Pod Insights The Startup Ideas Podcast Meet the AI Meme Millionaire About this episode Join me as I chat with Ben Benkhin, Creator of WOMBO, about how he built mobile apps that achieved over 250 million downloads by identifying emerging AI technologies and making them accessible through simple, user-friendly interfaces. His first app, Wombo, allowed users to animate selfies to sing popular songs, while Dream was an early art generator that predated tools like Midjourney. Ben emphasizes the importance of studying viral content formats and creating apps that help users easily produce shareable content.
Timestamps:
0:00 - Intro
02:00 - The "Copy What Works" Strategy
05:15 - Competition is GOOD
07:13 - WOMBO Demo
08:15 - Engineering for Virality
11:53 - Steps to creating viral mobile app
15:20 - WOMBO Story Continued
21:26 - Monetization strategy
23:57 - Optimization and Evolution of Wombo
29:22 - Advice for building an AI Mobile Apps
30:07 - Viral Content Creation and Studying Trends
Key Points:
• Ben created viral AI apps including Wombo and Dream by identifying open-source AI models and making them accessible through simple mobile interfaces
• His strategy involves studying what's already working in the market and putting his own spin on it ("mimesis")
• The most successful apps have a viral content creation loop where users create shareable content that drives new user acquisition
• Monetization came through subscriptions and ads, with only 2% of users paying while the other 98% drive virality
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WOMBO: https://wombo.com/m/home
Transcript Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.
0:00 Greg Isenberg? This is not your standard SIP episode. I brought on this guy who went from zero to 250 million mobile app installs using some open source AI models. He tells the whole story, how he did it. You know, it definitely fired me up around this whole new wave of creating, you know, multimillion dollar mobile apps in under seven months.
0:33 Greg Isenberg? Ben, you've created these AI apps. You've got hundreds of millions of downloads. You're backed by Nvidia. I want you to teach us. Well, actually, what do you want to teach us before I would? I want you to teach us.
0:45 Speaker 01 Yeah, I thought I'd just come on here and talk about a strategy that's worked well for me in many different domains in life. And it's sort of a basic fundamental of mimisus, which is if something is working, then probably you can copy it and put your own spin on it and it'll continue to work.
1:05 Greg Isenberg? Okay, and by the end of this episode, like, what are the concrete things that people are going to learn?
1:11 Speaker 01 I'm going to show you how I've applied that strategy to a few different successful things in my life. How I used it to come up with the concept for an app, my first mobile app ever that got over 100 million downloads. How we use that concept consistently go viral on Instagram and have reels that get millions of views and that are, on one hand, a remix of something else that already exists. But on the other hand, something that we put our own unique flavor on.
1:43 Greg Isenberg? Okay, I mean, how to create apps that get millions of downloads? How to get, how to create content that gets millions of views? How to raise, you know, millions of dollars from, from people like Nvidia? You, you have my attention.
1:56 Speaker 01 Okay, let's do it. It's actually pretty fucking easy if you don't overthink it too much. So, okay, first, very brief anecdote. I think I picked up this principle from video games. I was a jungle main in League of Legends. I was sort of like a platinum, gold level player, which is like 60th, 70th percentile. I wanted to get better, so I started watching streams of players that were better than me, that were playing the same role. And I would just copy them and then put my own spin. So that's where this sort of entered my head for the first time. In the summer of 2020, I applied this to conceptualize and eventually launch one of the most viral apps ever, Wombo. So there were a few signals that I picked up on.
2:41 Speaker 01 First was Reface. Reface, in the summer of 2020, was the number one app on the App Store, and Dreesen invested and led a five and a half million dollar round. And what got my attention about this was it was an app that I fully understood. So what did Reface do? Reface did face swaps. So you could put in like a Cardi B music video, take a selfie, it would put your selfie into the Cardi B music video. Hundreds of millions of downloads, memes that, you know, my friends were sending each other. I knew which model they were using and how they were accomplishing this. And the, the design of the app was also very simple and intuitive and kind of made sense to me. So that was the first seed.
3:24 Speaker 01 The second seed was this PewDiePie video, where he covered some very strange memes, and we can see the date here, four years ago, August 2020.
3:38 Greg Isenberg? It's beautiful, it's beautiful.
3:39 Speaker 01 Of course, this got seven million views because it's PewDiePie. And this got my attention as well because this was another open source AI model that I was familiar with, called the First Order Motion Model. And it was starting to go viral in sort of the AI circles, and also just like the hardcore, like Discord artist circles, like people on their computers for like 14 hours a day.
4:03 Greg Isenberg? People like us?
4:05 Speaker 01 Yeah, people like us. And they were using a Google Collab notebook to basically stitch this output together. He gave it a selfie, he gave it a driving video, which is what kind of creates this animated choreography. It's actually someone else moving their head around. And so this one driving video of a guy singing "Baka Mita" went viral over and over and over again. And so one night, I'm smoking a joint with my roommate on the roof, we're looking at these memes, someone had made a Telegram bot where you could do something similar. We're like, man, like... Why doesn't someone just make an app like where anyone can do this where it's simple? And so immediately like it kind of starts off as a joke, but the circuits start
4:49 Speaker 01 firing like, oh, wait, like reface just did the same thing. They have hundreds of millions of downloads. Here's a new open source AI model that like no one's done this for yet. Like, easy, like, we're gonna be billionaires. We'll get this done in a week, you know?
5:04 Speaker 01 Did not take a week, took us seven months. But in March of 2021, we launched Wombo. And maybe I can find a quick walkthrough on YouTube.
5:15 Greg Isenberg? When, when you had this idea and you saw that A16Z reface company, like, a lot of people would look at that and be like, okay, they're gonna win this space. Like, you know, it's already gonna get competitive. But you kind of said, no, no, I'm gonna create an, I'm gonna compete with them.
5:33 Speaker 01 Yeah, I wasn't thinking that I'm gonna compete with them. I was just thinking like it's early, like, there's lots of space to play. Like, I don't know, like, there's, where my mind goes to is like, like, like, movie directors or, or musical artists, like, we're never gonna run out of, like, new movie directors or artists. Like, we're gonna continuously want new, interesting shit. So I don't think anything is like too crowded.
6:02 Greg Isenberg? Mm hmm.
6:03 Speaker 01 Yeah.
6:03 Greg Isenberg? Abundance mindset.
6:05 Speaker 01 Yeah.
6:06 Greg Isenberg? Sam Altman, the co-founder of OpenAI, just said that it is the era of the idea guy, and he is not wrong. I think that right now is an incredible time to be building a startup. And if you listen to this podcast, chances are you think so, too. Now, I think that you can look at trends to basically figure out what are the startup ideas you should be building. So that's exactly why I built idea browser.com. Every single day, you're gonna get a free startup idea in your inbox, and it's all backed by high-quality data trends. How we do it, people always ask, we use AI agents to go and search, what are people looking for? And what are they screaming for in terms of products that you
6:50 Greg Isenberg? should be building? And then we hand it on a You know, silver platter for you to go check out. Um, we do have a few paid plans that, you know, take it to the next level, uh, give you more ideas, give you more AI agents and more, almost like a chat GPT for ideas with it, but you can start for free idea browser.com. And if you're listening to this, I highly recommend it.
7:13 Speaker 01 Um, so I'll just kind of briefly walk through this. You can actually see that in this video, this lady shows this old Google collab notebook for the first order motion model. It's like my grandma could never use this shit. Like, I mean, she could if I like.
7:27 Greg Isenberg? Told her Python.
7:28 Speaker 01 Yeah, but like she could never use that. Um, so here we go. Uh, you would take a selfie. That's the first thing you do. Then you pick a song. And then you sit through a little loading screen like this. And then finally you get your output. And, uh, we'll just see, see that at the end. Obviously looks super basic by 2025 standards, but literally those three screens of input, song selection, output, oh, sorry, loading screen and then output, four screens. That's all we needed to get a hundred million downloads.
8:09 Speaker 01 And, uh, we intentionally sort of designed something that would be extremely simple to use. Um, sort of, uh, the whole thing is engineered for virality in a way because the whole expectation is you as a user come in, you make a piece of content, you make that piece of content extremely easily and extremely quickly. And then your natural inclination is to share or to make another one where like your dad is the one singing or the pope or a politician or whatever. And so we, we spent no money on marketing and spent all our money on inference. And, uh, that's, that's how the thing went viral.
8:51 Speaker 01 Maybe the only other thing I'll say here, and I'll kind of kiss my own ass a little bit here, is the song selection. We selected fifteen songs that we launched with, and these are some of the most recognizable and iconic songs of all time. Or there were songs, there were kind of meme songs. And so like, you know, one example of something that would make a song a meme song is you don't need to know English to vibe with it. For example, Boom Boom Boom Boom by the Venga Boys. You don't need to know English.
9:23 Greg Isenberg? No.
9:24 Speaker 01 Sounds great.
9:25 Greg Isenberg? Yeah, absolutely.
9:25 Speaker 01 Wherever you are.
9:26 Greg Isenberg? Yeah.
9:27 Speaker 01 And so we really deliberately picked those fifteen songs, and then we really deliberately made the fifteen driving videos for those songs. And that was, I think, key.
9:40 Greg Isenberg? And you made it like stupid simple.
9:42 Speaker 01 Stupid simple.
9:42 Greg Isenberg? Stupid, like, this is, you can give this to a five-year-old and they'll know what to do.
9:47 Speaker 01 Exactly.
9:47 Greg Isenberg? A buddy of mine has an app that's going viral right now. Maybe you've seen it, Mixi?
9:52 Speaker 01 Mixi?
9:53 Greg Isenberg? Yeah. Have you seen that?
9:54 Speaker 01 I think so.
9:54 Greg Isenberg? Yeah, so it's like a mashup. Like, go to, just Google M-I-X-I.
10:01 Speaker 01 Mixi app.
10:03 Greg Isenberg? I think it's with an I. There it is.
10:05 Speaker 01 Oh, yeah, I've seen this.
10:06 Greg Isenberg? Yeah. So it's like two guys. You know, you put two beats together, it mashes it up, like, simple idea, right? But the UI is really simple, and they're getting like, I mean, it's one of the top music apps. I don't know the monetization of this, but I think there's this whole next, there's this whole new generation of apps that are just like really stupid simple. That, I mean, it's a similar concept, right? Like, I'm sure his songs are, like, he's doing a queue of songs that, you know, people actually want to choose, right?
10:47 Greg Isenberg? It's simple UI, and it's viral because you want to share that on IG, etc.
10:54 Speaker 01 Yeah, I personally...
10:57 Speaker 01 Like starting with stupid simple and maybe from stupid simple, you can do something more advanced and interesting.
11:04 Greg Isenberg? Yeah. With with respect to mobile apps, right?
11:06 Speaker 01 With respect to mobile apps. And I mean, it all kind of boils down to attention at the end of the day. Like if you're trying to make a product, it's not just someone's money that you're after. Like even before that, it's their attention. And there's so many fucking distractions. There's so many different things that are pulling you in a million different directions at all time that I find the best way to sort of introduce myself and get someone's attention for the first time is to do something stupid and do something funny, do something simple, not try to fucking explain Socrates to them or something. But just basically tell a small joke or another analogy could be like, give them a small piece of candy as opposed to like, you know, here's a fucking steak.
11:49 Greg Isenberg? Right. Yeah, because what I'm trying to figure out, what I'm trying to reverse engineer is how do you create a mobile app that gets millions of downloads? So stupid, simple one. What else?
12:01 Speaker 01 So in our case, there's always been some kind of viral content creation loop, meaning someone comes in, makes a piece of content, shares that content on other platforms, and that's what drives your user acquisition. And so that whole, that whole component has a lot of extremely important details. So first is the content creation. How are you going to help someone make a good piece of content? Also, the game has changed since five years ago with how far generative AI has come and the kind of content that people are interested in making. But still, I think it's applicable today. So here's how I would boil it down.
12:44 Speaker 01 How do you, how do you help someone make a piece of content that either they're going to post on Instagram and post on TikTok for the algorithm? And the algorithm is like, that's a great piece of content. Let's give it millions of views. Or more for their own like personal networks. And the people in the personal network are going to be like, wow, that's really awesome. I want to make that thing too.
13:05 Greg Isenberg? So you're basically saying you start with the content, like the end content.
13:09 Speaker 01 Yes.
13:09 Greg Isenberg? Which is kind of what my friend Joe is doing with Mixi, right? Cause like, he knows that people want to share these mixes.
13:15 Speaker 01 Absolutely. And so like, you know, one thing maybe we could touch on briefly is just the algorithmic feeds of today. Like the amount of human attention that is just being sucked into the full screen, infinite scroll format. Whether it's Tik Tok or Instagram or YouTube Shorts or, you know, X has one. Like that is just like the battlefield of attention. And so I think like a great source of product inspiration is to look at that. And look at where are people's attention going? What kind of content are people making? Can I make it easier for them to make some, some piece of content that is consistently going viral over and over again? And then, and then put my watermark in the bottom right.
13:54 Greg Isenberg? Does this only work for like B to C fun apps? Or could this also work for like B to B or, or prosumer type apps?
14:04 Speaker 01 I think it could work for everything. Like you probably need to adjust your like principles a little bit. And like, you know, maybe I'm going to stop paying attention to the Tik Tok algorithm and start paying attention to like, I don't know, the conference that all the people in a particular niche are going to. But it's, it's the same thing. Like what do the people you care about pay attention to?
14:27 Greg Isenberg? Right.
14:27 Speaker 01 And where?
14:28 Greg Isenberg? Right.
14:29 Speaker 01 Yeah.
14:29 Greg Isenberg? And, and sort of the key, the key point is like, look at what other, you know, look at the content, look at what's going viral and then apply that to whatever it is you're doing.
14:41 Speaker 01 Yes. So in the case of Wombo and the summer of 2020, it was, well, Refa has just got a number one app and hundreds of millions of downloads. And hey, there's this new model now, which is still very hard to use. This is another very good signal, by the way. If something is going viral inside of like some technical circle, but it's still, it's still difficult for a layperson to use. Then if you can help the layperson get access to that same technology and make it easier for them, that's typically like a really good recipe for virality or a really good sign that something might go viral.
15:21 Speaker 01 So I'll just wrap up the Wombo story. From kind of that moment of inspiration, it took us seven months to actually get the app on the App Store. But we finally launched it in March of 2021. It went insanely viral, got like 50 million downloads in its first month, in the first three months. And, you know, after sort of some just like stabilizing, taking it all in and raising a little bit of money and building out a team, the obvious like next question was, okay, well, we just did this with one AI model. What other AI models can we do this with? And now this is a really obvious question to ask in 2025, age of AI.
16:03 Speaker 01 Again, 2020 was still a little bit different earlier. Generative AI was not even a buzzword yet. And generative AI is already a buzzword that we've moved past now. Why, what's the latest now? I feel like now it's just like AGI, superintelligence, like agents, you know. So the next concept was Dream, which was an artwork generator. For the nerds, it predates Midjourney and Stable Diffusion and DALL-E and was basically the first time that image generation went viral. Now, of course, image generation is everywhere. And we saw something very similar happening. Again, almost the exact same thing we saw happening with Wombo.
16:46 Speaker 01 People were playing with a combination of two models, VQGAN, fuck VQGAN and, Prashant, I need your help. What's up? I forgot, what were the two models? Huh? Diffusion model? It was VQGAN diffusion? VQGAN clip. VQGAN clip, that's right. VQGAN clip. So you combine VQGAN with clip, you could generate these crazy dreamlike images. There was like maybe 20 or 30 people on Twitter, and really like five at the beginning, who were like messing around with this stuff. And those were like the earliest in context of like this era's neural networks for image synthesis. And we did the same thing. We wrapped that up into a fun and easy to use mobile app.
17:31 Speaker 01 We made an extremely optimized version of the model, which had fast generation times.
17:38 Speaker 01 And we did some templating to make it easier to create high-quality images, basically just adding words to the prompt that the user gave us. And exactly the same thing happened, another number one app. And many of the lessons that we learned from Wombo about give the user a simple to provide input. The case of Wombo is a selfie, and the case of Dream was a text prompt. Pre-process that user's input with your own input that kind of like structures it and makes it work well. So in the case of Wombo, it was the driving video.
18:18 Speaker 01 In the case of Dream, it was the kind of stylistic keywords that we were adding to the user's prompts. Make the inference really, really fast and free for the user. Did that in both cases. Put all that together in a fun and easy to use interface, and you have something with like all the ingredients for virality.
18:38 Greg Isenberg? Okay, and like, so it goes number one. What next?
18:45 Speaker 01 Yeah, so just in terms of the trajectory of the company. Listen, I had no idea what the fuck I was doing. Like, I'm not like one of these like Silicon Valley kids who like watched every Paul Graham video. I was just like smoking weed in my bedroom, playing League of Legends, and like really, really interested in AI. So made every mistake we could. But at that time, now we're sort of at the end of 2021. We had a team of about 20 people, all working here in Toronto. Got a few apartments that we were using as offices. In 2022, we're like, let's raise money, because that's what you're supposed to do.
19:28 Speaker 01 Ended up putting together a Series A, where the lead investor kept us in due diligence for two months, and then pulled out of the deal. And they pulled out of the deal partially because our original Wombo app used music, and there were some sort of unknown liabilities and risks around our use of music. I didn't know if I should bring it up with these mixy guys, but fucking the music licensing people are vicious, annoying motherfuckers. But also, you know, it is what it is.
20:04 Speaker 01 And also partially because FTX crashed and all this crazy shit was happening in crypto and
20:10 Greg Isenberg? Zirp was over.
20:11 Speaker 01 Yeah, there was like a market spook. So we went from having fucking number one app thinking we're about to get 15 million dollars to having negative runway and being like, what the fuck just happened?
20:25 Greg Isenberg? Negative runway meaning like you're out of money?
20:27 Speaker 01 Yeah, like.
20:28 Greg Isenberg? Or you're like really out of money?
20:29 Speaker 01 Like really out of money where and it really happened because that month Dream went viral again and we had a million dollar server bill on Amazon for that month for all the influence that we were doing. And I had like, maybe not the perfect philosophy around this, which was like, money is fake. Let's just make an amazing fucking product. Let's get all the users. We'll figure it out later. Yeah, didn't work at that point. So we went into like a year and a half of cockroach mode, basically, where I wasn't paying any of my bills unless I absolutely had to. We were extremely focused on monetizing our products,
21:11 Speaker 01 which previously we had never given a shit about, and basically getting to like profitability. And along the way, we, you know, still raised some money from investors who believed in us. So yeah, about a year and a half of cockroach mode, got to profitability.
21:26 Greg Isenberg? And how did you monetize the apps? Because I think, because I think that's a question that a lot of people have, which is like, okay, great. Now I've built this mobile app. It's starting to get some traction.
21:35 Speaker 01 Yeah.
21:36 Greg Isenberg? What, you know, how do you think about monetizing? Like, what's the sauce around monetizing mobile apps?
21:43 Speaker 01 Just copy people who are better than you.
21:46 Greg Isenberg? So who's the best? Who's the best? And what are they doing?
21:49 Speaker 01 Fucking Nikita, man.
21:52 Greg Isenberg? Nikita Beer.
21:52 Speaker 01 That guy is the, that guy's a great monetizer of apps.
22:00 Speaker 01 Shout out Nikita Beer. Yeah, go. I guess you can't do it anymore, but go like pay $10,000 to talk to him on intro. And I'm sure he'll give you some good tips.
22:09 Greg Isenberg? Okay. So how did you, how did you monetize it?
22:13 Speaker 01 We introduced a subscription and we introduced ads. The subscription did things like, well, if you want to generate an image, you could generate four at a time instead. If you're a subscriber or you could have access to some premium styles if you're a subscriber. And that took us from zero to, I think at our peak, Drew was doing over $500,000 a month. And that got us to profitability and sort of stability that we needed.
22:41 Greg Isenberg? And for us, like, what are we talking like $5 a month, $5 a week? I know a lot of people are doing weekly subscriptions now. Like, what was it?
22:51 Speaker 01 We've done everything from $5 a week to $5 a month. We started really cheap and got more expensive over time. And there's also like all the like dark patterns that you could do with like hidden trials and all that kind of stuff. We never went too deep into that.
23:10 Greg Isenberg? Yeah. Okay. Have you, I'm sure you studied like Cal AI and what they do.
23:15 Speaker 01 Yeah, yeah.
23:15 Greg Isenberg? What do you think?
23:16 Speaker 01 It's a new generation of killers, man. I love to see it. It seems like every few months now, there's like a new 18 year old kid making $2 million a month on some simple stupid shit. And I think it's only going to accelerate.
23:34 Greg Isenberg? Yeah. And, and those apps are monetizing via subscriptions, right?
23:39 Greg Isenberg? Weekly, monthly?
23:40 Speaker 01 I'm not sure. We'd have to double check.
23:42 Greg Isenberg? I think weekly.
23:43 Speaker 01 Yeah.
23:43 Greg Isenberg? I think that's a trend I'm seeing a lot is like weekly subscriptions, anywhere from like $3 to $20 a week.
23:54 Speaker 01 Makes sense.
23:55 Greg Isenberg? Yeah. Cool. Okay, so going back, so you're, you start making money, basically, and then what next?
24:03 Speaker 01 Yeah, so we slowly emerge out of cockroach mode. I guess bringing us into 2023 and 2024, the most notable things that happened were, one, we had a relationship with Nvidia. They approached us very early on because they saw that our apps were going viral and that we were doing this thing that was going to be called generative AI. And they want to kind of learn more about it and see how they could support it. Of course, it's evolved like far, far beyond that now.
24:35 Speaker 01 And that culminated in us meeting them more and more and them making an investment into Wombo.
24:45 Speaker 01 The second thing that happened was I sort of, I lost some interest in making apps and I gained more interest in, you know, where all of this was going, where AI was going.
25:01 Speaker 01 Oh, man, this is going to be kind of a convoluted point, but it'll make sense at the end. Okay, so one thing that we've always cared about is inference efficiency. How do we make generation times extremely fast? And how do we spend the least amount of money that we can on powering this inference?
25:20 Speaker 01 So initially, that meant we are going to host our models on GPUs. We're going to sign a three-year contract with Amazon where they give us some better pricing and we're going to pay specialists $3,000 a day to make our model produce the same output but in a fraction of the time. And it's just worth it to find a specialist like that. That was sort of the first solution. And then we're going to run all the inference on the cloud. Our users never have to worry about it and it's consistent. It's high quality. It's reliable.
25:59 Speaker 01 Then there was a motivation to move some of this inference on device, especially as your user base has devices in it that are powerful and perfectly capable of running the model that you care about. And so we started doing a little bit of that. And sort of the natural extension of that is, well, if there's someone in my user base with an iPhone 16 Pro or a computer with a 4090 on it that can run their own workloads, what if they could run workloads for other users as well? And so that idea of sort of peer-to-peer computing and using our users compute was
26:43 Speaker 01 born out of our continuous push towards inference efficiency. Hopefully, all of that is making sense so far. And so the other thing that happened was, at the end of 2023, at the start of 2024, I got really interested in how AI and crypto would intersect. And so I looked at every project in the space, studied them closely, again, coming back to that same principle of copy what other people are doing, or at least understand what other people are doing before you do your own thing. And so we looked at BitTensor and Jensen and Render and Akash and Golem and the Internet
27:24 Speaker 01 Computer and Folding at Home and all these other sorts of examples of decentralized AI or decentralized computing happening. And I just ended up finding that extremely interesting. And to make a long story short, aside from learning about those projects and even building in some of their spaces, the conclusion we came to was to build our own thing called W.ai, which would essentially allow anyone to turn their MacBook, their gaming computer, and in the future their PlayStation or iPhone or whatever into a compute contributor. And so it's almost like Airbnb for that device. When you're not using it, you can make it available to the world.
28:07 Speaker 01 It's going to run some, hopefully valuable workload and earn you a reward. And reward being money? Reward today being points, which were later turned into a token, which were later turned into money. I'm not like media trained, so I don't know what I'm allowed to say.
28:25 Greg Isenberg? You're not media trained? I had no idea.
28:26 Speaker 01 No, I'm not fucking media trained. But the idea is you are contributing to the network. Like if I just let, if I let W.ai generate 10,000 images for somebody else on my machine, then I should be able to generate at least 10,001 images in return. And that seems fair.
28:46 Greg Isenberg? Yeah, totally. Cool. And that's the journey.
28:49 Speaker 01 That's the journey. A lot of crazy shit has happened in between. Cycled through the team many, many times. We started with six co-founders. Only one remains. Three of them have started new companies that are very fucking cool and interesting. So check out Omega, check out Dippy. That's the Wombo Mafia. And now we all live in a big ass house in LA. There's like 12 of us who live and work there. There's a few of us who don't live and work there, but are still core parts of the team. But yeah.
29:22 Greg Isenberg? And, and just to tie a bow on it, okay. So I think that there's a huge opportunity to build, and I know you agree too, build mobile apps that have an AI component to it.
29:31 Speaker 01 Yes.
29:33 Greg Isenberg? A lot of, you know, like every startup, most fail. If you want to create a mobile app with some AI component to it, that gets millions of downloads. The way to do it is step one, see how other people, see, see, like, understand your landscape. What are the, what are the other apps out there?
29:55 Speaker 01 Go look at Cal AI, go look at Riz AI, go look at all those apps.
29:59 Greg Isenberg? Right. Study them.
30:00 Speaker 01 Study.
30:01 Greg Isenberg? Like, understand that every single screen.
30:03 Speaker 01 Yes.
30:03 Greg Isenberg? Why they're doing it, how they're doing it, what colors they're using, what typography, everything. Step one. Step two is from a content perspective, understand what is going viral in a bunch of different niches, right?
30:18 Speaker 01 And, and we can, we can stay on this point a little bit. I have two collections that I think of interest here. This group chat on Instagram. And this collection, which I can actually make public and share with you if you'd like. This has been me sort of cataloging AI-generated content, or content that could have been generated by AI, which has gone viral on these respective platforms for the last like two years. So for example, let's go, there was like a week or two where I was getting a bunch of these baby videos.
30:53 Greg Isenberg? Yeah.
30:55 Greg Isenberg? Like Theo Von?
30:56 Speaker 01 Yeah.
30:56 Greg Isenberg? Yeah, I've seen these, like the baby, this is with Hedra, right?
30:59 Speaker 01 Yeah, this is with Hedra and I think they were using ChatGPT to turn the original image into like a babyfied image.
31:05 Greg Isenberg? Okay.
31:06 Speaker 01 And then Hedra to animate it.
31:07 Greg Isenberg? Okay. Hedra.ai for folks who haven't checked it out, ChatGPT to create the reference image.
31:13 Speaker 01 Yes.
31:13 Greg Isenberg? Feed that to Hedra, okay.
31:14 Speaker 01 Yeah, so I'll upload like a picture of Heisenberg, be like, turn him into a baby, and then take that baby picture, bring it to Hedra. So maybe someone, you know, for the week or two that this was going viral, or even now, can make an app that just fucking abstracts that away from people. They don't have to worry about ChatGPT, they don't have to worry about Hedra, it's just, you know, take a selfie, choose a scenario, done.
31:40 Greg Isenberg? Right, so it's basically productizing the content format, is what you're saying?
31:45 Speaker 01 Yes, exactly.
31:49 Speaker 01 It's also just useful to study how this stuff changes over time, because it's, the AI is not just transforming or creating content in one way. It's doing a bunch of different things.
32:01 Greg Isenberg? So is your advice to people, just like scroll and then just save?
32:06 Speaker 01 Yes.
32:08 Speaker 01 If you want to brain rot, then you must be brain rotted first.
32:11 Greg Isenberg? Right, true.
32:13 Speaker 01 So lately, we've been having a lot of success with some really stupid shit. And it's churning celebrities, extremely recognizable celebrities, into pregnant cats.
32:27 Greg Isenberg? Okay, like the Trump, let's go open the Trump one.
32:30 Speaker 02 Hey Elon, it's time for our litter to be born.
32:41 Speaker 03 Hey Donald, why do these kittens look like Jeffrey Epstein?
32:48 Speaker 01 So like, why does this work? It works because you have celebrities who are recognizable. It works because it's kind of controversial. It works because pregnancy is a concept that everybody can evolutionarily like understand. And then male pregnancy is just something that shocks your mind a little bit.
33:10 Greg Isenberg? And it's top of mind, right? This is right around when Elon and Trump were fighting.
33:15 Speaker 01 Yes.
33:16 Greg Isenberg? Right?
33:17 Speaker 01 Now, the other thing about that meme I just showed you is we've repeated that exact same scenario, that exact same storyline, like six different times, and it goes viral each time. Including this one that has almost 20 million views.
33:49 Speaker 01 So literally the exact same thing, just changing the characters, changing the settings a little bit.
33:54 Greg Isenberg? Right.
33:55 Speaker 01 And as a result, like, we can pump that out in like an hour.
33:58 Greg Isenberg? And so that, that got 18.8 million views on Instagram.
34:02 Speaker 01 Yeah.
34:03 Greg Isenberg? And your goal is to get, you know, how many downloads from that?
34:07 Speaker 01 Well, hopefully like, even 1 or 2% is pretty good.
34:11 Greg Isenberg? Yeah.
34:12 Speaker 01 Right now, it's a weird time for us where we don't care at all about our mobile apps, and we care 100% about w.ai. And this content is not really about driving downloads to w.ai. It's more about keeping us sharp and on top of the algorithm. Like, I think that's really important.
34:33 Greg Isenberg? Yeah. The reason I ask is just for people who are creating content like this, what like, what sort of conversion rate should they expect?
34:42 Speaker 01 Yeah, I think 1 to 2% is like a win. And I think also a lot of the downloads are not gonna, like, it's possible that your downloads won't come from the video getting lots of views on the algorithm, but from people sharing some piece of personalized content with their friends. So like, for example, let's say we churned this thing, like whatever this recipe is, into an app.
35:07 Speaker 01 Like if I turn myself into a pregnant cat, I might not post that on Instagram, but I might post that into like a WhatsApp group chat and it'll go like that'll lead to some virality.
35:19 Greg Isenberg? Someone, someone in the comment section, I can hear it already now is, is gonna say, "Okay, I'm gonna go create an app that turns you into a pregnant cat."
35:29 Speaker 01 Yes, I want 10%.
35:31 Greg Isenberg? No, no, that's not even what they're gonna say. They're gonna say, "And you think that you're gonna get millions of downloads and then you're gonna be able to charge people $3 a week for the privilege to do that. That's crazy. You are, you guys are out to lunch." That's, that's what someone in the comment section is saying right now.
35:52 Speaker 01 Yeah, I think, uh, I think that person is not entirely wrong, but they are wrong. Like if you make an app and it goes viral, even if it goes viral once and people never use it again, like that's a eight, nine, potentially nine-figure opportunity. Think about it like you're making a movie. Like if you make a movie, people go to the movie theater and spend 20 bucks to watch the movie, another 30 bucks to get a bunch of fucking popcorn and shit. And then they leave and they never think about that movie ever again. So like you're just giving someone a bite-sized version of that, that they paid $3 for instead of 50. Um, so, yeah, I think, you know, the other thing is with these apps to get millions of downloads,
36:37 Speaker 01 98% of people are gonna use them for free and you're gonna make all your money on the 2% who don't. The 98% are gonna drive your virality and keep making your content and sharing it with their families and friends and getting you to the top of the app store. And then the 2% of people who don't give a shit and they're just clicking buttons and they want the extra thing that you can't get for free, that's where you're actually gonna make all your money.
36:59 Greg Isenberg? Cool. And let's, maybe let's end it on, you know, for people listening.
37:05 Greg Isenberg? You know, do you really believe that there's a lot of opportunity to create mobile apps with AI right now?
37:12 Speaker 01 Infinite opportunity.
37:13 Greg Isenberg? Yeah?
37:14 Speaker 01 Yes.
37:14 Greg Isenberg? And why do you believe that?
37:16 Speaker 01 Because people are glued to their fucking phones and they want to be entertained and they want utility. So if you can be useful or entertaining, then you can make an app.
37:26 Greg Isenberg? Do they need to raise venture capital for it?
37:28 Speaker 01 Fuck no.
37:29 Greg Isenberg? And, you know, how big of apps are we talking? Like, could they create?
37:36 Speaker 01 I don't know, like it's.
37:37 Greg Isenberg? Without venture capital?
37:38 Speaker 01 Like, if I make a really good song, how many people will listen to it? If I make a really good movie, how many people will watch it? If I make like a really good recipe for some gum, like it depends on a lot of factors. But if you make something truly great and truly unique and then kind of truly captures the current moment, then I think you can get hundreds of millions of downloads and make at least tens of millions of dollars just with popcorn mobile apps.
38:07 Greg Isenberg? All right. I like it.
38:09 Speaker 01 Yeah. And good luck to everyone. I hope you make it. It's a fucking crazy time to be alive.
38:13 Greg Isenberg? Thank you for coming on, sharing some sauce and you fired me up to create a pregnancy cat mobile app.
38:23 Speaker 01 I want 10%.
38:25 Greg Isenberg? Later, dude.
38:27 Speaker 01 Much love.
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