David Hsu: evaluation

Transcript context

…Yeah. So what's really cool, and this is my sense of the AI space overall, you know, if you're on YouTube as well, is that, especially in Silicon Valley, where a lot of the innovation is happening, I think there's actually not that many AI use cases, to be honest. And AI to me, even as of January 19th of 2024, still feels like in search of truly good use cases. And what's really interesting, though, about Retool, and I think we're in a really fortunate position, is that we have this large base of sort of customers, and a lot of these customers are actually much more legacy, if you will, customers. And a lot of them actually have a lot of use cases for AI. And so to us, I think we're almost in like a really perfect or unique spot, we're able to adopt some of these technologies and provide them to some of these like older players. So one example that actually really shocked and surprised me about AI was, so we have this one clothing manufacturer, I think it's either the first or second largest clothing manufacturer in the world, who's using Retool. They're a ginormous company, very multinational, stores on pretty every mall in the world. And so they have one problem, which is, they need to design styles every year, for the next year, basically, for every season. So like, hey, just like summer 2024, for example, and we're going to design. And so what they used to do before is they were hiring designers, and designers would go to study data, they'd be like, okay, well, it looks like, you know, big floral patterns are really hot. And like, you know, California, for example, in 2023, and like, do I think it's going to be hot in 2024? Well, let me think about it. I don't know. Maybe. And if so, if I believe it's going to be hot, let me go design some floral patterns, actually. And what they ended up doing in Retool, actually, is they actually automated a lot of this process away in Retool. So they actually now built a Retool app that allows actually a non-designer, so like an analyst, if you will, to analyze like, you know, who are the hottest selling patterns, you know, particular geos, like this was really hot in Brazil, this is really hot in China, it's really hot, you know, somewhere else, basically. And then they actually feed it into an AI. And the AI, you know, actually generates with Dolly and other image generation APIs, actually generates patterns for them. And they print the patterns, which is really cool. And so that's an example of like, honestly, a use case I would have never thought about, like thinking about like, you know, how clothing manufacturers create their next line of clothing, you know, for the next season, like, I don't know, I never thought about it, to be honest, nor did I ever think, you know, how it would actually happen. And the fact that they're able to leverage AI and actually, you know, leverage multiple things in Retool to make that happen, is really, really, really cool. k, you know, how it would actually happen. And the fact that they're able to leverage AI and actually, you know, leverage multiple things in Retool to make that happen, is really, really, really cool. So that's an example where I think if you go deeper into sort of, if you go outside the Silicon Valley, there are actually a lot of use cases for AI. But a lot is not obvious, like you have to get into the businesses themselves. And so I think we're, we personally are in a really fortunate place. But if you know, you're working in the space and want to find some use cases, please come talk to us like, you know, we're really excited about marrying sort of technology with use cases, which I think is actually really hard to do right now. Yeah, you know, I have a bunch of like, sort of standing presentations around like, how this industry is developing. And like, I think the foundation model layer is understood. The chain vector DB rag layer is understood, I always have a big question mark and actually have you and Vercel V0 in that box, which is like sort of the UI layer for AI. And like, you know, you are perfectly placed to expose those functionalities to end users, you personally don't really know what they're going to use it for. And sometimes they'll surprise you with their creativity. One segment of this, I do see some startups springing up to do this is related to the things that to something that you've you also build, but it's not strictly AI related, which is retool workflows, which is the sort of canvassy boxes and arrows point and click do this then do that type of thing like which which every what are we calling low code? Every internal tooling company eventually builds, you know, I worked at a sort of workflow orchestration company before, and we were also discussing internally how to make that happen. But you are you're obviously very well positioned to it to that. Yeah, basically, like, do you think that there is an overlap between retool workflows and AI? I think that, you know, there's there's a lot of interest in sort of chaining AI steps…

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