Buying a Building with ChatGPT - Ep. 1 with Sahil Lavingia

[00:00] Sometimes like you can say like, I'm trying to buy a building. [00:03] And then I was like, okay, well, let me, like, [00:05] Let me start visualizing, like, is this the right... [00:08] You're getting it to write a book. [00:11] in real time for you. It's like a book that doesn't exist. Like this one city per country is like this essay that I was writing. And so I started with this tweet, which is like kind of like a [00:25] Uh, [00:26] to make the point compelling. This is a thing too, right? Sometimes it can't suggest examples. I'm like, okay, this rule doesn't actually generalize. I have this theory that ChatGPT is the most important creative tool of the decade, but it's still so early that most of us don't really know how to use it. There are a few people though, who are living in the future, who have the time and the curiosity to figure things out. Those people light the way for us. They show us what our future with these tools will look like because they use them every day already. That's what this interview series is about. We'll go in depth with the most interesting [00:56] of how they use ChatGPT to think, write, make art, make decisions, build businesses, one chat at a time. [01:03] My guest on the show today is Sahil Lavindia. Sahil is the founder and CEO of Gumroad, one of the largest platforms for creators to sell their work online. He's also an active investor and the author of The Minimalist Entrepreneur. I've known Sahil for about 10 years, and he's one of the most original thinkers I've ever encountered. Let's dive in.

[01:32] Welcome Sahil. Tell us how you use ChatGPT. [01:35] Yeah, I saw your tweet initially about how, I think you had a poll about how often you use it on a daily basis. [01:43] And I just looked at the app, which is primarily where I use ChatGPT through their app, which has gotten, it sort of improves by leaps and bounds, like almost it feels like on a weekly basis. [01:55] and [01:57] Basically, I was using it like three or four times a day for different things. And I was just kind of like surprised by that. But I use it for... [02:06] Yeah, I use it for all sorts of things. I think of it like... [02:09] There's just no excuse for not [02:12] There's this phrase that often comes up in conversation, I really notice it now. [02:17] which is like, I don't understand why. [02:20] And I often hear this, right, where it's like someone will be talking about some thing and say, oh, I don't understand why like Democrats X, right, or like Republicans do this or like I don't understand why like Elon like doesn't get like or I don't want to get why like. [02:36] And, you know, I just find that, like, I just don't, I just refuse, like, that's not, there's no excuse for not knowing why anymore, right? Like, you can always ask. And so I find that, like, basically, it increases, like, one, I spent a lot less time on bad ideas. [02:55] I think a lot of people, what they do is they have like a to-do list of like things that they want to do at some point. [03:01] I don't have a to-do list. I don't have any. I mean, maybe I do. I could probably find something, but it's like one item long. And it's like right now it's probably says like buy a building.

[03:11] Like, you know, it's a very, like, [03:16] Actually, right now I don't even have that. [03:20] you know, just literally pick up some groceries from Costco, but it's one item. And the reason is basically because [03:27] when I have an idea, I can very quickly invest, you know, the equivalent of what would have taken like months of time to research or weeks. [03:37] And, you know, and because I would have to sit down at a laptop and I would spend like, you know, like half a day like looking at like and then I would have to do that three or four different times. And now I can sort of just like as I'm. [03:48] on the subway or going for a walk in Brooklyn or something, I can just ask it a bunch of stuff. [03:54] right, cue up like all of these sort of like serial research processes. [03:58] And then often most of my ideas are terrible, right? So like the reason I don't have a to-do list is because I don't have that many good ideas. But I think a lot of people, like they sort of delude themselves into thinking they have like all of these things. And they're like, they're on the back burner, right? And they just have to figure out like how to make the time and this and this. And like, but the truth is like if you actually examine the idea, like at a pretty decent level, you realize it's actually not that good. So I think that is one of the most useful things. [04:23] things about it is it focuses your research on like what actually matters. [04:28] I think a lot of people have in their minds eye a really good idea, right? An essay or a movie or something. But then when they like, [04:38] The truth is, it's actually not that good. It just...

[04:42] you think you can just like sort of like pretend that it's good when it's not in like a concrete form. Right. It's like, if it's a really good idea, like just write it. [04:50] Like, tell me the idea. Don't like tell me the log line for the movie. [04:54] like tell me the exact scenes in the movie, right? And I think, Chad, GBT, it allows you to ask these kinds of questions. And [05:02] basically get to a zero or like, is this worth pursuing sort of more? And I think this drastically changes like a lot of like the way, like even investing, for example, like the bar that I found, like a founder can do so much research [05:16] in a weekend, right? That like, they come to me, like, like, for example, before now, like, right now, for example, I'm like, I'm thinking about buying a building in New York City. And [05:26] It's a thought that I have. But the amount of... [05:30] sort of research that I can do, fact checking on lots, background checks on lots, [05:35] previous property owners, the history of usage for certain buildings, zoning requirements. I can visualize what it looks like. [05:44] that like in, you know, [05:46] the sort of pitch deck that I would be able to create to, you know, to raise, let's say any amount of money to do this. [05:55] Like the bar for what that needs to be now is like, it's literally like before, like three years ago, it would be like, and I still get these by the way, cause you go to loop net and you can find like, [06:04] the pitches for these buildings, right? And it's just like, [06:07] seven photos taken with like a Canon, [06:09] and some text and like there's just no... And I think that you won't see the impact in a lot of things, but I think in the top 1%,

[06:18] right? Top 1% of movies, the top 1% of hotels that get built, like the top 1% of all products. [06:23] will be so much more thought through. So anyway, that was kind of a rant. But that I think is like a big, a huge one is I just find that like, the research, like, I just don't have to, I don't have to pretend that like, I have like 50 ideas and I need to do them, I can focus on like, okay, I have road and has product market fit, you know, that's really hard. I've like, [06:44] I'd rather double down on the things that work. So I think that [06:50] That's been really, really helpful. [06:52] So what I'm hearing I think so far is [06:56] It's a tool for you when you have a random interesting idea that you get really excited about to [07:02] kind of go deeper on it to, I guess, filter out ideas that are actually not worth your time or are bad. And then also, like when you have something that you're pursuing seriously, like buying a building, it raises the level of quality of research and, I guess, output that you can you can create because it puts all the things that you might need at your fingertips. Is that a good summary of what it does for you? [07:26] Yeah, I think a lot of doing doing projects like that have an impact in the real world are [07:33] like they require having a lot of conversations with people. And so if you can like bring such a, [07:37] like a better level of conversation to your first meeting [07:40] with like a real estate developer and then your second meeting with a construction manager, your third meeting with a general contractor. Like at each level, you know, you're, you're having a,

[07:50] a conversation with them, you're learning a lot of things that you got wrong, basically. [07:54] And imagine if like you, you didn't get those things wrong. You actually brought them like a better plan in the first place. They would still tell you a bunch of things you got wrong. They would be different, better, more nuanced things. Right. And so I think that also, I think is like sort of a value is like, I can show up to a meeting and, [08:11] And people are like, how do you know so much about [08:15] architecture. It feels like you've read too many books. And it's like, well, ChadGBT just told me. If you ask a very specific question, as long as I can frame the question, [08:29] I can say what material was 58 Bowery constructed of? [08:35] and bring that up with like the person selling the building. And they're like, that is really like, [08:41] There's only one article on the internet. You would have had to have spent 15 hours to find that. [08:46] in a PDF somewhere. And it's like, well, actually, ChadGBT just told me that directly. [08:51] Right, right. Right. But the value is to them is like, okay, you're pretty serious. Yeah. But to them, it's like, this is the one building I've done this research for. It's not possible to do this for like 50 buildings. [09:07] But actually it is impossible to like, you want to like put the level of work on, you know, in every, in everything that you do and that you need to examine if it's actually worth pursuing like which one is. [09:19] is worthwhile, right? So imagine like

[09:22] If... [09:22] the equivalent of like every time you buy a piece of furniture, you're doing 100 hours of research. [09:27] And that means like a hundred hours of like actual research, like, [09:32] you're gonna make a lot less bad decisions, right? [09:35] you're going to buy a lot less bad products. [09:38] if you were actually doing the research. [09:41] Yeah, and I think that kind of like can extrapolate, right? Like imagine like right now, I don't think there's a YouTuber who says like, [09:51] I do 100 to 1000 hours of research every time I buy like a chair or something, you know, but that could be possible. Like, I think the. [09:57] like the types of content that you will be able to make. Because a lot of this, like humans won't actually do. [10:03] But someone will do it. [10:06] Right. So you can still benefit from like a lot of the value of like a better movie without having made the movie yourself. Right. Right. [10:13] um [10:14] Yeah. [10:16] Yeah, I think this is really cool. I think for the building, the building example is one that I'm really interested in. Like, take us through some specific chats that you've had so we can see [10:24] how you're doing it. [10:26] it looks like you started on this Dolly one, we can start there. Or if you have other chats you think are better to start with, [10:32] I want to know, okay, what was in your head where you're like, oh, this is a great chat GPT thing. And then what was your first message and what was the outcome of the chat? [10:41] Yeah, I mean, so I think of it like, you know, if you think about high risk investing generally as you make a thousand bets and one of those is going to be.

[10:53] you know, your thousand X return [10:55] ideally 10,000 X return or something, everything else goes to zero. You have like a 10 X founder, right? Like that's sort of like the model is this like power law returns. So I think similarly with [11:06] with investing in a building in New York City, for example, is that, let's say there's a thousand buildings you could potentially buy that will be listed on the market within some constraints. [11:18] uh in the next [11:19] three years, [11:21] one of them is the building, right? And everything else is not. [11:26] And so I think a lot of it is just figuring, like doing stuff like just narrowing down. [11:31] uh like for example i really believe strongly in the concept of like network effects [11:36] uh, [11:37] and investing in network effects, doubling down on the ones that you have, how hard they are to actually find, [11:45] And so, you know, things like asking like, [11:47] you know, what roads actually started to exist first in downtown Brooklyn. [11:53] Right. Like my guess is that like the first roads are still the most popular roads, like [11:58] The network effect just keeps building, even though people may forget. [12:03] you know like like basically for example like the first road in new york city is basically [12:07] Broadway. [12:09] Like Broadway and Bowery are the same road. [12:12] But that's like before basically the Indians like had that footpath that went basically through the center of Manhattan. [12:20] at a diagonal, right? [12:22] So anyway, fun fact, but it's, you know, being able to like actually ask and learn about all of these things without having to like traditionally I would go buy like a book.

[12:33] Like I would get a recommendation from somebody about like a 400 page. [12:36] kindle book yeah and i would have to go read that and now i can just like ask it [12:41] these questions, right? How did you start that chat? [12:44] History of downtown Brooklyn. Okay, got it. So you're sort of thinking to yourself, okay, I'm interested in downtown Brooklyn as an area I might want to buy [12:52] But before I do that, I really care about the history. I want to know what which roads came first. I want to I want to understand that because [12:59] the past influences the present so strongly. But rather than like having to go read like a gigantic book or like do like a ton of Googling, there's a type of couple of things into ChatGPT here and it gives you mostly what you want. [13:13] Exactly. And I think here, you know, it gave me this like very like Wikipedia ask thing. Yeah. I realized like, no, what I really want is the origin. [13:21] Like the real formation event of... [13:25] like, you know, the region. [13:28] And so, you know, you can modify [13:30] And it's kind of like you're getting it to write a book. [13:34] Yeah. Right. Real time for you. It's like a book that doesn't exist. Yeah. But ideally, if you know what you if you're starting to narrow down like what you what problem you're actually really trying to solve, you can like get the book written for you. [13:47] Yeah. [13:48] Like this could be have been much more specific if I if I was like, [13:53] By the way, you know, the reason here is to is to like buy a building and so like [13:59] focus on, you know, interesting structures that were the first structures that were built or something. Right.

[14:04] And then it would have focused on like, well, the steam ferry service like probably had a building associated with it. Right. Right. [14:10] I think you're also doing something that I think is really important, which is like, [14:15] that I think a lot of people miss is [14:18] It gave you an answer originally that you didn't like that much. [14:21] and [14:22] Um... [14:23] and you just told it go again. [14:25] Right? [14:26] And I think a lot of people just give up after their first answer rather than refining and being like, hey, like do it again in this specific way. [14:34] I think that's really valuable. [14:37] Yeah, and it's often... [14:38] like kind of stochastic right where it's it does often like kind of like investing like [14:43] nine times it might not be that interesting. But every once in a while it has like a really interesting like fun fact. [14:51] Like for example, like the region of Dumbo, [14:54] is... [14:55] one of the best investments, right, in the real estate in the US in the last 100 years or so. [15:02] Uh, [15:03] But if you think about like, like even something like just asking you this more specific question, if you really pay attention to what it said, [15:11] And you were able to like, let's say there was a book that you were reading, right? [15:15] 50 years ago about downtown brooklyn and it said very specifically like [15:18] iconic structures like the Brooklyn and Manhattan bridges. This is basically the reason that Dumbo is so successful. [15:26] And it literally uses the word iconic. [15:29] Right. So if I was even like... [15:32] it's like the answer is

[15:35] to making a thousand extra return investment. [15:38] is there. [15:39] you just have to kind of see it and ask the right question. [15:42] and pull it out. [15:44] And I think like being able to write better and better prompts like this. Yeah. Like I'm basically like and and sometimes it's funny like Sam Allman, I think he he had an interview. [15:55] And he said, someone asked him, like, how's opening I going to make money? [15:58] Yeah. He basically said as a joke, [16:01] I think. [16:03] We're just going to ask the AI. Like, what are you? [16:06] It'll tell us the best way to make money and we'll just do that. Right? Yeah. But it's sometimes like you can say, like, I'm trying to buy a building. Like sometimes people don't even vocalize what they're actually trying to do. [16:19] But if you just say like buy a building in UNC and finding... [16:24] Thank you. [16:25] network effects. [16:27] Thank you. [16:28] That may have kick-started. I need to go... [16:36] and it just yeah you start to learn like how to sort of focus the Kona vision of [16:41] of the AI. I'm curious, like, yeah, it's, I guess it sounds to me like once one of the things you're showing us is once you have a thesis, it helps you do the research to like support or find [16:56] opportunities based on that thesis. [16:58] Um, [16:59] But I'm also kind of curious the extent to which it's helped you [17:03] identify or refine a thesis. Like you have this, okay, there's one in a thousand buildings,

[17:08] Um... [17:09] you know, I want to [17:11] by building based on sort of the network effect of how the area was established. Yeah. Did you play a role in that or where did that come from? [17:20] I mean, it certainly can. I mean, those, I think, often come... [17:25] Like from that's kind of like the spark, you know, like just like it kind of just appears to you as like an idea. [17:32] like Harry Potter or like, you know, at some point the idea, I don't know where it comes from. Yeah, but I do think you can like [17:38] hold yourself accountable to like, is this actually a good idea or not? You can tell it your idea and say, [17:45] poke holes in this. [17:47] And that has been [17:48] quite useful too, right? Like you can, and this is less useful in maybe like the business stuff, but I do find that like someone, someone, I remember someone told me some fact about like Israel and Palestine or something. And I was like, oh, that's crazy. [18:02] And then I told somebody else. And then I was like, wait a second. [18:05] I never actually checked if that was true. I just thought it was like an interesting fact, you know, like the interesting this was why I was sharing it. But then I was also like as part of that sharing, like, [18:15] some numbers or whatever, uh, [18:17] And then I looked into it and I wasn't able to find that it was actually true. But being able to just in real time do that also, I think, is a way of just saying, hey, I learned this fact. [18:29] is it true or is it not true? And like, [18:32] explain why or what, you know, like cite your sources, like that sort of stuff is quite helpful.

[18:40] Even tweets, I have ideas for thoughts I want to share and I write an essay and I say, "What are the biggest holes in this essay?" [18:47] Yeah. And sometimes honestly, like sometimes it's like this is a big hole. I'm like, oh, yeah. [18:52] Right. I think of that. [18:54] Like this one, right? Like this one city or country is like this essay that I was writing. [18:59] And so I started with this tweet. [19:02] Which is kind of like a thesis. And then I just say add three to four... [19:08] uh to make the point compelling also suggest [19:12] more examples this is the thing too right it's like if it can't sometimes it can't suggest examples [19:17] There's no point to be made here. Then this rule doesn't actually generalize. [19:22] But then, you know, it kind of like responds with this nice thing and then I can kind of like edit it. [19:27] And then at the end, I can, you know, [19:29] uh, [19:30] I can sort of decide if it's worth doing or not. I also think it's a way to come at a problem from multiple angles. [19:38] Um, [19:39] right so if you have you can say you know like this idea isn't working but can you come up with different ideas [19:45] Yeah. [19:47] Like I'm looking at Chinatown, but am I missing... Are there places that are more populous? Right, right. You know, and then it sort of can expand, like... [19:56] I think of a lot of the innovation in this new wave of AI as peripheral vision. [20:02] Mm-hmm. [20:03] where it like because of the token, the way it works and like, you know, basically each token in the in the context, like, [20:09] influences the next thing, not just like the most recent ones. I think that allows for this like interesting like level of peripheral vision where like you wouldn't actually see. You see this a lot in Dolly, for example, where I would ask something.

[20:27] uh, [20:28] And then it's actually quite interesting how it shows you the prompts that it generates. [20:33] Let me just see, what did you ask? So interior of a social club inside Bowery Bank social club. [20:39] And what was the context? Why'd you ask that? [20:43] So, you know, this is sort of like fast forward. Imagine like I'm now refined my search to like, you know, I started getting into more specific areas and I eventually like found this like specific building. I was looking at like daily traffic. [20:56] So I got pretty close to like this. So you narrowed it down to like a building that you really wanted to look at. [21:04] and then called 58 Bowery. [21:06] And yeah. [21:08] Exactly. And then I was like, okay, well, let me like... [21:11] Let me start visualizing, like, is this the right... [21:14] venue. [21:15] Basically, I spent a lot of time on the exterior, like the location. It's like, okay, that's like part one of the thesis. Now part two is like, is this the right building from the interior? Like would it have the right... [21:27] vibes, basically. That makes sense. And what was the first? So it sounds like you send an image to chat GPT, the bank building social club one where you're asking. Yes. Okay, so you so you went in the building, you took a tour, it sounds like. [21:40] And then [21:41] you took a picture of it and then asked [21:46] Dolly to come up with or ChatGPT to come up with prompts for what it could look like. [21:52] um [21:53] Exactly. I specified, I don't know if it actually really used this image that much. I was hoping that it would, it would like generate prompts that would like kind of follow it a bit more. But yeah. But one day that, that, that, that I think will happen where you'll be able to basically upload, you know, upload a photo and ask it to edit it.

[22:11] Um, [22:12] But basically, yeah, I just asked it to give me some prompt generation ideas. And then I took this because they are currently two separate models. I basically just took all of these ideas and then pasted it at the top of this. Or not at the top. Why was that useful to you? Why were the prompt generation ideas what you needed? Tell me about that. [22:32] Thank you. [22:32] I felt like it wasn't [22:34] I needed to basically refocus it on what the problem actually was. [22:39] And the problem was basically I need a diversity of... [22:43] like prompts. [22:45] But they were all focused on this specific thing. [22:48] which is a social club for creative. [22:50] in this specific area. Like, to me, this is the thesis. Everything else is a little bit arbitrary. Yeah. [22:57] Or, you know, like this part. [23:01] And so I basically just wanted to kind of like seed it with tokens that were like, [23:06] like interactive digital wall, like interesting ideas that like, the problem with this is this was basically like too broad. [23:13] And it would just merge. And then I wanted to kind of like refocus it back on like, [23:18] the more specific vision. [23:21] Um... [23:23] Thank you. [23:24] Yeah, so I started just kind of asking you questions and [23:26] getting it to generate like what I thought would [23:29] would. [23:30] Basically what I would kind of use in a-- like I would actually go out and hire an artist and render stuff. [23:37] But it's just a way to get really fast.

[23:43] It's sort of like, yeah, like it's sort of the first draft, like really quick, like as many different things as possible. So you can narrow your search down into like a range of things that speak to you. [23:53] Yeah, and I think it helps, it aids in if you need to communicate with another human being and you can't like, [23:59] project [24:00] I know in my mind's eye what it should look like. [24:04] but I can't communicate that with you, right? Without having to spend 10,000 hours learning perspective and anatomy. [24:10] which I do I've spent thousands of hours learning to draw and I would like to be able to do that too [24:18] But it's just like life's too short. Yeah. And where did you, where did you get to like at the end of this? Like, where did you end up with it? What did it give you that you didn't have before? [24:29] I mean, one, it gave me confidence that this is still worth [24:33] pursuing that like this it's sort of farther than [24:36] the 50 other buildings that I've spent time on, that sort of thing. [24:40] Yeah. And so, [24:43] you know, I'm going to go like see it again and like spend more, more like basically I'm going to, uh, [24:49] Thank you. [24:49] My next step is I'm going to get the basically model. I have the floor plans. So basically model the [24:55] building in 3D. [24:56] And... [24:57] basically design, you know, [25:00] and basically designed this whole, whatever this ends up looking like in... [25:05] in 3D space. Because I think the thing that currently AI, like the leap it cannot make is [25:11] these aren't bound by reality in any way, right? There's no 3D. It's not like... It's pixels. It's not...

[25:19] a Feetian Coordinate plane or whatever. That's not the right thing, but it's not X, Z, Y, right? And so I think you can, [25:27] aid uh you know like you can aid the artist with these materials but at the end of the day you still have to like build the thing [25:34] perfectly. I think of it like it can't actually write the code for you. [25:38] yeah right like at the end of the day it's not going to actually write the code for you it can kind of give you like the rough like thumbnail of [25:45] The code, it can often work. Code is like very [25:48] deterministic. [25:50] But there's not enough data, at least right now, to be able to like... [25:53] build out like fully 3D. [25:55] you know [25:56] - That makes sense. - Or whatnot. But yeah, basically I would just like, I would kind of like take this and like build it out. And then I would, [26:03] uh, [26:04] It's just a way of, you know, at the end of the day, the decision is like buying the building or not, which it doesn't require AI at all, right? Like, [26:12] Um, it's just like deciding to invest money. [26:15] But the quality of the decisions [26:18] Uh, [26:19] should be much, much, much better. And I just look back at government and I'm like, man, if I was able to like, there's just like, you know, like we updated the pricing and the pricing was a better was so much better. And it took like 12 years into the business. [26:32] And if we had [26:34] hard to say what would have happened. But let's say this existed and I was able to make like this different pricing decision [26:41] Because certainly I would have asked Chad GPT, like, you know, the options, like, what should I, what's recommended? What are the other, what have other people done? What have price changed in the past and how were they received, blah, blah, blah, all these sorts of things. And let's say we've got to 10% flat, like much sooner. That's, it was about $70 million.

[26:56] in [26:57] profit margin over the last [26:59] since the life of the company basically. [27:02] Uh, [27:03] That's a lot. I mean, that's... But that's not, like... [27:05] You know, it's just a different decision. [27:07] Like it's a different number in one line. Yeah. Yeah. So that's why I think sometimes it's hard to like wrap your head and you won't see the impact of AI like you may never even talk to an AI. [27:18] But everything around you [27:22] is going to, like the materials, [27:24] I see this specifically in real estate development, like talking to people [27:28] Imagine when you're going to be able to source [27:31] Like I think every material is going to be sourced from like a much better quality supplier for a much cheaper price. Mm-hmm. [27:40] Because right now, imagine you just like most people just go on to like the single monopoly marketplace. Right. And it's just like listed on Alibaba Express or whatever. [27:48] And they buy like a pallet of [27:50] terracotta or something. But imagine if you had these AI agents that would like [27:56] scour the internet. Right. [27:58] for review, you know, and like, I think the, [28:01] the bar for [28:02] you know, for, for, [28:03] I mean, generally you already see this, right? I mean, like, just think about like, [28:06] I think the last Apple keynote was shot on an iPhone. [28:10] Yeah. [28:11] And the iPhone is like made of like something like 6,000 different [28:14] parts. [28:15] So imagine Apple to make something that amazing. Like it does have to research every single, you know, like they do do that. But imagine like that's a trillion dollar company. If like your Joe Schmoke coffee shop could make like 10x, 100x better,

[28:31] supplier decisions on the chairs that you sit in, on the upholstery, on the coffee [28:37] on the person making the coffee pots. [28:41] And I do, yeah, I don't know. I walk around and like, besides the news, like life does seem to be pretty nice, like pretty awesome stuff. [28:49] So I think these... [28:50] this is happening, you know? [28:52] Um... [28:54] Thank you. [28:55] But... [28:56] I think also the inertia of the existing system is also [29:00] mega massive. So you could generate like a trillion dollars in value and like [29:06] you're still competing with like... [29:07] a hundred trillion dollars in value. So it's like a 1% bump in the GDP, but that's like... [29:13] - Shoot. - Significantly. [29:16] I want to go back to the thing you talked about a little bit earlier, which is this decision to go flat. [29:23] um for for gumroad for flat pricing [29:26] Um... [29:27] which it sounds like [29:28] uh you know it's a huge sort of multi-million dollar decision for you over the last 10 years [29:33] And the idea that if you'd had ChatGPT, you might have made that decision a bit earlier. [29:39] How do you think about ChatGPT [29:41] in your decision making like when do you turn to it and what is the most useful way to [29:48] use it for that. And if you have specific chats that you've done that for, I know we've been talking about the building, but like if you have specific decisions that you've been making where you've gone back and forth with ChatGBT, it'd be really interesting to talk about that. [30:00] Thank you. [30:00] Um...

[30:02] Let me think. I mean, it's just like a constant hum of... [30:07] of stuff, you know, that I have. [30:09] If I'm like... [30:11] deciding where to eat you know i might like that's french toast place right or like [30:17] If I'm fact checking something, I might ask it something. [30:21] if I'm looking for something to do on the weekend, if I'm looking for like, [30:25] you know, people to... [30:26] like network with in New York. All sorts of like small [30:32] I mean, I don't I don't think there's any I mean, [30:37] The... [30:40] Thank you. [30:40] Yeah, I mean, I do think that there is like, it's not super useful, I think, for Gummer, because like the roadmap now is like there's so much in my head. [30:49] that like... [30:50] typing it out to tell you know chat gpt's like give it the context it's just not worth it so i think it's much better at like new [30:58] Yeah. [30:58] new stuff. [31:00] um [31:01] So yeah, I think it's mostly helpful for like, [31:05] for the first stuff that I'm thinking about, not stuff that I'm already doing. [31:11] Yeah, that's my guess. [31:14] I do use it in the government context. I do think it ends up replacing a lot of, like, I think one reason bad decisions are made is that you have a lot of people making the decision. [31:24] Right. So like. [31:25] the decision making kind of gets [31:27] It's sort of like the designer makes the design decisions, the engineer makes the engineering decision, and the car looks stupid. Like, it just...

[31:34] like it has to be kind of this collective thing um and i think [31:38] you [31:39] like this sort of empowers every single person to be like the PM, for example. Yeah. Like. [31:45] So the decisions ideally, like ideally, for example, the designer would often prior, like we're building flex out, it's like weird equity dividend complicated thing. [31:55] And before, people would have to hammer me with like, [31:58] How does equity work? Stock options, 4 and NA, exercise, track record, like all of these things. And that's every single person to explain it as a, to get it as like a, as a customer of the product. But then also like, if you're imagining you're designing it. [32:12] Right. You have all these questions too. And now you can just ask chat GPT and it'll just tell you. And so I think that also, I think the quality of the decision, not just by the CEO of the company, but by everybody. [32:22] helps a lot. It also means you need less people. So the pricing decision, I think, [32:27] For example, the more people you have, you're going to have people who are emotional. [32:30] and defend the [32:33] you know like oh no it's too expensive and like you know at the end of the day some decisions are hard to make [32:38] That's like the role of the CEO sometimes is like to make the hard decisions. Not necessarily like. [32:43] like you know surprising that it worked to a lot of people it's just like yeah [32:48] Oh, you did it. [32:49] Wow, that's hard. [32:51] You got to deal with some hate on Twitter or something. [32:55] So I think that also, like if you are relying on chat GPT, you get rid of the emotional component, right? Like the people. [33:02] saying like, oh no, like that's a bad, like, I mean, that might, maybe that still happens, right? Like every once in a while, AI safety, like it does like kind of,

[33:10] say like changing the pricing on your users might be a bad idea. You know, like it does stuff like that. But you know, it's better. It feels more objective. That's the other nice thing is like, I've, [33:20] I love it for fact checking my own biases because [33:25] It tells it like will tell me [33:31] For example, if I say like, [33:33] I have like some mental model in my head and I, but I always use like one example. [33:38] to explain the mental model, like one city per country, like New York City for the US or something. But if I go to ChadGPT and I say, [33:48] Tell me five, you know, like I just force it to improv and it only comes up with like the one example I have. [33:55] I'm like, okay, there's no good other examples. Like I should stop using this mental model. I need to like discard it in my. [34:01] decision making. [34:04] So I think that has helped. I think a lot of people, they want to make a decision, and then they justify it to themselves why they're making a decision. And it at least tells you, like, hey, you can still make that decision you want to make. [34:17] But that's not the reason you're making it. You're not making it because of this rational set of constraints. [34:23] You can codify and ask that GPT and it'll tell you like, [34:27] these don't align with your decision. It'll tell you like, [34:31] you should move to Dumbo because you're closest to Manhattan. The way you care about is you need to... [34:37] uh, [34:38] you know, commute to Manhattan or something. I have that too. I mean, one of the things I feel for myself is like,

[34:45] as a manager, as a leader of every, I'm just a little too opportunistic. I'll get really excited about a new idea and I'll kind of want to go in that direction. And I need to be a little bit more sort of strategic where I'm just like, okay, here are our quarterly goals. Let's make sure everything we do is... [35:04] like aligning with those goals. And I literally just have a thing in my custom instructions that's like, [35:09] Right now, one of the things I'm working on is I'm a little bit too opportunistic. I'm not being strategic enough. Here are our quarterly goals. [35:16] And so whenever I get excited about an idea, I'll always chat with ChatGPT because I think it's really interesting. And it's always like, hey, does this align with your quarterly goal? And I'm like, damn it, you're so right. It really helps keep me on track. [35:32] And just that slight little nudge does a lot for me. [35:37] Yeah, it's almost like a screen time reminder in a way. Where it's like, by the way, just reminding you, you have one core goal this quarter. [35:46] Yeah, that's kind of like just reminder, you're trying to buy a building. Does that goal or not? Yeah. I love that. Yeah. The other nice thing just to mention quickly is like you can empower your like certain people. Like let's say you have someone on your team who's like, oh, I really want to like explore this thing. [36:02] Sometimes you just have to like write in the prior world, you just say like, oh, let's like wait, like we don't have time or like, let's look at it that like next quarter or something. Because it would take like a lot of sort of time investment to figure out if it were actually worth doing or not. But now if it takes like, I can just say, hey, like spend five hours this quarter.

[36:21] Like just literally spend five hours talking to ChadGPT. [36:24] and like present, you know, whatever, like explore this problem as much as you can and then [36:29] The goal for the quarter will be just to evaluate [36:31] is this worth [36:33] And then, so sometimes it's nice because it clears everybody else's head too. [36:38] of the of these ideas that they may be like sitting on and like oh we should do this and that's like oh and it's like no [36:43] Just spend two hours, realize it's not that good of an idea or not, and then... [36:48] you know, [36:50] pursue it or not. So I find that also is like really like people have less excuses, right? Generally, across company when they have this tool, access to this sort of [37:00] this tool. [37:03] And I think Gumroad has product designers, software engineers, customer support people. [37:08] who also write all the help center copy. And like, that's like, I feel like fraud and risk review, [37:14] And that to me seems like [37:16] Why? Like every other role is like Chad GPT. [37:19] Mm-hmm. [37:20] you could just tell an engineer to use ChatGP to get the answer that they would need. We have lawyers and accountants, but they're both third-party lawyers. [37:28] um, [37:29] Yeah, I don't know. It feels like it just really, like, you just don't need as many roles, right? If something that used to take 40 hours a week, now it takes five hours a week. [37:38] You can kind of bundle all these roles into one person, often the CEO or the founding team or whatever will just do that. [37:43] Yeah. [37:44] So yeah, I think there's a lot of implications for like [37:48] the how these how companies like the size of the firm and like how come yeah

[37:52] stuff like that yeah I love that I mean I do think for every like [37:58] we are able to [38:00] go further with a smaller team than we would have before. And that feels just really, really exciting to me. [38:08] Um, [38:09] So, yeah, I think last question I have before we go, like, tell me more about the writing stuff. I know you showed us a little bit of writing stuff. [38:20] If you have any more examples of how you're using it for writing, I think that would be really interesting to go through. [38:27] Um... [38:29] Um, sure, yeah, I can see if I can... [38:33] So [38:34] Yeah, I mean, so this is like one idea is I was trying to figure out like, can I get, if I can really provide a really precise [38:42] thumbnail of what I'm trying to write. [38:44] Yeah, exactly. Like the. [38:47] the bits that, you know, even I was thinking of saying, like, use these three sentences and like, you know, so it provides them. [38:55] But anyway, I have this idea that there's sort of people who think in terms of logic and people who think in terms of rhetoric. And the example I wanted to use, so I would probably say, [39:06] use this example specifically logicians like this [39:14] Thank you. [39:16] Thank you. [39:18] Thank you. [39:20] Thank you. [39:21] Thank you. [39:22] uh,

[39:23] Doing good. Rat questions. Let me reply. [39:29] Thank you. [39:32] So it's kind of like basically like the way that you interpret the sentence. Mm-hmm. [39:36] Like if you think like how would an AI model work? [39:41] interpret this right like a logic someone who's like really logic based would be like okay clearly this is just like some weird [39:49] thing. Yeah. But [39:51] you know, I don't know, someone who's like maybe a little bit more like [39:55] caught up in the thing would be like, what the hell? Like, you know, something like that. Um, [40:00] So anyway, this is like, I think a good example. And I think it wrote something. It's funny because the format of Twitter has changed so much that it hasn't learned some stuff here, but. [40:09] and then you know I was like turning into a pithy essay like no I write but I attempted it um [40:18] So this is just an example of like, [40:21] you know is one better than the other trying to have a conversation with it [40:25] Yeah. So you have a little concept and you're sort of using this to help you refine and pull out like different ways to talk about the concept. [40:34] Exactly. Yeah. Like just, yeah, trying to spark [40:37] sort of sparked like basically I'm trying to figure out are there like [40:41] three or four interesting [40:43] little bits, right? That demand like little mini post on Facebook. [40:49] on X instead of just like a single tweet.

[40:53] Thank you. [40:53] Often, like, specific examples are, like, really what I'm looking for. [40:58] because I find that like, you know, it's kind of like, I think of it like a listening to like a really good Kanye West song, like to me, like, [41:06] He's a good... [41:07] He's like good at making music, but what's really interesting to me is how like he finds like crazy samples. [41:13] - Yeah. [41:14] And like he just kind of [41:16] highlights them. And so I think of it similarly. I'm trying to use ChatGP to be like, [41:21] Can I find a really good example? [41:24] that explains this topic. It's kind of like you read a book and everyone's site is the same. [41:28] examples for stuff. It's just like in the zeitgeist, like, oh yeah, 10,000 hours. The example is like, [41:34] uh, [41:36] I don't know, whatever it would be. [41:38] Yeah, anyway, trying to find the thing that... [41:42] people site actually like that becomes the thing people site yeah uh [41:46] Thank you. [41:47] um [41:48] So yeah, anyway, this is like what it would... [41:51] I would like it's certainly not good enough that I would I would definitely want to like spend like a couple of hours like [41:56] editing down. But my style of writing is really [42:00] Simple, which is like, I just edit down words. Like I just have a thing that's kind of like contains all of the ideas I want. And then I just spend like two hours, like. [42:11] do I need this word? Do I need this word? And like, eventually it gets down to something small. And then, you know, and so like, the ideas may already all be here. Then it's just a question of like, [42:21] you know, [42:22] Thank you. [42:22] trying to get... And I wonder even if you could say something like, re-above with...

[42:28] 90% of the words. And like, [42:32] you know, kind of recurse this. Right. [42:35] like keep asking it. [42:37] um, [42:38] Until it has left, like... [42:40] you know, as if you were looking for. It's probably not. It sounds like it's giving you sort of like, [42:46] Okay. [42:47] It avoids the blank page. It gives you some raw material to work with, and then you can rework what's there into something that feels like you and has new ideas that you might not have run into before, or new examples that you might not have run into before. [43:00] And that just makes the whole process a little faster and a little bit cleaner. But you're not like just typing a prompt and then tweeting whatever ChatGPT gives you. Yeah, exactly. Yeah. Like there's always... [43:13] Not that there's always going to be a need for that, but if you're trying to produce extraordinary stuff, you're always going to have a human in the loop, right? Because at the end of the day, it's like human plus AI versus AI. [43:26] Yeah. So like, [43:28] Humans will always [43:29] have something that they can add on top of AI. No matter how good AI gets, humans will be non-zero. [43:35] I think. [43:35] Maybe people will disagree with that. [43:39] Yeah, I think it's useful. Here's an example of this kind of thing, right, where I had an idea [43:46] I had like one example and I'm like, please come up with more. And then it didn't really come up with anything that [43:56] that compelling to me, so I didn't really have.

[43:58] doubled down on it. [44:00] or this one's another one. [44:02] Oh, yeah. This is another version of that. I really didn't get up, I guess. [44:06] uh, [44:07] This is more of a... [44:09] - Yeah, this is great. - This is great. - This is kind of like, another framing I often use is like, imagine I had like an employee [44:16] who's like dedicated to working on this project, what would I actually ask them to do? [44:20] Like what's the actual, like when you're doing it yourself, it's easy to like bullshit. Right. Right. But if you had someone like on payroll, [44:27] like what would they, what would they, you know? So I would basically ask them like, is this, you know, what renovations can I make to the building? [44:34] Like this would determine if it's worth buying. And it took me a while, like many days to realize like this is really [44:41] This is the question I really need to be able to answer that. [44:45] you know, um, [44:47] at least in the context of this specific building. But generally, this is what I realized, is I need to buy a historic landmark building [44:54] and renovate it. [44:57] that's at least my current thesis. So I love it. [45:00] And it actually tells you that it even like cited the, uh, [45:04] the URLs and stuff. So I need to go, you know, like read this, but it's like, it literally tells me exactly it's this one. [45:11] Rules, title 63. [45:13] Right. [45:14] And that would take like lots of lots of research or talking to people who are expensive or hard to get to to like find ordinarily. [45:22] Yeah, or just the possibility that it might, right? Like it could have been a Google search away, but it could have also been like,

[45:29] Because, you know, it's like some government document. Like you don't know. And a lot of people, I think... [45:34] they evaluate like the effort and then they just say it's not worth pursuing. Like the chance of this being a worthwhile project is so low. Yeah. But if you can tweak that risk reward ratio, maybe you can get it to a place where you're like, oh, actually it does make sense for me to spend like, [45:49] an hour. Like, yeah, [45:50] reading into this um [45:52] And then basically, at some point, I would hire someone [45:56] you know there's people that you hire that are basically like a [45:59] They just visit the site and then they do all the research and they give you a report [46:04] That's like, this is what you can do. [46:07] But like, they are happy to take your money to answer all the basic questions, right? Right. I want that piece of work to be as high quality as possible. I also think it holds me accountable to like, [46:19] do I really want to do this or not? Like it's easy to just, [46:22] spend 10 hours like [46:24] screwing around but if i'm actually trying to like like am i getting somewhere like is the quality of the idea improving [46:30] Right. Or am I just like [46:32] spinning my wheels. Um, [46:34] And I think that's another signal too. [46:36] Yeah. [46:37] This is great. I've learned a lot. I really appreciate you taking the time to do it. Yeah, you have so many good use cases for this. Thanks for sharing with us. [46:48] You're welcome. Thanks for letting me do it. Hopefully it was helpful. [46:51] It was great. [46:52] Cool, man. [46:52] Thank you.