His GPT Wrapper Has Half a Million Users—And Keeps Growing - Ep. 39 with Vicente Silveira

Everyone told Vicente Silveira that his startup—a GPT wrapper—would fail. Instead, one year later, it’s thriving—with about 500,000 registered users, nearly 3,000 paying subscribers, and over 2 million conversations in the GPT store. Vicente is the cofounder and CEO of AI PDF, a tool to help you summarize, chat with, and organize your PDF files. When OpenAI allowed users to upload documents to ChatGPT, the consensus was that his startup, and all the other GPT wrappers out there, were toast. Even when some of his competitors closed up shop, Vicente believed they could still create value for users as a specialized tool. The AI PDF team kept building. Today, AI PDF is one of the most popular AI-powered PDF readers in the world—and they did it with a five-person team and a friends-and-family funding round. I sat down with Vicente to understand, in granular detail, the success of AI PDF. Vicente explains how staying small and specialized is a key strategic advantage for his business. We get into why lean startups are better positioned than companies like OpenAI and Anthropic to create cutting-edge solutions for users, the role early adopters of technology play in shaping the market for new products, Vicente’s candid take on raising capital as a growing startup, and his thoughts on the emerging role of AI managers who will be responsible for overseeing AI agents. We demo an agent integrated into AI PDF, prompting it to analyze a bunch of recent articles from my column Chain of Thought and write a bulleted list of the core thesis statements—and even pit AI PDF against Perplexity live on the show. This is a must-watch for small teams building profitable companies at the bleeding edge of AI. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper Links to resources mentioned in the episode: Vicente Silveira: @vicentes AI PDF: https://myaidrive.com/ Dan’s piece on the allocation economy: https://every.to/chain-of-thought/the-knowledge-economy-is-over-welcome-to-the-allocation-economy

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  We're nailing the use case of getting a collection of documents that you have and being able to do end to end workflows with those documents.

• 0:07Dan Shipper?

  Can you go to this URL and download the articles and then create a document with the main ideas in those articles and express those main ideas as sentences? Write the text of the site into the files and then wow, interesting. Okay, so now we're getting some outputs.

• 0:34Dan Shipper?

  Sente, welcome to the show.

• 0:36Speaker 00

  Hey Dan, thank you for having me here.

• 0:38Dan Shipper?

  Thanks for coming on. So for people who don't know, you are the CEO of AI PDF. It's one of the biggest AI PDF readers in the world. You have about 500,000 registered users. And it's only been live since the end of last year. You've done over 2 million conversations in the GPT store. And you just started monetizing and you have about almost 3,000 paying subscribers. So it's a really, really cool business. And, and what I think is most interesting is there is this narrative, especially like in the sort of earlier days of AI, but I think it's still happening now, which is like, oh, like, yeah, all these like AI PDF companies are like, they're fucked and they're not going to do well and whatever.

• 1:19Dan Shipper?

  And I think you're actually building like a really interesting business and you're also part of this like broader wave of people who are making things in the, in this new AI economy with like really small lean teams. You run the company break even. Without raising a ton of money, I know you raised a friends and family round, but like you haven't raised a ton of VC. I think there's a lot of overlaps between the kinds of things that you're building and the kinds of things we're building internally at Everian. I just want to like, um, learn about how you're thinking about it. We can swap stories. We've done a lot of thinking too about fundraising and all that kind of stuff and how to build this, because I think. People assume, oh, you can't build a good business like this, but I think you can actually build like a sneaky, really, really great business this way. Small teams, especially with AI. So, um, yeah, tell us about, tell us about that. Tell us about your business and how you're thinking about running it.

• 2:05Speaker 00

  Yeah, it's funny you mentioned the, the whole rapper thing, right? We, we almost have like a, like a, a rapper death countdown, you know, clock, right? Which is like this many days since we, we died the last time that, that we keep track of. From, from time to time, we're pronounced dead, right? In reality, the business keeps growing. It's kind of interesting. At some point, it was when OpenAI for the first time, they allowed to upload PDFs to ChatGPT, right? It was like, oh, all this stuff is dead, right? Including some of our competitors actually just gave up during that time. But we kept plugging at it and, uh, and I think at, at some level, you know, this is an interesting industry because everyone is pointing at each other saying, you are a rapper, right? Just like, you know, I don't know if Nvidia is a rapper around math.

• 2:49Speaker 00

  Everything goes, goes from there. We started on, uh, on this because we tried different things, actually. When, uh, we first started, uh, when ChatGPT just was coming out and, uh, I was basically trying to do like prompt injection against, uh, ChatGPT and, and Sydney back then. And I found some stuff. I sent it to, uh, an email to Greg Brockman at OpenAI. And he replied, he's like, oh, that's kind of interesting. You should talk to this guy here, right? And at the time, I was actually still kind of like, I just, you know, got out of Meta and I was angry for that job at, uh, at OpenAI, right? I talked to this guy. He's like, oh, you know, you, you have an interesting background. You know, right now we're not hiring for this, maybe in a couple of months. So keep me in mind.

• 3:32Speaker 00

  And I'm like, well, maybe you can give me like an API key or let me into this new developer program. And that's how we started, right? And, and we tried different ideas, but the PDF one really took off, took off immediately. And, and reality is because, uh, this is one of the first things that people are trying to figure out with AI. It's a lot of pain around dealing with lots of documents and PDF is the, the, the main kind of document, uh, across platforms. So people just, just gravitated to that.

• 4:01Dan Shipper?

  That's really interesting. And so people, so people gravitated to that. And, and you know, you've said like, people have declared your death multiple times. I mean, if, if a PDF reader is in chat GPT, like, why are people using you?

• 4:14Speaker 00

  Yeah, yeah, great question. So the thing is, when we looked at this and we started building it, we actually at first, we didn't even have a place for people to upload PDFs, right? We just like, okay, you know, you can just give us a link and our server would go, go there and fetch the content. And because we were growing so fast at the time, people were giving us like Google Drive links and Dropbox links. And Google, Google and Dropbox started rate limiting our IPs, right? Because they saw us like as an aggressive bot. And, and this was a bad experience for our users because it would get an error. And we were like, well, you know, what we're gonna do? And we're like, well, I guess, we could try to play the cat and mouse game with those guys. But we, you know, we actually know how that works. And

• 4:59Speaker 00

  that would be kind of pretty bad. So like, well, what if we just let them upload their, their files? And we thought no one would do it, right? And so the first version of our website, my co-founder, Karthik, he was like, it looks scary. And to our surprise, like, in a week, that domain for our website became the number one domain for the links, you know, passing the Google domain and the Dropbox domain. So that was a lesson for us because he told us that the, the users that were gravitating to chat GPT, and they're going to all the trouble to enable plugins, that those people were actually risk takers and early adopters, right? So we built that for them. And then, kind of going back to your

• 5:40Speaker 00

  questions, like, why do they kept using us, even after this was created on, on chat GPT proper? It's because they don't want to just upload one file. When it works, they basically want to upload their whole collection of files. And even to this day, I think on chat GPT, you're limited to like 20 files, right? And for us, it's like, we have people with more than 150,000 files in one account. We have people with multi-level folders, right? No one else supports that kind of stuff. But it's important because people need that low friction and even respecting the intelligence they put in creating their folder structure to be part of, of this onboarding, right? So this is part of the, the product experience.

• 6:19Dan Shipper?

  That's interesting, but I wanna I wanna push you a little more. So like, it sounds like, you know, uh, one of the reasons people are still using you is because you're you're sort of staying one step ahead of what ChatGPT will do. Do you have a a theory about like, why they won't eventually do like a multi folder upload? Like an example might be uh, Notebook LM, where it's like, it it does let you, it does let you open a lot of files. Like, are you worried about that at all? Or is there some strategic reason why why you think um, you're gonna go deeper than a ChatGPT or like a Gemini or or whatever?

• 6:52Speaker 00

  Yeah, I mean, this is, this is interesting, right? Because I I feel like that these guys, uh, especially if you look at uh, ChatGPT, uh, their, their focus is to kind of race towards AGI and create a product that's uh, good enough to have enough usability there, uh, so that lots of people use, they can collect the training data and then feed their machine, right? I don't think they're going in into one particular specific direction. They're mostly kind of like touching on, kind of like, what is the minimum for core use cases, right? Um, so I think, you know, is it, is there a possibility that something like uh, ChatGPT or Claude or or something like that can actually compete with us and and and basically there's there's no need for this kind of platform?

• 7:37Speaker 00

  Yes, but that is always the question for startups when things start, right? So when you think about a startup like Loom, why the, why does Loom exist and was sold, I think, almost like a billion dollars to, uh, I think, uh, a classing. Uh, Loom is just recording video, right? But they did that use case so well, that, you know, even though YouTube had all the technology to do it, they didn't do it. Vimeo had technology to do it, they didn't do it. All of the major providers, they had the the technology, they didn't do it. But Loom actually nailed the use case. So for us, we're nailing the use case of getting a collection of of documents that you have and being able to do end to end uh workflows with those documents.

• 8:17Dan Shipper?

  Hmm, that's, that's really interesting. I I mean, I think it dovetails with some of the things that that I think about. Like, one of the things that I have in my mind when we build things internally at every. Is that ChatGPT and Claude, I think, like you said rightly, they're building for the most broad use cases possible. Like, they just want anyone to go on and be able to do whatever they want, basically. And it's sort of like, in that way, it's a little bit like Excel, where anyone can go to Excel and you have a blank, you know, blank new sheet full of lots of cells and you can just like, start typing numbers and anyone can do that.

• 8:55Dan Shipper?

  And then people are going to discover as they're using ChatGPT and Claude that

• 9:02Dan Shipper?

  that they have specific, more specific, like, they're going to discover use cases for themselves that they didn't know exist existed. So, for example, we have a, we have a product called Spiral that lets you automate a lot of creative work. Like, it helps you do headlines and come up with tweets and, and all this, all this kind of stuff. And, and that's a thing you can do with Claude. But Claude is not purpose-built for it.

• 9:24Speaker 00

  That's right.

• 9:25Dan Shipper?

  So our kind of like thesis is, people will discover use cases for AI and discover problems to solve with AI by using these more general purpose tools. And then that will create demand for other players to sort of peel off some of those use cases for particular kinds of people, for particular kinds of workflows. Like, for us, it's like marketers and creators who have like a, a very specific need for that kind of workflow. And, and having a product that's purpose-built is going to serve those people better. And I'm, I'm sort of curious for you, because a, a key part of my thesis there is like, you need to have a particular persona in order to like be powerful enough for that kind of workflow.

• 10:07Dan Shipper?

  But it sounds like you're, you're kind of going a, a, a level up, which is like more general.

• 10:14Dan Shipper?

  But do you have a particular persona in mind or like, how do you think about it?

• 10:17Speaker 00

  Yeah, that's, and, and I, we get this question quite a bit. And it's, uh, it is interesting because our. Our persona is an early adopter of technology, a risk taker, that has an actual job to be done involving lots of documents, right? So that's like, all of those things are important, right? So one is like, they're not just an early adopter, right? Because an early adopter, and a lot of actually ChatGPT and Claude use, is people that sign up to just see what's possible. They don't have an actual job they're gonna do there, but they they just wanna get that, you know, familiar with technology, be able to talk to someone about it, those kinds of things. So a lot of, a lot of that is, is that kind of use case.

• 11:00Speaker 00

  So that's, you know, one component of our user base. The other component of our user base is they have an actual job that they need to do, right? Today, and they have a lot of documents, right? So this is the combination of things that creates our, so like, who are these people, right? So we have like, uh, uh, there is a law firm, you know, the, the partner is an eighty year old lawyer, right? And he found us, he's like, I'm using this every day, and we're gonna have it within our firm, and a decision maker, I'm, we're gonna have it, you know, adopted here. And we have people that are like, uh, researchers, we have accountants, uh, we have writers. So there's a range of these different types of profiles,

• 11:45Speaker 00

  but what you find in common is that they bring a lot of documents, uh, to the platform, and they are basically trying to get some job done today, and, you know, they want to do this in the new way, which is the AI-first way. So, so that, that's one thing on the persona. The other thing that I want to kind of, uh, highlight is, we also differentiate from a platform like, uh, like Claude or, or ChatGPT in a way that I think They're not really going there, which is we're building this from the perspective of it is kind of like we're giving a cloud drive to an AI agent. Right? That's very different than you allow an AI agent to access some files.

• 12:31Speaker 00

  So what do I mean by that? And we can show you a little bit about that as well, but like the the agent that we have in AI Drive is capable of doing things like creating new files, updating metadata in files, kind of going through the file structure, right? So it's really kind of driving that effectively that that cloud drive to be able to accomplish a job for the user. Right? Because a lot of the job involves manipulating a lot of documents, right? So that's like another very important point, which I think it's not really the focus for these other platforms.

• 13:02Dan Shipper?

  Why do you think it's not the focus?

• 13:05Speaker 00

  Because I think it's not, it's not necessary to accomplish what they're trying to do. And it also introduces other types of considerations and risks that they may not be interested in dealing with. Right? So like this opens up our platform for for a Tinker type user, right? To be able to do things like, so think about this, so you have a, you know, chat history in something like a chat GPT. Right? But that's something that, you know, you can go there, you can look at the chat history. In our product, chat history is actually made of files that the the I can access those files on your behalf. And use the same tools like a search tool to be able to go into those kinds of files. Right? So these are all kind of like the same primitives that we're building on.

• 13:47Dan Shipper?

  So you're kind of like, one of your core users, you saw early adopters, but it's like, I mean, I'm thinking of myself like information nerds. I was like, ooh, your chats are files like that's amazing, like that's so cool. It's like feeding back into itself, but like that's a certain kind of nerd that like cares about that.

• 14:03Speaker 00

  I was just going to illustrate what you're saying. So you see like we have this little system folder here.

• 14:08Dan Shipper?

  So basically you're sharing AI PDF and it's it's called, the product is called in the actual product itself, it's called AI Drive. And basically you're showing me on the left, you have basically, it looks like you have a list of files. So it's like, that's your drive. It's like a Google Drive and then you have a chat window, which I assume allows you to sort of chat with those files, sort of like a notebook LM. And then on the right. It looks like there's a reader view where you can, for any particular file that you're talking to, you can also like see the PDF. Is that, that's basically what I'm looking at?

• 14:38Speaker 00

  Yes, that's right. And you can see like on the left side here, we have this kind of shortcuts here. So if I click on this little, uh, what looks like a clock, right? And you can see a history, right? So this is very similar that you have in chat GPT. There's, there's a history of the chats that you had today, right? And that's all you get in a typical platform. That's not really open for people that are like tech enthusiasts like, like you and in many others. But what, what that means for us is that we're building this. So if I go back to files, you can go and find these as files under the chat history folder. Right? So we're building these as basically kind of like an open platform where everything from your chats, uh, to, you know, and we're going to be adding memory. All of that will be basically just a file in the system.

• 15:24Dan Shipper?

  That's interesting. Um, I want to go back to what we were talking about earlier, like, so one persona is like information nerds like me. And maybe those that like cuts across lots of different industries, like there's probably information nerds who are lawyers or accountants. It doesn't seem like any of your marketing is like specifically about that, like your marketing is a lot more like general AI PDF stuff. How do you?

• 15:46Speaker 00

  Yeah. And we're flipping that because our, our, our trajectory is going through this transformation, right? So if you go back when we built this, and I think this is actually a good, uh, I, I give this advice to people when they're, when they're thinking about what they're going to do. It's like what we did with the plugin, that was the least effort thing that we could have done at the time, right? It's just like an API. At the time I had a server running on Replit, right? Replit's amazing. Uh, and that was everything. And we, with that, we discovered the market, right? But then at that point, we're just a plugin. So we couldn't operate independently, right?

• 16:26Dan Shipper?

  What do you mean by it was just a plugin?

• 16:27Speaker 00

  There was no web app, no place for you to create an account. We had no direct relationship with the user. So you would go to chat GPT, you would, you know, enable plugins, you would find us.

• 16:36Dan Shipper?

  I see. It was a chat GPT plugin. Okay. I just forgot about. That whole, that whole era.

• 16:43Speaker 00

  It wasn't that long ago, but it feels so, feels like that. Yeah, so like, so at that point, right, we, we were a product that only made sense as an add-on to ChatGPT, right? But what we realized is, is one, is that people needed an actual environment where they could do the work end to end, right? With the AI and the files, be able to verify the work of the files, which is another thing that we, you know, as you can see on the right side of our, you know, AI Drive screen, you have the actual files that, you know, are the source material. But beyond that, the other thing that we realized, and I think it will continue to be true for the foreseeable future, is because of this arms race between the, the main providers, right?

• 17:25Speaker 00

  So you can, you can, the, the ones that can play the game right now, probably, you know, Google, Anthropic, and OpenAI X, I guess, is coming up as well, uh, as a potential one. So you have maybe like four, four or five providers there that can actually provide unique capabilities when it comes to the models. And our users, because they are like you, right, and, and, and, you know, I, I, I heard you say in your podcast, you tried this on Claude or this on O1, right? They want to be able to have the latest and greatest. Now, if you're gonna upload your files to ChatGPT, and then tomorrow Claude is, has a better reasoning model, then now you get to upload your files to over there as well. So we bring that one place where, where you can use all the models combined. So that's the other aspect of that.

• 18:10Dan Shipper?

  That makes a lot of sense. I mean, it's funny, like, we do a lot of work with the companies where we're, we're, help them figure out what to use and, and, and sometimes train their, train their employees and that kind of thing. And I think mostly they're not in this category, like, they just, they're excited to see that ChatGPT added a new feature, but none of them have heard of Claude. They're like, what? Well, like, it's the best, like, it's whatever, you know, and, um, so, yeah, I think there is, there is that sort of separate, a different, it's, it's a different market. The early adopter market is a bit different for people who like really want to use the latest and greatest type thing. And I assume that, like I said earlier, like, that sort of cuts across industries and, and there's, there is room for that kind of like nerd.

• 18:52Dan Shipper?

  And what's a nerd as a customer, and, and what, what's interesting to me about how you're doing this is,

• 18:59Dan Shipper?

  You're kind of like, you're just taking the first step first. You're like, okay, cool. I'm gonna make a plugin. And then that starts working. And then you're like, okay, like now our customers really need like a place that's like different from the chat GPT form factor. So I'm gonna go build this other thing. And then now you're adding more features onto it and that kind of thing. Rather than I think there's this other approach, which is instead of getting to market like super quick, you kind of

• 19:25Dan Shipper?

  come up with an idea, you make a deck, you raise money, you start to recruit a team and you take like a year to like put this thing that's like your vision into the world. You know, and that's a, that's an alternative thing. I think that works too. And there are always trade offs, like a trade off that I'm seeing here in the way that you've built this is the product that you eventually

• 19:47Dan Shipper?

  ended up building is sufficiently different from where you started. That there's like always this like difference between what is public, like what the public marketing is about and how you talk about it and like where the, where the product is now. And you need to like constantly sort of like catch up. I've, I've sort of, I've experienced that a lot before. So that's one trade off where someone who just likes, just put the vision out into the world like singularly, like that's not their problem. Their problem is like, does anyone even want this?

• 20:17Dan Shipper?

  I'm just, yeah, I'm curious how you, how you came to that or like why that's your, that's your methodology.

• 20:23Speaker 00

  Yeah, I'm glad you asked this because I, and you were right, you know, there's different ways and I have other friends, founders, and they took these other paths, right?

• 20:36Speaker 00

  I think one is, you know, what, what works for you, right? And for us, this whole thing started as a side project. You know, with, with me and Carte, we're just like hacking over the weekend because we just love the, the stuff, right? That's one. But, um, but the other thing that I think about it now, and I think it's still a reality for us. Is that we are, even though we may feel like, oh, you know, AI is kind of already sort of happened, right? And we are so early in this AI cycle in, in the, in the ground and you, I'm sure you feel that way as well, Dennis, like.

• 21:10Speaker 00

  The the end, the steady state of this technology, or the productivity state of this technology, it's still not very clear what that's gonna look like, right? So, just just in this short time that we've been doing this stuff, you start with like, okay, you have these, first you had these these like specialized models, right? That people had in a bunch of companies. And we talked to, I just recently talked to a a company where they had a model for PDF extraction that they built on Watson and all of that. And then they tried it with, you know, GPT-4, and it just blew that thing that they worked on for years out of the water, right?

• 21:55Speaker 00

  So, so that that was like a big phase shift there, where a lot of people had like a rude awakening there. Uh, there's a great paper by Microsoft, when they they did a bake-off between the Microsoft PII, the private, you know, information detection model that was built over years with Microsoft resources. And they baked that against GPT-4, and it destroyed it, right? So, so that, so that was the first, the the big first phase shift. But the reality is that that continues to happen, right? So, we we build this thing, and you know, at first chat barely worked. Now chat works pretty well, right? And we have multimodal chat and all those kinds of things. And now, you know, the, if you look at what, you know,

• 22:37Speaker 00

  Sam Altman and a bunch of people building now are saying, building the the foundation, they're pointing to like, oh, the AIs are gonna become more and more capable, so they can take more of the task and become these agents, right? Where everyone's talking about this kind of, okay, we're gonna move to agents. So, the ground is shifting as we go along, right? We have something like computer use now. And so Claude did a little, right, a little demo of that. So what I mean by that is, by building this for

• 23:09Speaker 00

  An early adopter crowd with an actual problem to solve, right? They have day jobs, that's very important, right? We are actually capable of tracking the evolution of this market, right? So that we don't get stuck on a kind of like a early internet type, type thing like, oh, there was ICQ. There was, you know, a bunch of different things that eventually became irrelevant. Once you got into the productivity state. So, so in a way, it's like for us, doing this is a little bit also, it's both strategic and also defensive as well.

• 23:43Dan Shipper?

  Well, let me unpack a little bit of what you said, because the question I'd ask is sort of like that tinker mentality where you're, you're going out and you're just building like the thing and you're getting to market super quick. And it sounds like what you're saying is that by serving an early adopter market, you'll be able to, and you're incentivized to kind of like keep up with the latest and greatest so that you don't get left behind. How do you bridge the two? How do you bridge the gap between the two? Like, what's the bridge from how you got to market to not being left behind because you're serving early adopters?

• 24:15Speaker 00

  Yeah, I think, I, I think the early adopter, what they give to you is some leeway to experiment more, right? So for example, we now introduced the agent into our product. Before, if you look at our product, right? And it's still there, so that's the main way. You can see this menu, right? And basically I clicked on this menu in the chat prompt and you have the models from the main families here on Tropic OpenAI and, and Google Gemini. So you can just go into this and just do a regular chat, which most users, that's what they are, they're used to. But then we have our kind of like, the users are pushing us forward. They want to go into the agent and be able to do more of that task, right?

• 24:56Speaker 00

  So we're trying to basically work with the core of our early adopter users and also listen to the ones already moving forward to the next thing. And what this early adopter users, what they give you is more tolerance for the experimentation. Because of course, and something like an agent today still doesn't work great, right? You, you may have a moment where it's like amazing and you, and the next run that you do, it may not, it may get stuck, right? But they actually want to see where that thing is going. So that's why these types of users, they help us kind of like bring the, both like the main use case and the leading use case at the same time forward.

• 25:39Dan Shipper?

  I think this is like an important related point to kind of this competitive thing that we've been unpacking together. Like, how do you compete if you're like a two-person team, or I don't know how big you are, but we're eight, we're eight people. So like, how do you compete where, you know, against OpenAI or Google or Notion, whatever.

• 25:57Dan Shipper?

  And I think like, the, the thing that comes to mind for me that I, that I think you're saying, which I think is true for us as well, is, um, people forget that when you're a big company, you have to serve a lot of users. It's really hard to take risks. And for a while, there was this like, feeling about AI where it was like, well, the AI is gonna be smart enough that it's never gonna make mistakes. So like, uh, big companies are gonna be able to do anything that startups can do. And I was always just like, no, big companies like always find a way to fuck things up. Um, it's, it's just like, it just, it's not because they're not smart. It's just innovators, all that stuff. It's basic stuff that you just like, can't take risks. And, and I think like, I think that's why, when you look at a lot of the AI stuff,

• 26:42Dan Shipper?

  um, like, for example, and I won't name names, because I don't, I don't like shitting on people directly. But, um, for example, I, I got a fitness tracker app recently, and I, it's really great. Like, I love actually the way it works and, and the app and whatever, but like, they have an AI feature in it. And the AI is just like, it's so milquetoast, like, it just like, doesn't say anything useful, basically. It's like, and the reason is, they have to, they have to make it work for like, the lowest common denominator user. They have to make it not confusing, and they don't wanna take any risks, because they're like a big company. And it would, it would be bad if it said something that was risky. Um, which makes a lot of sense, but it means that the experiences you're able to do as a bigger company are, are less good

• 27:25Dan Shipper?

  in a lot of ways than the experiences that you can do as like, as a small company, that you can just like, decide, okay, yeah, we're gonna serve these users that like, don't care if there are rough edges, and we're gonna like, explore on the boundaries of what's possible, and our users are gonna understand if we return a result that's like, not so great, and that allows us to experiment. And they understand, because they're, they're like, want the greater power, and they understand that there's a trade-off there. Which I think, I think that's really important. I think people miss that all the time.

• 27:51Speaker 00

  Yeah, I think that's totally true. The only reason why startups have a, a, a shot at anything, it's, it's because there is, there is some

• 28:01Speaker 00

  I guess core vulnerability to establish business and usually that is their customers. Right. So the thing that makes them powerful is that they have lots of customers. It's the same thing that makes it hard for them to take risks with those customers. Right. So if you think about, you know, the mainstream products, you take a spreadsheet product. Right. A product like that, there's a lot of investment that was done on a ton of features and training of users. I mean, they actually have, you know, certification courses for their users. Their user base goes there day in and day out, expecting a certain experience. They also want to know that there's some AI on the side and you can put some AI on the side that they do sprinkle AI everywhere.

• 28:45Speaker 00

  But to radically change that experience to be something like, oh, it's going to be AI first. You're not going to go, you know, click the buttons, you're going to tell an agent to go do for that for you. And that's going to be the core of the experience, no distracting anything. That is the change that is just too radical, you know, typically for the incumbents to be able to do. So that's why you have the opportunity for, for, you know, a startup like, like yours and ours to come in and introduce a new way of doing things, which I think is part of what we're trying to do, which is what is going to be the new way of doing things, right? And we feel like it's a lot more, like we have this, this analogy here.

• 29:28Speaker 00

  So you just think like how a very wealthy person operates, right? They, they operate through intelligent agents, right? People that they hire, they're very smart, they learn everything about them and they operate all the complexity, you know, behind them, right? And so that's kind of, kind of like where we think things are going with AI. Of course, right now it's, it's too far from that, but we will approach and get very close to that. So this opportunity to build for the new experience, I think is, is leaning into that, right? It's very important.

• 30:01Dan Shipper?

  I totally agree. Um, I think that that metaphor is so powerful. It's something that I I've written about a lot and I thought about a lot is like. If you want to know where things are going with agents, like, yeah, people have been hiring agents for a long time. Um, and they're they're solving problems that uh with these agents that like, there's a lot of overlap with what AI is going to be able to do. And maybe you can do new things with AI that you couldn't do with like hiring a personal assistant or whatever, but like. There's a lot there that you can just like kind of carry over, like even for me, you know, I I I run a media company and. Um, I employ a lot of people like, you know, editors and writers that help and designers that.

• 30:43Dan Shipper?

  Um, help me do things at a high level frequently all the time. You know, this YouTube video is going to be edited and it's going to have. You know, it's going to have an intro sequence and it's going to have a thumbnail and all that kind of stuff. And I can do that because the company is successful enough that I can hire those people. But it took me a long time to get to a scale where I could do that. And I think. Um, if you want to understand, for example, where the future of media is going, it's. It's not that teams of creatives are going away. It's just that an individual creator is going to be able to do a lot of the things I have to hire people to do. Like on day one. Um, and you know, I'll still have lots of people doing stuff. I'll just be doing it at a higher scale because. The people that are editing my videos can edit twice as many videos or whatever.

• 31:29Dan Shipper?

  Yeah, I think that that's I think that's a really good place to look for ideas. It's like. If you want to understand how people are going to run their calendars or their emails or whatever, just like look at how people with assistants do it. Um. Uh, so that's definitely a metaphor that that we use a lot internally. I'm curious for you, like you you raised only a a friends and family around. I assume with the kind of traction you have, you could have gone and raised a venture round. Uh, why didn't you do it?

• 31:56Speaker 00

  Yeah, I think first our experience raising was kind of very interesting, right? The beginning was like, oh, this is amazing. We're just gonna be, you know, we're gonna raise a ton of money now and maybe we should raise more. But the beginning was fast and the process then later started dragging along, right? And I felt like I was, you know, back working at Meta, doing PowerPoints and tweaking PowerPoints and prepping with a friend, you know, a friendly VC to to talk to another one. And when we had users who were basically asking us to do stuff, and at the time it was just Kartik and I, right? So I'm like, I I'm hating this, right? And if we if we can just go and monetize, let's just do that, right? And then we'll come back.

• 32:40Speaker 00

  So I think that was the that was the main reason. And it was a time as well where with AI, the the whole kind of like hangover of the first wave of investments was what set in, right? So people were really worried about this. It was a time also for us product wise that, you know, the product was very much dependent on OpenAI and ChatGPT specifically, right? Which is not the case now anymore. So for those reasons, we're like, yeah, let's just focus on the product, which I think was the right, the right thing to do.

• 33:11Dan Shipper?

  That's interesting. Do you think you might raise again in the future or like what's what's the path look like for you?

• 33:17Speaker 00

  Yeah, I think so. I I think the reason is we want to be very careful in in.

• 33:26Speaker 00

  I guess diligent about when when we do it, why we're doing, right? And and how did how we're gonna use the the capital that that gets invested? And and this is one of those things where kind of going back to how many, how many people, how much softer? That's the other question. A startup is gonna need moving forward. And we think it's actually less than what has traditionally in the last, you know, five to 10 years been, right? So we want to make sure we we do it right so that we we're not like.

• 34:00Speaker 00

  Sometimes, you know, and I hear that, I think Bill Gurley famously said that is companies raise money and that because they have that money, then they end up becoming more complacent, right? So that's one thing that for now, we want to make sure we don't do. But, but yes, I think once, once we know like, okay, this is gonna allow us to grow in this, this direction. Uh, it will make sense, right? I think the other thing that I want to, you know, maybe touch between this point and the previous one. On um, how both the experiences difference, but also how you end up saving money, right? If you just lean in is, so we think about like, let's say a job, like onboarding on our product. When you sign up for our product, our onboarding sucks, your onboarding is beautiful.

• 34:45Speaker 00

  I, I did this spiral one, it's beautiful.

• 34:48Dan Shipper?

  Thank you.

• 34:49Speaker 00

  Yeah, I, I love it. Our sucks, right? And uh, we're like, okay, we need to make our onboarding better. Um, I do think that the way I want to do that is basically give an AI a job to do that onboarding of that user, right? So what does that mean to us is like, instead of having sort of a either a product that we attach to our, our app that will kind of be configured for that onboarding in some way? Or, or build that ourselves, we are going to basically lend you an agent, right? That knows about the product, knows where you came from. Oh, you know, we have a landing page for lawyers, right?

• 35:32Speaker 00

  You came from the landing page for lawyers, so you're likely a lawyer. Um, hey, you know, this is what the product does. Uh, do you want to, you know, upload one of your files and we can, I can show you what, what it can do for you? And it basically give that AI a job. And what we want to do is, so we have a person that we just hired that is gonna be responsible for this area. So that person's job. The person, the actual human that we hire is to basically manage that little agent, right, and be responsible for the delivery that that little agent does, right? And of course, as the agent gets better, there will be more and more that it will be able to do.

• 36:12Speaker 00

  So it's kind of an interesting way to think about these things where we feel like that as we hire people, they will end up be responsible for certain agents on the product that have specific jobs for the user and for the company as well.

• 36:28Dan Shipper?

  I love that. I think that makes a lot of sense. Like, I've been writing a lot about, you know, what I've been calling the allocation economy, and I think this is like right on that, on that train, which is like, in an allocation economy, you're, instead of doing a lot of the IC work, you're, you're, you're doing a lot of more management work, where you're managing the allocation of intelligence, managing agents, and and in that world, like, the skills of managers become more important than they are now, and they need to be more widely distributed. So I think, I think that makes a lot of sense. That's really interesting. I'm curious for you, do you have any sense, like quantifiable sense of, you, you said earlier, the things you can get done with a smaller team with less capital,

• 37:13Dan Shipper?

  you can get a lot more done now. Do you have any quantifiable sense of what that is versus like 10 or 15 years ago?

• 37:20Speaker 00

  Oh, for sure. And, and you can see this everywhere, right? And I can give an example, like, working at Meta, right? Of course, Meta has a ton of money, right? And pre-gen AI, and, and now they're deploying it very aggressively internally as, as I hear from, from the outside. But pre-gen AI, you would have things like a product manager, and I was a product manager there. They would want to know, like, okay, you know, what's going on with this particular feature? What are the, the top issues that our customers are having in this particular, you know, area? And so you would, the PM would basically talk to a person in the support area, which their job was only to go collate all this feedback and create this report.

• 38:04Speaker 00

  And it would take like maybe a, a day, or, you know, if they're busy, maybe a little bit more, depending on how priority is your problem, how much of a priority. So all of that now, right? It's like you can get done with with AI. That's that's just there, right? You can you can get directly with AI. So that's just one example of how with the tools that we have now, we should be able to be a lot more efficient and do things that would only be available to to larger companies.

• 38:33Dan Shipper?

  Yeah, I think that's true. I mean, we see some of the apps that we work on internally, like I can see someone take something from zero to it's a fully finished product that would have taken a year and they can do it in like two or three months if they're good and they're they have a whole general skill set and we have a bunch of support for them and all that kind of stuff, but it's it is kind of wild and I think I probably have a particular like anti VC bias or I've been historically hesitant to raise. We raised a little bit point twenty, raised like seven hundred K and we raised a little bit more recently, but it was like hundred fifty K. It's like amounts where it's like a VC would like laugh at it and be like, what are you going to do with that? And for me, I'm like, we've raised less than a million bucks. And if you look at the number of products we've built, there's a lot of there's a couple

• 39:18Dan Shipper?

  of products and companies that have come out of just that one raise and I think we'll in a year we'll have a bunch more. And I think about raising capital and why you do that. It's, you know, if you if you spend a couple of months raising theoretically, you can hire more people and spend more on growth so that you can pull forward the progress that you would have made over the next year and maybe make that progress in like three months or whatever. And I think that that equation, it's still there, but it's different. Like it's the amount that you can get done is you basically have gotten a lot of that pull forward effect from just like properly using AI, which is really interesting.

• 40:03Dan Shipper?

  And of course, everyone else has that. So to some degree, like having extra capital can help, but capital has always been capital has been pretty available for technical teams and whatever. And I think it's rarer to actually be using AI well than it is to like get capital in certain areas, like some people have a very difficult time getting capital and that's a whole different problem. But if you're like a technical Solcandali-ish team, I think a lot of those people are. Just feel like they don't use AI that much in their daily work because they're like, oh, I'm better at it. Or I'm better than the AI or whatever. I think that's changing a lot. And people that have like really gone headfirst into it are quite a bit more productive.

• 40:44Speaker 00

  Yeah, and and for us, it's like productivity at all levels, right? So I I have a software engineering background. I coded like early in my career. And then I stopped, pretty much went to the business side. I thought I was never going to be able to code again. And when this came back with Gen AI, he was like, he was kind of, you know, you can't mount them bike anymore because you can't go up the mountain. Now you have an electric bike and, you know, up you go, right? It was incredible. And and then, as I say, I have like two two mentors. One is, you know, AI, the other one is my co-founder. And I see that even for him, kind of world-class engineer, you know, former Google AI.

• 41:28Speaker 00

  He makes him so much more productive. So it's like everyone goes up like for whatever level you are at, you become a lot more capable. So that's that's absolutely true. And we think that there is a huge lack of awareness overall in the population. I think some of this is, and I like your show because it helps spread the word, which is AI is actually for everyone, right? Like, people are like, if you just follow, I think, the more mainstream media, you think that, well, one AI is going to kill you. But if it doesn't kill you, then it's gonna, you know, take your jobs. And by the way, the rich will get richer. So so you end up like, what kind of message is that? What does that do to the population, right?

• 42:12Speaker 00

  Everyone gets demotivated. You take agency out of people. On in reality, you have the opposite. You talked about like this, this like learning to be a manager. Well, if you if you have access to an AI, you're practicing being a manager. If you have a phone, you have access to AI. So you can you can start like specifying a task. The AI doesn't do what you want. You're like, hmm. Well, actually, my question wasn't good enough. That's a lot of what being a manager is. So you get your your prompt, your question better. Now you have to look at the result, what the AI brought back. Is this quality good? Am I willing to put my name on this thing, right, that the AI came up with? So so, yeah.

• 42:51Dan Shipper?

  I think I think that makes a lot of sense. I mean, you know, obviously, there's a lot of difficult social and economic issues to like, you know, broad AI rollouts. But I I do think that point is totally right is people tend to miss how powerful this is as as an immediate upskill for lots of people. Like even people we have internally where, you know, for example, if English is their second language, like maybe they speak fluent English, but their writing of English was like not as good. And you could tell and that limits their ability to like get hired or get promoted or do certain jobs. And like the minute chat GPT came out, it was like a total shift, you know, they could immediately write like fluent English.

• 43:31Dan Shipper?

  And that level of opportunity like it just opens up that they was was not available before and they didn't have to do anything. Um, and I do think that that's that's one of the things I would love to do with this show is show people the easy sort of ways that they can get started and also like where the what the most interesting or smartest or furthest ahead people are doing. So that we can like bring forward like everyone else to use it. Cause yeah, I think um, hopefully raising the floor like creates a lot more economic opportunities for people. And and I love that you have this like tutor in your pocket that I would have just talked to chat GPT all day if I was like eleven or whatever.

• 44:14Dan Shipper?

  And and I think we're kind of lucky. You you know, there's a lot of concern about AI companies like racing ahead and releasing it to public before it's ready and all that kind of stuff. I think on the other end of the scale, we're kind of lucky that we live in a world where um all these companies are trying to make it as cheap as possible for everyone to use. Uh, like there's an alternative timeline where it's like IBM invented this and like only like the DOD gets access for the first like fifteen years. And um, like that would suck.

• 44:49Dan Shipper?

  I don't know, you know, like I could I could imagine a lot of things being written the other way where it's like, well, only like rich, big companies get access to this like crazy intelligence and I'd rather just like have it have everyone if we have to pick. I'd rather I'd rather this world, I think um to to some degree, I don't know, I'm at this point, I'm like, I'm totally off what we usually talk about in this show, but I think it's I think it's really interesting and important.

• 45:14Speaker 00

  Yeah, I I think you're totally right and uh or you're in Europe, right? And there's still

• 45:19Dan Shipper?

  Yeah.

• 45:20Speaker 00

  I hope uh that a lot of people get to see this, right? Because uh uh it's the first time that I see uh and I've seen these other, you know, tech revolutions where most people already equipped to be able to use it, right? So before it's like with, you know, the the microcomputer was super expensive, you know, I I actually grew up in Brazil. We couldn't get it.

• 45:45Speaker 00

  And and we we had to basically smuggle parts and and kind of build Frankenstein computers there.

• 45:52Speaker 00

  And, you know, even with cell phones when they came out, right? It took time until people had access. Then the networks were not good, right? And then now we get this thing that, you know, if you can get whatever social media uh on your phone, you can get AI. AI actually works better because, you know, most of it is is lower bandwidth. So that works well. And I I think, you know, for for us is is what we see as we go into this kind of like this direction of from just conversations with AIs, right? The I ask a question, it gives me an answer, right? Which is the initial like with chat to, you know, moving to agents, which is I give it a task and he executes, you know, that task for me is

• 46:35Speaker 00

  is this evolution of possibilities that you can that you can have, right? It's like one of the things that we spend a lot of time now is building tools for the agent, right? And it's kind of super interesting because you start to think about like is is my tool good? Right? Is like is is the tool self-explanatory? And does it do what it's expected to do, right? And so you have that that second that second level there and and all of this is is opportunity because if you think about Like people say, well, you know, when the AIs do everything, then there's nothing to be done, right? But again, if you use the rich, you know, wealthy person metaphor, you can be very rich and you can hire a bunch of people to create a company to do something.

• 47:19Speaker 00

  But mo-most of the time, that doesn't work, right? Because it takes, you know, leadership and talent and some vision and some grit there to be able to organize these human agents, right? Into a, into a company that actually succeeds. And I think same thing will play out with, with the agents, right?

• 47:41Dan Shipper?

  You're so right. Like, I was, I'm, I'm literally like writing an article about this today, but like, it's, it's like this, there's this weird fallacy where people are like, well, agents are gonna be doing it, so you won't have to think about it. And I'm like, have you ever managed a person who is literally a, a, a general intelligence? Like, they are really, people are very smart, you know? It's hard. It's really hard. Um, and it's, it for sure is like a different kind of thing than, um, doing it yourself. But, uh, even if someone else is doing it, like the skill of delegating, like the, like going from, there's this thing that early managers, you have to figure out, it's like, okay, uh, how much do I delegate and how much do I micromanage?

• 48:24Dan Shipper?

  Cause if I, if I micromanage, it'll get done the way I want it to get done. But if I delegate, uh, but, but then I have no leverage and I'm like, just basically doing their job for them. So why did I hire them? But if I, if I delegate, then I have more time to do other things or think at a higher level. But, uh, it comes back wrong. And that's like literally the, the problem that a lot of people are having with AI right now is they're like, oh, it sucks or whatever. I have to do, I, I could just do it quicker myself. And I'm like, that's exactly what managers face. And, and so a world where, oh, we have these cool, let's say it's AGI, like really cool agents that do all this stuff. I still think there's a lot of. You're skipping a lot of invisible things that have to be done to like

• 49:06Dan Shipper?

  scope the task and pick the right resource and like have the taste and vision to be like this is what I want done in the world. And I don't, I don't think like, okay, maybe we'll get to a point where even they're doing even that, but then there's, there's a lot of stuff that is sort of invisible in an AGI type scenario, or even before AGI, just like intelligent agent scenario, where there's a, there's a lot of skill and talent that needs to be directing them. And I think you're pointing to that.

• 49:34Speaker 00

  Yeah, we actually think a lot about delegation. I can show you something cool.

• 49:39Dan Shipper?

  I would love to, because I think that there's a lot of talk about like agents and, and, and there's a lot of stuff happening, but I don't, I haven't seen anything like really compelling yet. Like we had, we had Yohei on last week, and I think he's got a lot of cool stuff with, with, with Baby AGI, but he's like, I think a lot of that is still like pretty prototype-y and experimental. So I'm, yeah, I'm really curious to see what you guys are working on.

• 50:01Speaker 00

  Yeah, let me show you some, that's just kind of a, and this is a live demo here, so anything can help. So, okay, I did download a few of your posts. I think the context window series of articles, right?

• 50:14Dan Shipper?

  So I just want to set the scene for people. So basically we're back, we're back in AI Drive. We've got the same kind of three column layout, which is like, we've got a, you know, a folder structure on the left. We've got a chat in the middle, and then we've got an open PDF on the right. And you've downloaded some every articles, some from context window, which is our Sunday digest that goes out every Sunday. And you're typing into the chat and I'll read what you type after you're done typing it.

• 50:43Speaker 00

  Yeah, so I'm just here in AI Drive and I'm just typing this, you know, prompt. Hi, I'm talking to Dan Shipper, so I'm writing this to the AI, which is our agent in AI Drive. And he has a series of blogs, context window in the folder, and then I'm pointing it to which folder I have downloaded it.

• 51:05Speaker 00

  Can you read them all and suggest some interesting talking point or conversation starters?

• 51:18Speaker 00

  For us, and I'm gonna use this thing here too as well, which is use the expert to plan, right? So this is one delegation to, so the reason, and I'm gonna fire this up as I explain. So now it's kind of processing. And if you click, you can see what it's actually doing. So first thing it's doing is getting a tool plan from the expert model. So the main agent you're talking to here is GPT-4O, which is great, but it's actually not the smartest at planning. So what we do is, we allow this agent to delegate to an expert in planning, which can be O1, which is great. Or it can be the latest Claude, which is also very good. And you can see this here, right?

• 51:59Speaker 00

  It says, oh, you know, this is the task, I need to read all the blogs here, give me a plan, and then you get a plan back. And yeah, so now it's outputting the conversation starters, right? So as you can see, let me just collapse here so we can look at all the tools that were used. So the first thing that it did is get the plan from the expert, right? Then with the plan, it went about executing it, which is, okay, let me take a look in Drive at what's in, you know, in, in, in the folders and files. So it went into the context window folder, just to see which files were there. Okay, great. So now, because, and this is one of the things that you have to do with AIs, is that each AI has an amount of context window

• 52:40Speaker 00

  or, you know, working memory that it can work with, and you have to work around that, right? So here, this particular model, GPT-4, that family doesn't have that big of a context window. So in this case here, we basically tell it like, okay, you're gonna delegate the task of reading these files, right? So it went ahead and said, okay, go into this folder and extract the key arguments, unique insights, personal anecdotes, blah, blah, blah. For, and organize this as a conversation starters. So, and then you have the output here, which, you know, it brought back into the chat. So, and then we have here, I don't know, app integration to ChatGPT.

• 53:20Speaker 00

  So there's like some interesting conversation starters here about the app integration there. So this is just to show like how in one chat now with a smart agent, you can actually have two delegations that are happening to get that task done.

• 53:37Dan Shipper?

  I get it. I think that's interesting. So which articles have you downloaded?

• 53:41Speaker 00

  We can go, we can go take a look. So here, and I'm going to drive into the folder for context window. It's the Apple took the stage for WWDC, Blue Sky Thinking, Creator Led Businesses, Generative Thinking, Spiraling Auto Control, and your AI Research Assistant.

• 54:00Dan Shipper?

  Because one of the, one of the tasks, and we can try it on this. I don't know if it'll work. But one of the tasks I really want to do, and I don't think these models are capable of it yet, which is putting everything in the context window is I want to create like a list of all of the like thesis statements or all of the ideas that were like, like, you know, for example, I have this allocation economy idea. That's like an ongoing thread that I write about, and I really want to create like a list of all those threads. Just to like have, so I can, you know, refer back to them. And this seems a good thing to do that with. Do you think we could try and see if it can pull out things like that?

• 54:36Speaker 00

  Let's give it a shot. So where do you start from? Where is the information?

• 54:40Dan Shipper?

  I would go into Chain of Thought, which is my specific column on every. It would be every.to slash chain dash of dash thought and download.

• 54:50Speaker 00

  Let's, let's try one thing real quick here. Can you go to every dot is dot TO?

• 54:58Dan Shipper?

  To, yeah. Last chain, chain dash of dash thought.

• 55:03Speaker 00

  If I did chain of thought.

• 55:09Speaker 00

  Just to make sure this is the website here. And chain of thought column URL. And so we are starting to introduce. Yeah. So we're going on the web, right? So we're using a tool that is a fetch URL content. So it's going at this every.to. So Dan's website. And let's see if it's going to find the right URL. Well, apparently we found something here.

• 55:37Speaker 00

  Oh, it's actually going into AI Drive because we may have downloaded something. So this is one of the interesting things you see with, with the tool, right? It's a tool to go out to fetch URLs, but even files here on AI Drive are URLs itself. So he went there. Let's see what he did. Oh, okay, there's some issue here. Let me try another approach. That's one of the cool things about the agents, right? Is that they kind of work around issues. And the more tools you give, if there's some overlap between the tools, they can actually find work around. So let's see what he did. So he went for fetching URL again. Oh, he found it.

• 56:17Dan Shipper?

  Uh, that's awesome. Uh, so what I wanted to do is, uh, there's a, there's a place, there's a way to sort it by newest. Um, and so I would like it to just, uh, sort by newest and, you know, take our, the last, I don't know, all the articles that are on the first page of newest and tell me like, okay, what are, what is the, what are the main ideas? Um, of each article as, as bullet points.

• 56:45Speaker 00

  Okay, we can give it a quick shot here. So you want the, the latest articles there?

• 56:49Dan Shipper?

  Yeah, so basically there's a, there's a, it's a new URL. So I'll just send you the URL just to make it a little bit easier. It's just a parameter where you just sort by newest.

• 56:57Speaker 00

  Got it, okay.

• 57:00Dan Shipper?

  So basically I wanted to go to that URL. I wanted to go to article in the URL and pull out the main idea of the article and express it as a sentence. Um, and then give me a bulleted list of the main ideas.

• 57:19Dan Shipper?

  Can you go to this URL, um, which is the chain of thought URL and download the articles? Um, and then create a document with the main ideas in those articles and express those main ideas as sentences. Use the experts to plan your, expert to plan your task. So it's basically like going to the expert model, which is, I guess, oh, one.

• 57:35Speaker 00

  Yeah, right now it's Claude.

• 57:36Dan Shipper?

  And Claude's basically like creating a plan. Uh, so it's writing a plan for the, for the other, um, AI to follow. Um, and it's, you know, giving it some, you know, things like it's gonna fetch the URL content and write to the file. And, uh, you know, all that kind of stuff. It's telling it, okay, here's some things to like watch out for. And now it's starting to take action. So we're starting to see it, I think, um, go to the, go to the site, um, and then write the files into, into another file. So write this, write the text of the site into the files. Um, and then wow, interesting. Okay. So now we're getting, now we're getting some output. So the first one is how to figure out what people want is the article title. Understanding customer needs involves thinking in sequences. That's right.

• 58:19Dan Shipper?

  OpenAI launches a document and code editor. And the main idea is canvas enhances human AI collaboration by allowing real time document code editing. This is cool. Yeah, this is actually, uh, quite helpful. I, I think you may have converted me.

• 58:36Dan Shipper?

  This is, this is definitely different than I think the experience, for example, like one of my problems with notebook LM, for example, is I have to like go do all this manually, um, like uploading all the stuff manually. And it's really nice to, uh, uh, to have it just be able to fetch it for me. And I think the other, the other thing that's nice is like, yeah, there's some more complex workflows you can build here that is helpful for text processing. I, I like this. This is cool.

• 59:06Speaker 00

  Yeah. Uh, what we find is, uh, it's kind of interesting if you think about the evolution of these things, right? Uh, something like if you do a Google search, uh, you can do something like this in Google search because usually Google searches are optimized for like maybe two words. I, I think that the, uh, even perplexed, do you want to try this in perplexity?

• 59:23Dan Shipper?

  Sure.

• 59:24Speaker 00

  Yeah, let's try that. Let's do a quick bake off here.

• 59:29Speaker 00

  Yeah, I'm gonna get the exact same prompt to be fair.

• 59:34Speaker 00

  Well, I mean, might as well, right? Um, so we can go to perplexity here and, uh, oh, uh, share this tab. Okay. So can you see perplexity here?

• 59:45Dan Shipper?

  Yeah. I guess eliminating any chance of perplexity ever sponsors the show, but, um,

• 59:52Speaker 00

  no, no, no. They, they do great work. We, we, we like them a lot.

• 59:55Dan Shipper?

  You should do pro. Yeah. Make sure it's pro.

• 59:58Speaker 00

  Yeah, pro. All right. That's fire.

• 1:00:02Speaker 00

  Okay.

• 1:00:03Dan Shipper?

  Okay, so it's doing some of the, it's, you know, saying, okay, we're going to navigate to the URL. It did that. It's going to extract the main ideas from each article. And then it says, I apologize, I cannot directly download content from external websites. See, this is exactly what I'm talking about with the risk thing is perplexity is a huge startup now. There are all eyes on them. They have to make sure that it works for everyone and that they don't get sued. And that means that they have to limit, like, the edge of the product that they can build is not the edge of the technology. It's the edge of what they legally are allowed to do and like what they think can work for like the greatest number of people.

• 1:00:46Dan Shipper?

  And because you're, you know, I don't know, how many people are you now?

• 1:00:51Speaker 00

  We are very small team, so we have basically, it's Cartier and I and another three engineers. We have a few contractors for some front end that work.

• 1:00:58Dan Shipper?

  You're five people. So you can do, which is great. And what we, what you can do with five people is just so much different. And it's, it would not get easier if you had 100. It would get harder. I think that's a really important thing that people miss about this type of product.

• 1:01:13Speaker 00

  Yeah, and it's also because I think perplexity's focus is, is really kind of like replacing Google, right? It's the answer engine versus the question, right? Which I think is a great angle. Our focus is not that. Our focus is like what you have, which is I have all these, you know, different kinds of documents here. And I need to manipulate and create new documents from it. And usually what that means is you have to be really good, like you have to have tools that are really good at fetching, parsing, manipulating, creating documents. So it's a kind of like a different focus as well.

• 1:01:47Dan Shipper?

  Yeah, totally.

• 1:01:49Dan Shipper?

  Well, this is really, really cool. I'm, I'm really glad we got a chance to chat. Before we go, if you want to check out what you're working on and just check out your stuff personally, where can they find you on the internet?

• 1:02:00Speaker 00

  Yeah, so our website is myaidrive.com. That's basically the app that we've been using here during the show. If you want to use, if you have ChatGPT Plus or Teams, you can see our GPT, which is in the productivity category. You can find me on X as well. And I think my handle is @VicenteS. So V I C E N T E S. That's my handle on X. And you know, it's awesome to be able to discuss this kind of stuff with you, Dan.

• 1:02:31Dan Shipper?

  Thank you so much. A true pleasure.

• 1:02:33Speaker 00

  Likewise.

• 1:02:41Speaker 02

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• 1:03:13Speaker 02

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