The Exchanges

Q Um, and I think it's a testament to your just overall general philosophy in building Retool that you are, you're just very efficient and, um, you do things from first principles. Um, yeah, I mean, like any, any, um, updates on, like, would you still endorse that? Um, you know, would you recommend that to everyone else? Uh, what, what are your feelings sort of two years on from that?

A Yeah, so on a high level, uh, yeah, so exactly what you said is correct, where we raised less money and a lower valuation. And I think the funny thing about this is that when we first announced that, even, you know, internally and both externally, um, I think people were really surprised actually, because, uh, I think Silicon Valley has been conditioned to think, oh, raising a giant sum of money at a giant valuation is a really good thing. So like, you know, you should maximize both the numbers basically. But actually, maximizing both the numbers is Actually, really bad, actually, for the people that matter the most, you know, i.e. your employees or your team. And the reason for that is, uh, more, uh, raising more money means more dilution. So if you look at, you know, a company like, you know, let's say Uber, for example, if you join Uber at, like, I don't know, like a ten billion dollar valuation, uh, or, you know, let's say you join before their huge round, which I think happened at a few billion dollars in valuation, they actually got diluted a ton, uh, when, uh, Uber fundraisers. You know, Uber raises, if Uber does lose himself by 10%, for example, they'll say they raise 500 to five billion, for example. I think employee's stake goes down by 10% in terms of ownership. Same with, you know, previous investors, same with the founders, et cetera. And so, if you look at actuall…

AI assessment note: “maximizing both the numbers is Actually, really bad, actually, for the people that matter”

Q Retool AI. Uh, obviously AI has been sort of in the air. Uh, I'd love for you to tell the, the journey of, um, sort of AI products ideation within Retool. Um, given that you have a degree in this thing, I'm sure you're not new to this, but like, when did the, what, when would you consider sort of this, the start of the AI product thinking in Retool?

A Yeah. Wow. That's funny. Um, so, uh, we actually had a joke internally at Retool. Um, we, uh, on our product roadmap for every year, I think it was like, twenty-nineteen or something. We had this, uh, joke, which was like, uh, what, what are we gonna build this year? We're gonna build AI programming is what we always said as a joke. And so, uh, but it was funny cause we were like, ah, that's never gonna happen. I was like, let's add it because it's like a buzzwordy thing that enterprises love. So let's look at it. And so it was almost like a funny thing basically. Uh, but it turns out, you know, we're actually building that now. This is pretty cool. So I would say maybe AI thinking on Retool probably first started maybe like, I would say maybe, I don't know, a year and a half ago, something like that, and the evolution of our thinking was basically, ah, when we first started thinking about it sort of in a, you know, philosophical way, if you will. It's like, well, what is the purpose of AI, and how can it help, you know, what Retool does? And there were two, uh, sort of, uh, main prompts, if you will, of, uh, value. One was helping people build apps faster. Uh, and so, you know, you've probably seen the Copilot, you've seen sort of so many other coding assistants, uh, like, you know, stuff like that. So that's interesting, uh, because, uh, you know, engineers, as we talked abou…

AI assessment note: “AI thinking on Retool probably first started maybe like, I would say maybe, I don't know, a year and a half ago”

Q What, what are you going to ask differently for the next survey? Like what, what info do you really actually want to know that's, that's going to change your worldview?

A Awesome. Ask you that, but if you have any ideas, let me know. For us, actually, we were planning on asking very similar questions because for us, the value of the survey is mostly seeing changes over time. And understanding, like, okay, wow, like, let's, like, for example, GPT-IV Turbo MPS has declined, you know, and that would be interesting, actually. Um, one thing that was actually pretty shocking to us was, let me find the exact number, but, like, if you look at, like, the, uh, one change that we saw, for example, like, if you compare GPT-IV.V. MPS, I want to say it was, like, 14 or something, like, it was, like, not high, actually. Um, but the GPT-IV MPS thing was, like, 45 or something like that, so it was, like, quite a bit higher. So just, I think that kind of progress over time is what we're most interested in seeing is, you know, are models getting worse? Model's getting better? Are people still loving PG vector? Do people still love Mongo? You know, stuff like that. That I think is the most interesting thing, so. Do you two have any questions that you think we should ask?

AI assessment note: “we were planning on asking very similar questions because for us, the value”

Q sort of chaining, um, AI steps together. Do people, uh, I, I, I couldn't tell if, like, that is already enabled within Retool workflows. I don't think so. Um, but you could, you could sort of hook them together, it's kind of jankily. Um, like, uh, is there, is there, like, what's the interest there? Um, you know, is it all of a kind, ultimately, in your, in your mind?

A It is a hundred percent, uh, time, and yes, you could actually already, uh, so a lot of people actually are building AI workflows down every tool, uh, which is, we're gonna talk more about that in a second, but a hot take here is actually, I think a lot of the utility in AI today, uh, like, I would probably argue 60, 70% of the utility, like, you know, businesses I found in AI is mostly via ChatGPT, uh, and across the world, too. Um, and the reason for that is, I mean, the ChatGPT sort of, uh, UI, you could say, or interface, or, you know, this experience is just really quite good. You know, you can sort of converse, uh, you know, with an AI, basically. Um, and, uh, that said, there are downsides to it. Um, if you talk to, like, a giant company, like a J.P. Morgan Chase, you know, for example, um, they may be reticent to, uh, have people copy-paste data into TextGPT, for example, even on J.P. Enterprise, for example. Some problems are that I think China is good for one-off tasks, so if you're like, hey, I want a first version of representation or something like that, you know, and help me write this first version of a doc or something like that. China's great for that. It's a great, you know, very portable, you know, if you will, form factor, so you can do that. However, if you think about it, ah, you think about some economic productivity more generally, The chat, again, will …

AI assessment note: “we're gonna talk more about that in a second, but a hot take here is”

Q Yeah. And just like general, um, market thoughts on AI, um, uh, are you, uh, you know, are you, do you think spend a lot of time thinking about like AGI stuff or regulation or safety, um, or like, uh, what interests you most, uh, you know, outside of the retail context?

A Wow. Uh, well, if you want us to read the context, the actual question. Yeah, in my opinion, I mean, there's a lot of hype in AI right now, and there's, again, not, not so many use cases. So for us, at least from a regional context, there really is, how do we bring AI and have it actually meet business problems? And, uh, again, it's actually pretty hard. Like, I think most founders that I meet in the AI space will always leave more use cases. They never have enough use cases. Uh, sort of real use cases. People always pay money for it. Really where the regional interest comes from? Me personally? I mean, philosophically, uh, yeah, I've been thinking recently myself a bit about sort of intentionality and AGI and like, you know, uh, what, um, what would it take for me to say, yes, you know, GPT-X or, you know, any sort of model actually is AGI. I think it's kind of challenging, because it's like, I think if you look at like evolution, for example, like humans have been programmed, you know, to do like three things, if you will, like, you know, we are here to survive, you know, we're here to reproduce, and we're here to like, you know, uh, maybe those are just two things, I suppose. So, like, it's basically, to survive, you have to go eat food, you know, for example. Uh, to survive, maybe like, um, uh, having more resources helps, you want to go make money, you know, for example. U…

AI assessment note: “I've been thinking recently myself a bit about sort of intentionality and AGI”

Q this space, and like whoever is best positioned to serve their customer, Um, in, in the way that they, they need sort of need to shape is, uh, is going to win. Um, do you have a philosophy against around like what you won't build? Um, like what do you prefer to partner, um, and, and not build in-house? Because it seems, I feel like you build a lot in-house.

A Yes, there's probably two philosophical things. So one is that we're developer first. And I think that's actually one big differentiator, apparently, like Austin's actor. Now, if you know, we're so very rarely able to see them, actually. And the reason is we're developer first. Because developers, like, If you're, like, building a sales ops tool, you're probably not considering Notion if you're a developer. You're probably like, I want to build this by React basically, or, uh, user tool. And so, uh, are you a build for developers? It's pretty interesting, actually. I think one huge advantage of some of the developers is that they actually don't, like, developers don't want to be given an end solution. They want to be given the building blocks to themselves to build the end solution. And so for us, like, you know, actually, You know, uh, interesting point that, uh, equilibrium we don't get to. It's basically to say, hey, we're just a consulting company, and we basically build apps for everybody, for example. And what's interesting is that we've actually never gotten to that equilibrium, and the reason for that is for some of the developers. Developers don't want, you know, like a consultant coming in and building all the apps for them. Developers are like, hey, I want to do everything myself. Just give me the building boxes. Give me the best table library. Give me, you know, goo…

AI assessment note: “We have, I think, basically never built anything specific for one customer”