The Koerner Office - Business Ideas and Deep Dives with Chris Koerner - AI Agents and Deep Research Hacks. The Latest Updates⏐Holdco Bros. Ep. #149

Episode Date: March 28, 2025

HoldCo Bros are back! In this episode, Nik and I talk about the latest in AI and some unique business ideas. We begin by comparing ChatGPT and Perplexity, highlighting the strengths of Perplexity's de...ep research function. Our conversation touches on our experiences with custom GPTs and the power of using AI for identifying emerging trends. We also discuss the current reality of AI agents versus more traditional RPA. Later, we explore the idea of leveraging AI to create forward-looking industry reports, a concept brought up by Zach Ashburn. Finally, Nik shares the incredible entrepreneurial journey of Ethan Kohan, from the world of gambling to the unexpected success of vending machines on college campuses.Learn more about Nik here: http://linktr.ee/cofoundersnikShare your ideas with us:Nik@cofounders.comChris@cofounders.comTimestamps below. Enjoy!---Watch this on YouTube instead here: tkopod.co/p-ytAsk me a question on or off the show here: http://tkopod.co/p-askLearn more about me: http://tkopod.co/p-cjkLearn about my company: http://tkopod.co/p-cofFollow me on Twitter here: http://tkopod.co/p-xFree weekly business ideas newsletter: http://tkopod.co/p-nlShare this podcast: http://tkopod.co/p-allScrape small business data: http://tkopod.co/p-os---00:00 The Rise of AI and Research Tools02:56 Custom GPTs and Their Applications05:50 Deep Research and Market Trends08:48 Exploring Unique Business Ideas12:07 The Evolution of Agents in AI15:07 Predicting Future Trends with AI18:01 Innovative Business Models and Side Hustles

Transcript
Discussion (0)
Starting point is 00:00:00 There's a lot of money, billions of dollars pouring into agent rappers. Well, Vegas always wins. Why don't I just become Vegas? That sounds like the perfect side hustle, actually. I agree. 15 grand all day. For thousands of years, recorded history, every king has had their advisors. Expert on farming, expert on war, expert on commerce.
Starting point is 00:00:15 We don't have that at our fingertips. Whereas in the past, it was the billionaires who could afford to have somebody on their staff. If you want the deep research, just use perplexities for $20 a month. And you basically get the same thing, if not better. Banana ketchup. It is 90% of the ketchup market in the Philippines. What? All right. I got a little framework, AI hack for our listeners today. You've got Chad GPT,
Starting point is 00:00:38 their $200 a month pro plan. And then you've got perplexity. Their pro plan is $20 a month, but they have a deep research function that is in mind and Kamal's opinion. Shout out to Kamal for pointing this out to me better. Just because of the UI, the way they organize it, it's better. Okay, so the experience is better, not necessarily the output. Both. Have you messed around with GROC's deep research? just a little bit. I would be curious to hear your guys's opinion on that too. Okay, but like we've talked a lot about operator and deep research.
Starting point is 00:01:08 Most people, myself included, are hesitant to pay $200 a month, especially when free options out there exist like rock. So if you want the deep research, just use perplexities for $20 a month. And you basically get the same thing, if not better. Because I'm not using operator. Like now that deep research came out, I haven't used them about two or three weeks. It's a little life fact. Let me ask you why.
Starting point is 00:01:28 Why aren't you using operator? Because deep research does it for me. it's faster. It's the same thing for me. It's like I was going to use operator to go and scrape all these sites, but now I can just tell deep research, go to these sites, pull this information, put it into this table, and it just executes it. So it's kind of weird to me. Like, well, why would I ever use operator at this point, especially given the functionality currently? I'm assuming that operator is going to get a lot better and a lot faster and then we'll go back to using it. But I'm having a lot of luck. I have like a GPT just called deep dives.
Starting point is 00:02:00 And that's where I do a lot of my deep research prompts. And I still do deep research prompts and other GPs, but I do it mostly in deep dives. So it'll spit out 10,000 words. And then I just say it. I just say, hey, take the most interesting things based on my preferences and give me bullet points of everything above. And it's like so much easier to read. Can we talk about this right now? We both have custom GPs.
Starting point is 00:02:24 In fact, I texted you this morning about like one of your custom GPs. Tell me about that custom GPT that you built. There's nothing custom. It's just one of my GPTs that I only use for deep research. Like I didn't upload any PDFs or anything to it. There's no overriding prompt. Oh, you just created like a separate folder basically. Yeah.
Starting point is 00:02:42 Yeah. Do you want to talk about GPs? I think that would be interesting to at least like. I'm not having a lot of success with it. Like building a GPT based on all of my tweets or all like where you have like you upload a bunch of stuff and then you have like instructions and then you just start talking to it. I haven't had a lot of success with it. Really?
Starting point is 00:02:59 Maybe I have given it a good enough shot. I have for like very specific tasks. So what we're talking about right now is in chat TPT, you can build a custom GPT. It's not like you're not training it on your own data set, but you are training it more than is allowed in the current context window on chat GPT. So what you can do is you'll say, hey, like I'll give you one of my custom GPs. I have my weekly newsletter GPT. And I've trained it. and I've said, hey, I'm going to upload three transcripts from my podcasts from those podcasts.
Starting point is 00:03:31 This is what I want you to pull out. I want you to summarize each business model with these specific criteria. And here's an example of two that I've done. And then for business idea of the week, I want you to give me three suggestions based on that conversation. And then I want you to, right? So I'm telling it. And then I'm giving in examples.
Starting point is 00:03:52 And then it's saved. And I never have to enter the custom prompt to. again, it's essentially like helping me save a prompt. And so I do use it for that for like very, very specific use cases just to like give me an idea and get me going. But to your point, no, I don't find it to be like perfect every single time. You know what I've had better luck with is whenever Chad GPT spits out something perfect, right? It's just like my voice, my style, whatever. I always tell it, remember this. Hey, remember this. This is, this was really good. Remember this. And it will show you like a little, a little, a little,
Starting point is 00:04:25 like a widget will appear. And it's like, blip, remembered. And it will carry that memory across other chats or other GPTs. I had somebody post this week, Hector Resendez. He posted, he's like, hey, I feel like I need to get into AI. Like, how does a guy even get started in this space? And so I responded and said, here are my three like suggestions. Number one, just pick one.
Starting point is 00:04:48 Chat TPT, perplexity, Gemini. I don't care what it is. Just pick one. Upgrade to the pro plan on whatever which one it is. So it's 20 bucks a month. Cool. And then stop going to Google for anything that's not geographic based. So if I'm not looking for a restaurant or a sports team or hours of operation of a business,
Starting point is 00:05:06 if I'm like, what was the biggest country in the world in 1952? Don't go to Google anymore. Go to the AI. I'm going to say chat GPT for the AI. Cool. And then third, anything that you would have used an expert or an assistant or bounced ideas off of, start using chat TPT. So like I really like uploading contracts or I really like uploading.
Starting point is 00:05:25 financial statements. I really like uploading just things that would have longer than a paragraph that I'm going to have to actually read through. I upload it and then it gives me bullet points and I can start just interacting with it and asking it questions. So if you're thinking about like, how do I even get started? Do that. Get a pro plan for any of the, any of the models. Stop using it for anything other than geographic questions and start anything longer than a paragraph that you need to synthesize, putting that information into it. I think it's a good thing. good framework to basically separate in your mind the geographical or the more recent news because Open AI does not want to go scrape the internet again, right? That costs them money. And so you just
Starting point is 00:06:09 know that open AI is biased. And if you're like, what's the best Filipino restaurant in Dallas, Texas? It's going to have to go look right then. And it's already done that, you know, maybe a month ago, maybe a year ago, it would rather not. And so you're going to get a more biased or a less quality answer than going to Google for stuff like that. But for almost everything else, I go to chat GPT. Totally agree. So one cool framework that I found for deep research is if you're trying to think of trending things or business ideas, one of the best places I get new business ideas is just when I travel anywhere, right? Maybe it's an hour away, just out of my circle. And so I've been using deep research for that. And so I asked to the prompt, I want you to find me like unique foods in other countries that are
Starting point is 00:06:55 starting to take on here in the United States. And then it spits out a bunch and I can take one of those or more and go deep on that one and see, huh, could there be an opportunity there? And I found something interesting called banana ketchup. Have you ever heard of that, Nick? I've heard of banana hammocks, but I've never heard of banana ketchup. All right, banana ketchup. It is 90% of the ketchup market in the Philippines. What? Yeah, it's ketchup made out of bananas. It's healthier. Okay? They eat it with their spaghetti, with their eggs. But ketchup's tomatoes. Not in the Philippines.
Starting point is 00:07:36 Okay. The banana ketchup market in the U.S. is $225 million and growing at like 7% a year. $225 million a year. Yeah. Tiny. Yeah. Tell me the growth percentage again? Wait, wait, wait, tell me the growth percentage again.
Starting point is 00:07:53 7%. That's not that fast growth. It's like if you look at the Google Trends data, It is booming. Like the search volume for banana ketchup, specifically in the United States, is booming right now. Okay. Hold on a minute. So we're talking about frameworks.
Starting point is 00:08:07 Say that again. So you, you're traveling, you're using food. What food is popular? You find, you found banana ketchup. And then you went to Google trends. So you didn't just go to like Google. Well, yeah, yeah, yeah. Yeah.
Starting point is 00:08:20 Then I'm like, okay, interesting. I go to Google trends, type of banana ketchup. Look at the last five years, 12 years. Okay. So you're not going to Google period and being like, what is the, gross domestic product. Okay, you're going to Google trends because that's actually real-time data. I'm just looking for redundancy on what Chad GPT told me. And if I find it outside of Chad GPT, then I go back to deep research and I say, huh, banana ketchup, that's interesting. And when you say
Starting point is 00:08:44 redundancy, you just mean you're trying to find evidence that what ChatGPT said is true. Another data point. Yeah. Okay. Yeah. And then this was my exact prompt. I said, deep dive on banana ketchup in the Philippines and launching something similar in the U.S. Is there an opportunity there? And then it's like, do you want feasibility study, general market analysis? Because you're doing deep research. Yeah. Yep.
Starting point is 00:09:07 And then I say it gave me four bullet points. And I said yes to the top three, no to the fourth. And it gave me so much info. And then I'm like, okay, just give me bullet points of this. Okay, fill me in. What were the bullet points? You could charge $4 to $6 a bottle. It says according to like Google, Google's keyword tool.
Starting point is 00:09:24 there's much more demand than supply. It kind of looks at it like Saracha was 10, 20 years ago, right? Because 20 years ago, you're like, okay, what kind of market is there for like pickled pepper sauce called Syracia? Well, that's pretty huge. Peter Piper picked a pack of pickled peppers. Exactly right. Yeah, I just think it's interesting. Like people are going away from red dye, right?
Starting point is 00:09:45 Red dye is being banned in the U.S. It's a healthier alternative to ketchup. Ketchup is the biggest condiment in the United States by far. Something interesting there. Can I give this is kind of an example of how I use deep research. All right. So I downloaded all of my tweets because you can download that from Twitter. It takes a while.
Starting point is 00:10:07 It takes like 24 hours for them to actually produce it for you. And I got this massive file. What do you want to know out of your tweets, right? You want to know which ones perform the best. You want to know which ones had the most engagement, right? And so whereas a couple of months ago, I would have probably just uploaded the sheet and been like, tell me which tweets were the best. I don't do that anymore. This is the prompt I gave it.
Starting point is 00:10:25 You ready? Okay. Yeah. I have a spreadsheet with all of my Twitter posts from the last year and a half. There are about 520 lines of data. Each line has a link to the post. Let me interrupt you. I really like that you said how many lines of data there are because a lot of times it
Starting point is 00:10:39 will just pull from a sample size. And you don't even know until you really start probing. So it's like this is what to expect, right? Do you know why I started doing that actually? I'm assuming because it was only pulling from a sample size. No. Actually, I didn't know. was pulling from a sample size. I started doing that because of our conversation of you building
Starting point is 00:10:56 that tool with Steve, uh, with. Oh, and how mine was only. Yeah. Yeah, yeah, yeah, because you were, you were like, why the freak isn't this data correct? And then you found out it's only pulling a sample size of 10. So I was like, I don't want you pulling a sample size. I want you pull in all the day. So that's why I include all of all of the lines now. Are you able to look at each post and categorize it for me? I would like you to. I would like you to give a brief one line, 30 characters or less description. That's cool. That's cool. Categorize the post with at least one of these tags, podcast, thread, how to guide, quick share, troll, because I have on troll tweets, framework, tool, deep dive, personal, and story. Give me a quality score on the post based on a mix
Starting point is 00:11:40 of the number of views, bookmarks, and likes relative to my followers at the time. And then I enter. Okay. So, but the reason I wanted to read it out is because it was like, there are probably people listening to her like, wow, that was a lot more detailed than I would have asked. We've talked about this before. If you want to get the right answer, you've got to ask a longer question. And even after asking that, there were other follow-up questions that I had to clarify. But I think I've like shifted in my mind as like, oh, this is a research assistant. I've got to be very specific with them.
Starting point is 00:12:12 They're going to give me good data back. But I've actually got to prompt it in the way that I would prompt a human to go and look at this data. Yeah. because you and I do that all the freaking time. We've been employing people like, hey, go get this done. And they're like, okay. Like they're eager, please. They're like, okay.
Starting point is 00:12:27 Then they're like, frick, what do I actually do? Or worse, they go do it. And they come back to us and they're like, here's 10 hours of work. And you're like, that is not at all what I wanted. And it was our fault for not being clear on what we wanted. The more you treat it like a human, the better it performs, which is a little freaky. Yeah. It is very freaky.
Starting point is 00:12:50 we very free. I was thinking about this last night on the drive home. AI is going to get really good, right? We have really good and really bad employees, though, and they're very smart. What if we have AI developed and it's not the tool that we think it's going to be? It's like, oh, it's going to help me. We give it a prompt and it's like, nah, I don't like what you ask me. Here's what you should be looking at. No, no, you should actually just be looking at the number of tweets by month and the aggregate volume of views. That's what you should be. It's like, well, I didn't ask you that. I want to know exactly about my tweets like I'm curious some employees do that too that's what I'm getting that right is like I'm curious if at some point you know we've got to figure out how to ran it back in but
Starting point is 00:13:27 anyways that was a quick squirrel and then when you combine AI with hardware like a robot and it does the same thing it's like huh instead of cooking you stir fry I'm going to kill you okay let me ask you something about agents. I feel like agents are, it's almost like crypto, even today or five years ago where it's like everyone's like crypto, this, crypto that. And it's like, Web 3. Hold on. Hold on. Yeah. Web 3. Back up. Who's actually using this? Like who is actually buying their coffee with crypto? Well, no one, but like all this potential and we just need to put our tax records on the blockchain, yada, yada. And it's like the business of crypto is buying and selling crypto. And like today, that's still pretty true. I feel like agents are very similar. There are literally over five, over five companies
Starting point is 00:14:17 that have raised seven to eight figures just to be an outsourced sales agent. You know, outsource your sales to an agent. Okay, there's a lot of money, billions of dollars pouring into companies building agent wrappers. And like, we're all talking about it. Agent this. And I was talking to Kamal a month ago. And it's like, hey, anytime I have something to do, if you can do it, then see if the VA can do it. If the VA can do it, see if an agent can do it. That's the new framework so we don't have to hire a bunch of people. Okay, cool. Who is actually using agents to do tasks for them autonomously without intervention on a daily basis?
Starting point is 00:14:51 Are you? What are the, no, no. Like, I'm, you're like actually trying. I'm trying. Like, there's Gumloop. There's Lindy. There's all kinds of tools that like make integrating things and automating things, like the Zapier for AI.
Starting point is 00:15:06 There's a bunch of tools that do that. But like Lindy, we spent. hours trying to get Lindy to work with my freaking inbox. And it's just not there. And I want it to be there. Are you using agents? I tried. Like I'm trying to use agents. The problem with agents is like I still feel like it's manual, right? Like operators is the perfect example. You have to sit there with your tab open and watch it move slower than a human to actually complete a task or a function. Now, I don't think all APIs. I don't think all integrations are the same as the way the operator works. but that's like a good analogy where it still feels like RPA.
Starting point is 00:15:44 So video is cool, but you know what's better? Longform audio via podcast and my newsletter. TKOPod.com. Go there to subscribe for free to my newsletter. It's one email a week, very tactical. And then go to my audio podcast, three episodes a week, stuff like this. You're going to love it. All free.
Starting point is 00:15:59 No sleazy sales bitch. TKOPod.com. Robotic process automation? Mm. Right. So like RPA for people who don't know. I didn't know what it was, but it was very, very specific set of instructions of what to do. Okay, at 10 a.m. go to this website, click this link, click download this report,
Starting point is 00:16:18 export it to this file. But it was it was very, very, very specific. And so you could do really cool things. You could like run a report every single day and then populate a dashboard, but it wasn't an agent. It was just doing what you told it to do. And so I feel like we're saying the word agent, but it's still this like robotic process. automation system. It's going to be agents when we can say, hey, find me the best tweet yesterday in SMB that performed the best, right? And then it goes out and using context and critical reasoning. It's like, okay, well, this one didn't get the most views, but I had the most bookmarks and I had the most shares. And oh, this one was actually retweeted by Mark Cuban. And you know what I mean?
Starting point is 00:17:02 Like best tweet, how do you define that? Like either you're going to have to do the robotic process automation and very clearly defined pull the best tweet or you have an agent that you can say pull the best tweet and it goes and executes that task on its own. I have not found the agents yet. I've found the robotic process automations. Yeah. Which sucks. I want them to be here. We're still so early. I think I told you this a week ago. My mind's kind of shifted from, oh, AI is going to replace everybody in six months to it's going to disrupt and displace a lot of things, but the adoption curve is still going to be a long one. Like it's not. Dude, it's the last mile. Like the last mile for any new innovation is so long.
Starting point is 00:17:42 Like self-driving cars, that last mile. Like, it's so hard to just get that last bit finished. Yeah. Well, and think about it like this. We have been working for years on achieving AGI. The smartest humans in the world. At some point, we're going to get to AGI. And at some point, there's going to be parity between a human and a computer.
Starting point is 00:18:05 but at that point when there's parity, it's only that we have more smart humans to work on problems. Right? We don't have smarter humans yet to work on problems. We just have more smart humans to work on problems. So we will get there. Like there will be an inflection point where we're able to actually develop smarter technology because we've brought computers along and they've reached AGI.
Starting point is 00:18:26 But like we're just not even, we don't even have the resources yet to really get to that point. All right. What you got for me? I got an idea for you. We had a guy. we had a guy tag us on the Twitter sphere. Dragon Slayer 6-9-420 said, no, I was kidding. This is Zach Ashburn.
Starting point is 00:18:44 Zach tagged us. It was a video of him saying, look at this freaking thing right here. Did you watch it? Mm-hmm. Okay. Yep. So I'll explain it and then we can talk about it. I thought it was really cool.
Starting point is 00:18:52 I don't remember exactly what it is, but his wife somehow is in the fashion industry. I don't know if they have an e-commerce store or if she just works in the fashion industry. But he was talking about how in the fashion industry, they have to make decisions a year in advance. they're guessing basically like, okay, what does fall 2026 fashion look like? Because if we want to deliver fashion in fall 2026, we've got to buy products, we've got to manufacture it, we've got to get it shipped. Like there's a whole lag in between when it's produced and when it's actually popular. And in order to prepare for that, these people will literally read industry reports of like, hey, this is what we think is going to be the most popular thing a year and a half from now. Here's the color scale.
Starting point is 00:19:30 Here are the different fabric types, all of those things. And his idea was, why would you not be using chat TPT operator, or an operator deep research to effectively create these forward looking reports and sell them at a much cheaper price point than what companies are currently doing? I thought that was really interesting. So it wasn't just fashion. I went and asked operator, I was like, hey, tell me if there are any other industries that do this. And it gave me some good ones. So he said fashion. here are some of the other ones that it gave me. Food and beverage.
Starting point is 00:20:07 Right. Hey, what food and beverage is going to be popular a year from now? Because again, there's a lag time between what's popular and when you actually produce it. So you could build reports for people to say, this is where preferences are trending. Oh, did you know that there's never touchplastic.com? That's booming right now. So actually a year from now, we think it's going to be three times as big. And so you should have XYZ products on your shelves. Technology. So you could literally go and say, say, hey, here are the top 20 Google trends right now. I went on Google trends and these are the top 20 things. This is what it means for your industry. Did you know more and more people are
Starting point is 00:20:41 searching in-home caregiver? Well, that means the industry is going to grow at a, you know, a rate of 10x percent. And this is the product that you could sell through that vertical, right? Automotive, this was an interesting one, just looking forward and predicting long-term shifts, not only in technology of new cars coming out, but the current cars that are being produced today, what problems are they going to have down the road, right? Like, oh, we're going to have a big problem with LCD screens needing to be replaced in about five years because all those cars that we sold are going to have problems.
Starting point is 00:21:10 I like this idea of like, because I think AI is really good at this, taking information and extrapolating data points that help you understand not only what happened, but how to look for patterns in the future. And I think that this would be like a perfect use case. So thank you, Zach. I'm going to stop talking. What do you think? I think it's great. It's a no-brainer. It's like how long of research has been around, right,
Starting point is 00:21:35 like forever. I mean, pick an industry, healthcare, science, math, engineering, whatever. There's just so many variables out there to really dive deep on and to connect data points on from here to there. So with deep research being, you know, a thousand PhD level researchers in your pocket, we're going to be uncovering incredible use cases for deep research for the next decade. Like, where does it end? I was talking to somebody the other day, and for thousands of years, recorded history, every king has had their court, right? Their advisors.
Starting point is 00:22:09 Hey, I got this guy. He's an expert on, whatever, farming. This guy's an expert on war. This guy's an expert on commerce. This guy's an expert on trade, whatever. We don't have that at our fingertips. Like, I now can have an expert on all of those things at my fingertips, whereas in the past, it was the billionaires who could afford to have somebody on their staff who was like,
Starting point is 00:22:26 hey, let me get Brian. he's the AI expert get him in here I want to ask him a question yeah I got a guy for that yes sir I and Brian graduated with a PhD and like computer science from Stanford University you know what I mean is like yeah so he only knows stuff about computer science and there's only one of Brian right and it's like great I have like the best expert in this field who works directly for me and so that billionaire is able to make much better decisions because he actually has the right inputs well now we have that at our fingertips yeah and Brian is so biased because his favorite professor specialized in job And so he loves Java.
Starting point is 00:23:00 And like, you know what I'm saying? Whereas like deep research doesn't give a crap. It's just going to give us a bunch of data. Back to agents. Like we're all talking about agents. Well, like, we need to be talking about deep research. Like, that's an agent. You just have to prompt it once.
Starting point is 00:23:13 It is an agent because it's doing agentic things. It's going out and it's scraping and it's putting it into a data set for you. If you ask for a data set, it's giving you the links. You still have to go and digest it yourself to understand it. Let me tell you, Nick. You sound really smart when you say the word agentic. Okay. You need to know that.
Starting point is 00:23:30 Can you say that again so I can play it for my wife? That's unnecessary. Just hit repeat. Let me bring an idea that's not AI related and see if you like it. Okay. I love it. I would hate to talk about someone else's business idea and not name them. All right.
Starting point is 00:23:45 I'm not going to call this person some guy. All right. Oh. I'm going to call him his actual username at Justin underscore XYZ on Twitter. Oh, interesting. You give them attribution. That's really weird. Hmm.
Starting point is 00:23:57 I don't think you're supposed to do that. I don't think you're supposed to do that. I haven't thought I'd do something nice today. You know, pay it forward. So Justin from Taiwan, that's his Twitter name, he tagged me on a tweet. And have you ever heard of Activate Games? No, I've heard of Activision. Blizzard.
Starting point is 00:24:16 Activate Games is a retail space blowing up. I think it's a franchise, blowing up across the country. They're in about 4,000 square feet. You're going to find them next to a Chipotle or a Shake Shack. And they're for families, kids and adults, millennials, all ages. You go in, you pay 35, 45 bucks, and you're in this room that has all these rooms that break off. You go in this main room with all these touch screens and a scoreboard, and then you go play these games, like basketball games or like tiles on the floor that light up or, you know, kind of like carnival games. But it's all gamified.
Starting point is 00:24:50 It's you're connected to everyone else there. You have a certain amount of time to do it. And you just, there's like 15, you know what? There's like 15 different rooms. Each room has like five to 15 different games. So there's hundreds of different games in this one space for 35 bucks. It's fun as crap. It's an legitimate workout.
Starting point is 00:25:07 Like you break a sweat. And think like escape room or like a trampoline park, but better than both of them. It's just blowing up. It's like a modern checky cheese. Yeah. That's a good. But like for all ages. Right.
Starting point is 00:25:20 It's got a ton of different games. You can go play a ton of different games. But these are like a lot more physical. Like it's a place for you to bring your kids or for you to go in a double date with your wife and two other adults. No kids. Like it's literally for all ages. Okay. Okay.
Starting point is 00:25:35 So this guy on Twitter found the source of these floor tiles. They're like these light up tiles. They cost like, I don't know, $15,000. You can set up a whole room with the hardware, software, everything. And you can charge people to play instead of hundreds of different games. in a big expensive retail space, you could have them up in your house and charge people 10 to 20 bucks
Starting point is 00:26:01 to play 10 different games all based on these floor tiles. Really? What do you think? Yeah. Like you just set up an iPad, little touchscreen, which game do you want?
Starting point is 00:26:08 And then it plays. You've got lights and you've got the tiles and you dance and you jump from one to the other and there's a timer. And like, this could be a side hustle. Dude, like my mind goes to a mobile side hustle. Sure.
Starting point is 00:26:20 Oh, there's a corporate event. Oh, hey, we're having the company picnic this year. It's at Gerber Park. Oh, that's cool. Hey, let's get the game company, mobile games. Oh, yeah, great idea. And then you come and you have your tile and it's like, oh, the kids want to play a game? Cool.
Starting point is 00:26:34 What game do you want to play? And they take turns playing. It doesn't have to be in a physical location that you're renting out. You can just start on a mobile basis. I would bet it takes like 30 to 60 minutes to set up. Oh, really? Like, yeah, but even so, like that's like $20 worth of labor. You set it up at a park or an outdoor shopping area or totally.
Starting point is 00:26:53 Yeah, I think of like, schools when they're having their like back to school fairs and they're raising money carnivals, especially in the summer when you're having a bunch of cities are having lots of things. This would be like the perfect thing. You just set up. This guy claims, I can't vouch for this, but he says for under $15,000 you can set up a room that pays for itself in a month, charge $25 a person, six to eight people per session, five to six sessions per day.
Starting point is 00:27:18 That's $1,000 a day. Our clients are already doing it. Now granted, he's selling these things. It's in his best interest to say. that but it's interesting because like I wanted to take my daughter to activate games we we showed up and they're like oh there's yeah yeah you can play there's a four hour wait and I crunched the numbers and like because you can see on their website how many slots how many people per slot at a hundred percent occupancy they're doing like seven million a year did you know where this would crush in a college town
Starting point is 00:27:47 that doesn't allow liquor like I don't know provo Utah oh you mean in the only college town on the planet. I'm just thinking like if you set it up in the dorms or if you set it up in like shared student housing, especially, I'm thinking of UIU, right? It's like, Heelman Halls. Heelman halls. They knock those down. I think they're now, I don't know. Anyways, but yeah, it's just like for young couples to go and have a date, that would be a freaking really cool place to go have a date. Anyways, it could be in the dorms. It could be at the university itself. It could be something mobile. That sounds like the perfect side hustle, actually. I agree.
Starting point is 00:28:27 15 grand all day. I have one. So I had this guy on my podcast. His name is Ethan. In fact, I'm going to find his last name real quick. Cohen? Yes, Ethan Cohen.
Starting point is 00:28:38 I had planned to talk to him because he's franchising his business model. I planned to talk to him about franchising. He told me the craziest freaking story. It was just bonkers of how he got into doing what he's doing. Here's the short of the long. He goes to college. He has saved up.
Starting point is 00:28:52 $15,000 and proceeds to lose it in a four-week period of time because he gets into betting and gambling. And the more he loses, the more he doubles down, he's going to make his money back, whatever. Has to go and confess to his dad. His dad's like, you're never doing this again, man. Here, sign this contract. His dad makes him write out this contract. Goes back to college. He's doing fine. Gets an internship six months later. He's got six grand NBA playoffs roll around. He's got the itchy trigger finger. Gambles again. loses it all. He's lost over $20,000 at this point. Then he's like, crap, I got to tell my dad. So he tells his dad. And the lesson he takes from this is not, I should stop gambling. The lesson he takes
Starting point is 00:29:31 from this is, well, Vegas always wins. Why don't I just become Vegas? So he starts a sports book. He becomes Vegas. His friends all start placing bets through him. That's pretty smart. In one month, he's like, I made $22,000 the first month that I had this betting book. He's like, but people weren't paying me and I had to be like threatening to them. He makes $22,000, but he's owed like 10 grand from these other people. And they're not paying them. And he's like, I had to contact a guy. He goes on the dark web. He emails this guy, his social security number and is like, hey, look, man, I have your social security number. Either pay us what you owe us or I might be doing something with this. Ethan did that. Yeah. Ethan had a guy who did that work. And so Ethan's like, I just didn't like it.
Starting point is 00:30:13 I didn't like feeling like that. So I ended up getting rid of the sports book selling it. he then gets into vending machines and starts selling zen through vending machines. It's insane, dude. She's freaking amazing. He's nuts. He committed Zen fidelity? Dude, he was screaming Zen Fidelity. That's how bad it was.
Starting point is 00:30:34 We're so stupid. You're either Zen or you're Zen. You're either Zen or you're out. He was all Zen, dude. Once he found that business, he was all Zen. Anyways, start selling Zen in these vending machines, places it in his dorm he's making like $3,000 a month a kid in his dorm or not his dorm his frat house breaks it he's in europe he gets a message it's like dude your vending machine's broken he's like
Starting point is 00:30:59 oh crap two minutes later also dude that video's trending videos freaking trending what three million the video of them breaking oh i didn't know there's a video of it yeah so they take a video videos of him breaking the vending machine is now freaking trending on barstool sports he starts getting all these DMs. People, they're like, hey, how did you get a Zin vending machine? He's like, oh, well, all I did was buy an old vending machine. And then I swapped out. I took, I got rid of the coin and the, and the paper money reader.
Starting point is 00:31:29 And we just inserted a credit card reader. They're like, oh, cool, could you do that for us? He gets a hundred orders. He's ordered them. He's placing them. They're in the process of fulfillment. He's placed 30 of them. He gets it a loan for $250,000 from friends and family.
Starting point is 00:31:43 He's looking at this. He's like, dude, I'm going to make him for $80,000 a month. profit. This is March of 2020, Chris. What happens March of 2020? Everything shuts down, dude. Everything shuts down. So then he's got these machines that he can't place. Anyways, he's got to like retool everything. It was nuts. It was a crazy story to hear. The interesting thing that I took from that was he got started by buying these old vending machines for like three grand and then working with this Israeli company that's apparently the number one company for the credit card payments on vending machines to then retrofit them with the electronic payments.
Starting point is 00:32:21 And then all of a sudden he was like, I was just buying the shell essentially to make sure that it was safe. But then I had vending machines for way cheaper. So I just really liked the idea that he had, which was going and buying old shells of vending machines and retrofitting them with new technology and then placing them within colleges. using the colleges as a distribution model, I think is a really interesting idea. I mean, we tried to do this with co-founders where we're looking for people who to start business with us using the college system as a distribution channel. He's using it for vending, but I wonder if there's any other cool ideas. Anyways, I just vomited a lot.
Starting point is 00:32:56 What do you think? Dude, I just, I love how his brain works because it reminds me of the midwit meme distribution curve where it's like all the guys in the middle are like, all right, time for some research and development. We're going to figure out how to make a vending machine. can dispense the Zen canisters. All right, let's get a 3D rendering of a Zen can. And like, he's just like, we're going to buy a vending machine to put Zen in it.
Starting point is 00:33:21 It's like, no, you can't do that because, no, you can just do that. And it's funny because the story that he told, he was like, I thought I was going to be patenting these machines. And he's like, and then eventually it was like, no, I'm just buying machines and retrofitting them to sell zin in them. Or like, what's the book or the movie about the guys, the MIT crew that goes and like beats the house? Blackjack? Oh, yeah, yeah, 21. See something like that. So that's like one end of the spectrum. And they're like, all right, we're going to beat Vegas by using data and machine learning.
Starting point is 00:33:51 And he's like, I'm just going to be Vegas. Like, I don't need to be Vegas to the world. I need to be Vegas to my dorm room. And I'll do just fine. It's the same mindset. It's so crazy. He's like totally clean cut like from Beverly Hills. I'm guessing from a Jewish family.
Starting point is 00:34:07 Great kid. And I'm like, hold on a second. You became a gambling, a degenerate gambler. Then you became a bookie. Then you started selling vice products like drugs. You became a drug dealer. Like, how did this evolution happen? So nuts.
Starting point is 00:34:25 He's checking all the boxes. I think I'm having him on the podcast at some point. Well, you'll probably release it before me. It's usually what happens. Bias for action. Awkward. Just got awkward. No, you'll like, you'll like his story.
Starting point is 00:34:38 I like it. Yeah, it was awesome. I'm stoked. You should be. All right. Hey, keep a sleazy. All right, what did you think? Please share it with a friend and we'll see you next time on the Kerner office.

There aren't comments yet for this episode. Click on any sentence in the transcript to leave a comment.