Y Combinator Startup Podcast
00:16:12 · S3, Paul Copplestone, Harj Taggar
[00:16:12] S3: And [00:16:12] S0: and actually, I like, I don't know if you need like, such a Ferrari for a lot of these workloads. We made an acquisition recently, Turso. They've got a architecture that's compatible with Postgres, and actually, it's compatible with SQLite as well. I think SQLite's a phenomenal database. And so we'll provide this tier, which we call Supabase Spark, which is basically for for these getting started workloads. The idea won't be the same. You get started with the same experience. You can scale up to petabytes. So our tagline's gonna prototype to petabytes. And we, as a company, need to make sure that we can provide for everyone. And if they do scale up and their business keeps growing, then we make sure that they have a great time. [00:16:59] S2: Yeah. That's something I was curious about how you think about this actually is like the classic sort of software company you start with, you know, maybe early stage startups, like in a YC batch, and then you sort of have one eye towards the enterprise. And I feel like especially if you're a database company like pre AI, like conventional wisdom as well, you wanna be Oracle so you gotta get to the enterprise as quickly as you can because that's where all the money is and so you start building out like enterprise features. You sort of leaning into SQLite is sort of going the opposite direction. Like, how do you how do you think about it? Like, are you sort of looking both ways?
00:16:59 · Harj Taggar, Paul Copplestone, Garry Tan
[00:16:59] S2: Yeah. That's something I was curious about how you think about this actually is like the classic sort of software company you start with, you know, maybe early stage startups, like in a YC batch, and then you sort of have one eye towards the enterprise. And I feel like especially if you're a database company like pre AI, like conventional wisdom as well, you wanna be Oracle so you gotta get to the enterprise as quickly as you can because that's where all the money is and so you start building out like enterprise features. You sort of leaning into SQLite is sort of going the opposite direction. Like, how do you how do you think about it? Like, are you sort of looking both ways? [00:17:31] S0: Yeah. Yeah. We're having to do both, which is, like, incredibly difficult. Basically, we've got two products that cater on the two ends. So multigresses scale up to petabytes and then terso scale down to, like, these prototyping and SQLite type workloads. So trying to do this at the rate of growth with, like, having to employ more people, it's just... Even with AI is becoming... Or has been a real challenge, but a fun one. [00:17:58] S1: So you ran a poll recently where people went from 10% of your engineers were writing 80% of their code with the coding agents, and then that number recently got up to 60% in a matter of six months. Like, how did that happen? What's happening? Like, you know, where is this going from here?
00:17:58 · Garry Tan, Paul Copplestone, Harj Taggar
[00:17:58] S1: So you ran a poll recently where people went from 10% of your engineers were writing 80% of their code with the coding agents, and then that number recently got up to 60% in a matter of six months. Like, how did that happen? What's happening? Like, you know, where is this going from here? [00:18:19] S0: So we don't have an AI policy internally. We just let people do whatever they whatever they want, and we give them access to to whatever tools they they want to use. And I think now it's just that they're convinced that the models can do so much better better work and so much more. So the adoption has been crazy. And, yeah, the the things that they're building internally are not just five coded type stuff. They're pretty intense. And as we're, like, shifting into this, like, AI coded realm, like, just the amount of testing that we're doing and the tools that we're adopting for testing has been pretty useful to make sure that they actually know that the end result is gonna be good. [00:19:04] S1: Yeah. We're seeing that across y c... The y c startups like Blacksmith Depot, UbiCloud, like, they're all vertical because everyone's doing CI [00:19:13] S2: Yeah. [00:19:13] S1: And the number of tests that you have for just, like through [00:19:16] S2: Like reptile for the So big [00:19:18] S1: that's pretty wild honestly to see. Was it like a pretty... Like, it's just the models are good enough now, and like, it's just people spend enough time where they're like, oh, actually this is quite good.
00:19:18 · Garry Tan, Paul Copplestone, S3
[00:19:18] S1: that's pretty wild honestly to see. Was it like a pretty... Like, it's just the models are good enough now, and like, it's just people spend enough time where they're like, oh, actually this is quite good. [00:19:26] S0: And people need to be convinced, especially engineers. Like, I mean, they might not... At the start of the year, I've thought that it was very good. And the models have gotten better, but also they're starting to see, oh, actually, can achieve some great things with with these models. And all the stuff with Navier-Stokes and all these stuff, like convincing the market that actually, yeah, we can break new ground here. So I think that's the world that we're moving towards, and now people are convinced that this is the way that it's going to be. [00:19:58] S1: You've seen Supabase, like, through three eras. First, kinda like a dashboard company built in a hundred days during YC, then the API company, and then now it's, you know, sort of this agent, you know, make something agents want sort of moment. Was there, like, one or two things, like, in each era that really jumped out at you? Just like, oh, that was the thing that made us in that moment. [00:20:22] S0: I think, like, those shifts happened. So the first one, actually, yeah, I think you were saying, like, why would a database company exist when we came into YC? [00:20:32] S3: We actually like such a contrarian idea at the time, actually.
00:20:32 · S3, Paul Copplestone, Harj Taggar
[00:20:32] S3: We actually like such a contrarian idea at the time, actually. [00:20:35] S0: Yeah. Yeah. Yeah. Yeah. Think, like, we saw how hard it was to use a database even for developers. And so that dashboard first was like, oh, let's build a UI that looks like Airtable on top of Postgres because I actually loved Airtable as well. I was like, wouldn't it be cool if that was just a Postgres database on the back end? So that one was just seeing that even software engineers struggled. And then like when we moved to AI, I think we talked about this on the other podcast. The AI API shift was because we had someone integrating with us and they were like, oh, we want to launch lots of databases. We need an API to do all of this. And that was, like, 2021 maybe. And it turns out that was exactly the right move for 2024 when the likes of Bolt and Lovable and all of these people started building on top of us. Then this year, I just saw that, actually, no one's coming to the dashboard. Like, no one no one visits dashboards anymore. So how are agents gonna build? In this one, I just kinda put out a product memo to the team that said it has to be code first, get native. Supabase just has to shift to to code first. So if it exists on the dashboard, it basically has to work in lockstep in code, infrastructure as code, essentially. And we rearchitected a lot of the CLI and everything to work in sandboxes in code. [00:22:03] S2: Well, you guys maybe too far back, but were you inspired by Parse, another way to see a company?
00:22:03 · Harj Taggar, Paul Copplestone
[00:22:03] S2: Well, you guys maybe too far back, but were you inspired by Parse, another way to see a company? [00:22:07] S0: Yeah. Yeah. Yeah. Parse and Firebase, I I liked both of those companies. And it's funny these waves, right, because they did the back end and Firebase acquired by Google and Parse by Meta. But in some ways, I think they, like, blazed the trail for us to come along and actually have a legitimate database business. Because in 2014, it would have been ridiculous not to use RDS for your for your database. Then they came along. Mongo came along. Mongo started moving to Atlas, and a lot of these database companies kind of showed that you don't need to just use one of the three hyperscalers. You can actually have a legitimate database company. And so that that timing was crucial for us. [00:22:55] S2: Yeah. Past sort of forgotten that. But it was like actually a really well built product. They launched, like, just when I was building iPhone apps for the first time, and it was, like, quite nice to switch to, like, a nice restful API that I trying to deal with. [00:23:07] S0: These shifts always happen with, like, inflection points. Right? So at that point, there were two things that happened in the market. Somehow MongoDB convinced everyone that NoSQL was supposed to be like an amazing way to store your data. And the second was mobile. And so, you know, we're fortunate that we had a couple of these waves as well. And now we're right in the thick of it.