Modal’s sandbox product grew from a small experiment to a third of revenue

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 32:03

   It's, I guess, like the main product, obviously, is like the GPUs. Then you have Modal sandboxes. Is there anything else? I think of the two big products that we have is basically, number one is Modal Functions, and number two is Modal Sandboxes. So with Modal Functions, we launched that back in 2021. It was the idea of serverless functions that are very easy to deploy and very easy to scale, and we manage all the capacity.

2. 32:27

   That turned out to be really, really good for inference, and it turned out to be really good for managing GPUs and running on things like that. But we actually never had a dedicated inference product or a GPU product per se. We never thought of modal as a NeoCloud and I think there's a risk of getting sucked in that direction and becoming a NeoCloud, like just selling what I think was rectangular, like here's a three-year, you get this many GPUs.

3. 32:51

   Modal's always been very good at, you deploy something, you can kind of scale it up, you have this very cyclical or bursty stuff. We manage all the capacity. And the beautiful thing is like, because we have many, many thousands of customers, we can sort of aggregate that capacity and get very smooth workloads, you know, very smooth aggregate demand, which we can manage very, very efficiently. So modal functions was the core.

4. 33:11

   We launched that in 2021. Like I mentioned, we started seeing product market fit in 2023. And now, you know, it's about two thirds of our avenue and empowering a lot of, you know, in practice, it's mostly inference, but you can use it for all kinds of other stuff. Modal sandboxes, we launched that in 2023. three. And it's actually kind of, you know, took a while to see product market fit similar to functions. Why did we launch it? We realized a lot of people we talked to were using LLMs to output code. This was like me and Akshat talking over lunch one day. We're like, maybe they need a place to run that code.

5. 33:42

   And we realized like, actually we kind of have like a lot of the infrastructure already to just take code and run it. Because we've already built the primitives for like managing containers and isolation. We already had, you know, GVisors and isolation and primitive and things like that. So we got kind of excited about that idea and Nakshara wrote a prototype and launched it in basically one day or two days or something like that.

6. 34:04

   Zero, like we saw like very little like growth. I don't want to like trivialize it. We did see some growth. Like there were like some sort of, you know. And it was 2023, so. Yeah, it was 2023. And like, you know, like some people picked it up. Like we had some early users who kind of enjoyed it for certain things. But like overall, it was a pretty insignificant source of revenue going into the summer of 2023.

7. 34:27

   So two years later, we even discussed, do we even need this product? Should we shut it down? Then it just started exploding. So 2023, and I think what really happened in 2023 was LM's got really good at generating code. In 2023? 2023. I mean, it was around that time. I feel like that was when they went from being able to refactor functions and write snippets, So like generating like full apps, right?

8. 34:53

   And so we started seeing a lot of growth coming from like Vibe Coding, you know, companies like Lovable and other ones. And then, you know, companies like Ramp started using model for background agents. And then we started seeing tremendous growth coming from a number of Neo Labs doing things like reinforcement learning on model sandboxes. So sandboxes is now about a third of our revenue. You know, we consider it like basically like our second product.

9. 35:17

   And to me, it's like really exciting because like even back in the early days of modal i always knew that modal you know is about like creating a whole toolkit of products like we always wanted to be almost like a cloud you know you have the storage and the compute and a bunch of different ways to work with it we always wanted to be a multi-product vendor but that wasn't necessarily true in practice until like now where like i think now it's like kind of clear we have functions we have sandboxes we're working on a bunch of other stuff too working on training working on batch we're working on a bunch of other stuff so to me that sort of evolution into becoming like a multi-product company i think it's been amazing because that was that was always so core to the vision even in the very early decks

10. 35:55

    i had a bunch of slides on this uh but but it wasn't necessarily true to the external world until recently.