, right? Uh, they're going to commoditize every space. So I think, I think in some ways you, this, this amount of, of just understanding that, Hey, like reevaluate your hypotheses and get into an uncomfortable…

AI assessment note: “this idea of just being okay with being wrong faster.”