This Guy Built a $1.8B Company That Shouldn’t Exist

Growth Newsletter: https://levelingup.beehiiv.com/subscribe Need marketing help? Visit: https://www.singlegrain.com/ and https://npdigital.com/ Want to recruit great marketers? Find them here: https://marketingschool.io/hire Eric and Neil break down how one founder used AI and 800 fake doctor profiles to scale a GLP-1 telehealth business toward $1.8B in revenue, and why aggressive AI-powered marketing (done ethically) is the new edge. They unpack the Jevons paradox of skyrocketing AI infrastructure costs, the four levels of AI marketing maturity, the Ferrari vs. Honda model routing strategy to cut LLM spend, and why Chinese sentiment toward AI is wildly more optimistic than in the US. A sharp episode on building custom AI tools, scaling infrastructure, and adapting before the curve leaves you behind. Key takeaways ◾ One-person billion-dollar companies are becoming reality with AI ◾ AI infrastructure costs may soon rival headcount costs ◾ The four levels of AI marketing separate winners from laggards Chapters (00:00) The $1.8B one-employee AI company (01:52) ClickFlow AI content break (02:31) Tractor adoption and the AI jobs debate (04:30) Why AI token costs will skyrocket (05:47) Agents will transform corporations, not consumers (06:48) Mapping infrastructure scale for hypergrowth (09:05) Cutting AI waste with the Ferrari vs Honda model (10:52) The caveman prompt hack to slash costs (14:16) Building a company "single brain" with Nemo (15:39) Nvidia DGX Sparks and rising chip prices (16:20) The four levels of AI marketing (17:58) Custom tools vs off-the-shelf software (19:08) Alibaba funds real-world AI (19:40) China vs US: AI optimism gap (21:00) Why human content still wins for some customers

• 0:00Speaker 00

  Finding customer information shouldn't mean digging through emails, call notes, and spreadsheets. HubSpot's Starter Plan brings all of those details together, so it's easier to track what's happening with every deal and what to do next. It pulls information from calls and emails. Then it gets to work, logging and summarizing them. Right after your call ends, HubSpot pulls next steps from your call notes and drafts suggested follow-ups. And it stays up to date for you, so you can build demand, win more deals, and spend less time on repetitive work. Your records, insights, and next steps are ready for you to act on. And you don't have to miss a beat searching for any of it. Try the Starter Plan for $10 a month. Learn more at hubspot.com. This guy created 800 fake doctors to generate 1.8 billion in revenue with one employee, okay? So, this, this guy, um, this guy Matthew Gallagher, okay?

• 0:45Speaker 00

  So he made 800-plus Facebook accounts for fake doctors to advertise on Facebook and went on to build a GLP-1 telehealth company with just $20,000 to start with, AI, and only one full-time teammate, his brother. So it generated 401 million in 2025 and could reach 1.8 billion in 2026. So this is the guy over here, and then these are all that he's running. Uh, I don't think so. I mean, he, this GLP-1, uh, that he's doing, a lot of people are doing it. They're basically like affiliates for this GLP-1 company. And he's just going hard on the, the doctors. And he, he was responding to this. He was saying like, a lot of people do this. So I don't know if it's okay. He says a lot of people do it. I don't know if it's okay.

• 1:19Speaker 01

  I don't think that's okay, creating fake doctor profiles.

• 1:22Speaker 00

  Yeah.

• 1:22Speaker 01

  Typically, when you can make money in marketing that fast,

• 1:25Speaker 00

  Yeah.

• 1:25Speaker 01

  something's wrong.

• 1:26Speaker 00

  Easy come, easy go.

• 1:27Speaker 01

  Yes, and it's gonna get shut down, so, but if you made your money really quickly, great for you, but me personally, I wouldn't wanna do something unethical like create fake doctor profiles.

• 1:36Speaker 00

  I think we're gonna see more, maybe not exactly like this business model, but I think we are gonna start to see more one-person, uh, billion-dollar companies with one employee. Like, just, cuz he used AI to write the code, which isn't really that sophisticated. Produced the website copy, generate the, the, I really, I really think his main wedge was he pushed hard on AI ads piece cuz someone else on X responded saying, "I'm in this space as well. Everyone knows this guy. He's just super aggressive with the ads." Um, and that's what you need to do as an affiliate. You need to be hardcore. That's how the biggest affiliates win.

• 2:05Speaker 01

  Yes, but you also have to be careful cuz if you're super aggressive, you can get sued too cuz you're probably making claims. And promises that you shouldn't be.

• 2:11Speaker 00

  Yes, and so we're not saying you should do that, but I think we're saying be aggressive and you'll be able to do well.

• 2:17Speaker 01

  Or let me rephrase what Eric is really saying. He's not saying be aggressive from the aspect of creating false promises.

• 2:24Speaker 00

  Yes, don't do that.

• 2:25Speaker 01

  He's saying be aggressive with AI and have it help you scale up faster.

• 2:29Speaker 00

  Correct.

• 2:29Speaker 01

  Sorry for interrupting you.

• 2:30Speaker 00

  No, no, you're fine. And speaking of, because we're talking about AI right now, have you seen, I've been reading these CO2 charts. I think it's worth it for, I'm like, I really like how they do their charts. They have, their blog is just all these, you've seen these, right?

• 2:43Speaker 01

  Yeah.

• 2:43Speaker 00

  So, okay, this CO2 chart over here, those of you that can't see it, I'm going to explain it. Neil can re-explain it as well. So if you look from 1900 to 1960, this is the adoption of the tractor, okay? So the tractor decimated farm employment, but led to the greatest expansion in US history, okay? So when you look over here, you have 12 million agricultural workers in the beginning of 1900 and the manufacturing starts to take off, okay? And then this guy Keynes, who is the economist, we're being afflicted with a new disease of which some readers may not have heard the name, but which they will hear a great deal in the years to come. Namely technological unemployment, okay?

• 3:26Speaker 00

  So the tractor becomes widespread in 1917 and then what happens is you see agriculture, the green line over here continues to go down. All the way to 1970, so it goes from 12 million to 3.5 million, which is 2% of the workforce, from 41% to 2%. But what ends up happening, Neil, is employment actually goes up. So job displacement happens, okay, from this period, 1970 to 1940-ish, but it goes up over time, right? And that's the same thing with the bank, the ATM. The ATM, when it came out, people were like, oh my God, everyone's going to lose their jobs, blah, blah, blah. There's a period of time where like, sure, there's some job displacement, but after what happened? More banks, more banks opened, which created more employment. So I think short term, yes, fear. Long term, everything's going to be okay.

• 4:08Speaker 01

  I'm with you and I think Marc Andreessen talked about how um he believes that we're gonna see a massive boom because of AI. And I agree with that.

• 4:17Speaker 00

  Yeah.

• 4:18Speaker 01

  We're seeing it actually create more employment opportunities than it did before. Yes, it's also reducing employment, but you know, it's about how can you shift people from uh a job that can easily be replaced, retrain them and put them into something else.

• 4:31Speaker 00

  Here's what I'll say, Neil. Uh I don't, this is just my observations. I will say that, you know, um everyone on my team's a good person, right? I will say the interns are completely cracked out right now. Okay, so the interns are extremely hardworking, all in on AI. Okay, that's one piece. The second piece is the engineers and the product people, all in, okay? When you talk to them about this stuff, they're just working around the clock. They are working until they, their eyes hurt, right? Um and so I, I actually think, so my, my, uh, I have two Nvidia DGX sparks arriving today, so I'm gonna be working on that over the weekend. I think my token costs, even though I'm reducing it with this infrastructure, I think it's gonna go way higher because everyone's starting to use it like this. And so what's gonna happen is, I was, I was doing the math. I'm like, man, maybe even thirty-six months out, I'm gonna need the power of three hundred thirty-six H one hundreds from Nvidia.

• 5:16Speaker 00

  And by that time, it's gonna be something else, but I'm just, this thing's called Jevons paradox, Jevons's paradox. When electricity came out, people started to use it more. Internet came out, people started to use it more and more. AI came out, people were gonna wanna use it more and more. So our costs, it's, I think it's gonna skyrocket. It might even be equal to or more than our headcount costs.

• 5:35Speaker 01

  Yeah.

• 5:36Speaker 00

  Have you mapped that out yet for your company?

• 5:38Speaker 01

  No.

• 5:38Speaker 00

  I'm sure your people have.

• 5:39Speaker 01

  They may have. I have no idea honestly if they mapped it out or not.

• 5:42Speaker 00

  Yeah.

• 5:43Speaker 01

  I just, dude, it's just fascinating on how many things are changing so fast. Like, you're, we're coming to inflection point where AI

• 5:55Speaker 01

  is really useful in corporations in, because of agents. Everyone talked about agents and how they're gonna change consumers and, oh, they're gonna shop for you and do all this stuff. I think the big revolution with agents is not gonna be the consumer side. I actually think it's gonna be the corporate side. On the consumer side, yeah, people want an agent to be like their little mini assistant. But on the corporation Side, I think it's just gonna change the world on how businesses do work. But the hard part that we're seeing everywhere we go, dude, everyone wants to move 10 times faster now. We're not seeing people talk too much about like, hey, how do we cut costs? They're talking about, we need to do 10x more.

• 6:33Speaker 00

  Yeah.

• 6:33Speaker 01

  And that's the mentality that I think is the correct approach.

• 6:37Speaker 00

  That's the vibe. So like, one of my friends messaged me, he's like, so I wasn't even telling him to buy anything. I was just telling him what we're working on. And all of a sudden, he's like, the answer is yes, we need this. And so whoever, like, I think if you're working right now, you're like, man, there's not gonna be that much opportunity. I'm telling you, the opportunity is going to be insane for everybody. I think a lot of people are going to win. And I just, by the way, I've been mapping out these charts, Neil, check this out. So here's, here's the infrastructure scale. Check this out, Neil.

• 7:08Speaker 00

  This is the infrastructure requirements for single brain. If we experience hypergrowth, it goes like this in terms of how much infrastructure we need in the next 36 months. Aggressive is like this blue line over here. Conservative is like, it still goes up. But this shows how many H100 nodes I'm gonna need. And by that time, it's gonna be something else because the chips are advancing so quickly. We're probably gonna rent this infrastructure and you're probably gonna have to rent. So which is why I'm like, oh man, maybe we should buy CoreWeave stock. Not financial advice, but they have all the infrastructure. I think a lot of people are gonna be renting this stuff.

• 7:39Speaker 01

  Yes, sorry, my bad. Someone was texting me, they're like, you jacked a client from me. And I was like, I'm like, I don't know a client I jacked from you. I'm sorry. We have like a ton of people in our company.

• 7:51Speaker 00

  That's, do I know this person?

• 7:53Speaker 01

  Yeah, you know him and I know him and they're a good friend and I'm like.

• 7:55Speaker 00

  Oh, are they in Orange County?

• 7:57Speaker 01

  Yeah, they're in Orange County. And I'm like, I didn't jack a client from you. I'm like, dude, I don't know who the heck reaches out to me, you know?

• 8:03Speaker 00

  Yeah.

• 8:04Speaker 01

  So, but yeah, I was like, what can I do?

• 8:08Speaker 00

  What can you do?

• 8:09Speaker 01

  I can't. It's like, this is what happens when you have a company and people reach out. And then like, I get blamed for jacking a client when I didn't even.

• 8:16Speaker 00

  Oh, that means it's okay for me to poach from Neil. Just kidding, just kidding.

• 8:20Speaker 01

  No, you do whatever works for your business.

• 8:22Speaker 00

  No, I don't do that. That's screwed up. Remember, we have, we know someone that has done that to you multiple times. And that's not cool, because this person came to you for advice.

• 8:31Speaker 01

  That was employees.

• 8:32Speaker 00

  Yeah.

• 8:33Speaker 01

  No, no, but this person didn't, he's pissed off that

• 8:35Speaker 00

  I know, I know.

• 8:36Speaker 01

  That I took his client, but I didn't reach out to his client.

• 8:39Speaker 00

  I kind of look at them in similar veins, right? Like, you just don't do that. But like, in your case, like, this is not something you were, like, aware of. Like, if you were aware of, you wouldn't have done it. This person willingly did it to you on the employee side, right?

• 8:51Speaker 01

  Yes.

• 8:51Speaker 00

  So, yeah. But by the way, this is, this is maybe rosy, but it shows how revenue scales and infrastructure scales. The revenue is the blue. So, it scales a lot faster than the infrastructure cost. So I'll pay for this all day.

• 9:04Speaker 01

  Yeah.

• 9:05Speaker 00

  Yeah. Anyway, you can pick.

• 9:06Speaker 01

  I'm just, I'm just hoping all these costs start going down, because we're starting to see our financial bills, or, you know, our, we had an internal meeting about reducing our AI costs, like, it's getting out of hand.

• 9:17Speaker 00

  But why would you reduce it if it's, you're paying for intelligence that can do more for you, and the costs are going to continue to come down?

• 9:22Speaker 01

  Not necessarily.

• 9:25Speaker 01

  Just because AI is going to be more efficient, and just because the costs for using these platforms and technologies is going to come down, there's efficient ways to use it, and there's inefficient ways to use it.

• 9:35Speaker 00

  That you should reduce.

• 9:36Speaker 01

  Yes. And when we look at how some of our team members are using it, there's much more efficient ways where they can be using it, and your costs go down drastically.

• 9:45Speaker 00

  Yeah.

• 9:45Speaker 01

  Like, dude, you know, this, there's a lot of things you can do on-premise on your own machines or buy machines, and it's just way cheaper than paying some of these guys money. So it's just like, okay, do we wanna, do we wanna end up putting in all this effort to set up our own machines? And I'm like, yes, because we're spending so much money on a monthly basis. I'm like, the recuperation time is not years. It's really quick, like, a month or two. This is like, just pay for this.

• 10:13Speaker 00

  Quick break. Look, I know what you're thinking. Another AI content tool, great, more garbage content on the internet. And I thought the same thing. That's why we spent years building Clickflow differently. Here's actual feedback from a user. It's sophisticated, grounded in real language. Authoritative but not academic. You hit the sweet spot. That's not AI slop. That's content that you would actually publish. Clickflow also helps with things such as internal linking, building FAQs and reporting on the content performance. If you're skeptical, you can just go to clickflow.com and try it for free for 14 days. And if it sucks, just cancel. But I don't think you will. Back to the show. I'll explain it this way, like, so here's how we save on AI right now. So the way we save on AI is 15% is Ferrari cost, okay? So you have Ferrari models, which is like the Frontier models.

• 10:57Speaker 00

  And then the other 85% is Honda Accord budget, okay? So that's where you like, that's a daily beater that you use to go get your groceries or whatever. So most of the time, your people are asking like, like normal questions, like basic queries, like going back and forth. Maybe sometimes I might ask the stupid questions. That goes in 85%. The 15%, the Ferrari budget, that goes into you actually having the model think for you and code for you, okay? And that, that's how our infrastructure is like, the, the cost is breaking down right now. And you might use tools like Open Router to route to the right model and that'll save you more on cost. They'll charge you like 5% or something. That's pretty good. But also, you know what you can do with your model? Here's the hack. If you tell your model to speak like a caveman, that saves you a lot on costs. So it was like, me code this now, me need this.

• 11:39Speaker 00

  Frictionless Growth Marketing hosted by Sonya Thompson is brought to you by the HubSpot Podcast Network, the audio destination for business professionals. Frictionless Growth Marketing hosted by Sonya Thompson shows how modern brands grow by removing the friction in their marketing and customer experience that pushes customers away every single day, often without leaders even realizing it. Each episode delivers practical insights, real brand examples, and conversations with marketing leaders showing brands how to win with the new rules of growth, identity-driven marketing, cultural relevance, and frictionless customer experiences. Listen to Frictionless Growth Marketing wherever you get your podcasts.

• 12:16Speaker 00

  I'm not even joking, like, it's, it's cuts down like 50 to 70% of costs. I'm not even joking. Yeah.

• 12:22Speaker 01

  It probably is.

• 12:24Speaker 00

  Yeah.

• 12:24Speaker 01

  I haven't actually looked at the breakdown, but it probably really is.

• 12:27Speaker 00

  Yeah. So like-

• 12:28Speaker 01

  And then what do you think of the outputs? I don't think people are getting the outputs they really want, but they're burning the money.

• 12:33Speaker 00

  Oh, okay, I have an example. So there's, there's this gal, Clairvo, that, that shares this on her, her Twitter. So she, her open call is full caveman right now. So here, check this out.

• 12:46Speaker 00

  Oh my god, she tweets a lot. Okay, here we go. Check this out. Need find files, need maybe scripts in another dir hidden, directory hidden grep. Need locate script, maybe grep with find plus grep. Need likely there is another script for mention monitor generating worth engaging. Maybe system uses X search. Search worth engaging.

• 13:04Speaker 01

  What we're starting to analyze on our end is how much are people using internally? What's the output that they're getting? And how much of the output do they actually use? Because there's a big problem right now, at least what we're seeing in marketing departments. Yes, people are using AI. Yes, there are some efficiencies to be had and you can say you can save on employees or whatever, but you're paying these LLMs and it's not cheap. And what you're finding is people are using them for whatever they want. And a lot of the stuff that they're using AI for, A, they may have not needed to use in the first place. And B, the outputs that they were created,

• 13:43Speaker 01

  they aren't using it because they weren't happy with it. But sometimes they are using it, sometimes they're not. So if you start looking at the wastage and how much money you're spending on that, it's adding up for like big companies to be millions of dollars a year. And you know me, I go through credit card statements line item by line item and expenses. And I'm like, dude, they're just waste. How do we cut the waste?

• 14:04Speaker 00

  Dude, the good news now is we started getting paid for a sponsorship. So that's why you're not getting bills for a while. So for this stuff.

• 14:12Speaker 01

  We have been for a while now.

• 14:14Speaker 00

  No, they just started paying. We just got the first payment.

• 14:17Speaker 01

  Oh, but we were doing it for a while. We just started receiving the checks is what you're saying. But before then, dude, we had sponsors for a while. Did she ever pay up on all the other stuff? Or did the other company ever pay up on the other stuff?

• 14:27Speaker 00

  We didn't get that much. It came over to cover our costs. We didn't get a lot. We got like, like she would send us like payments for like $10 sometimes.

• 14:37Speaker 01

  But I thought we were doing all these sponsorships and she's like, look at all these contracts that I got you.

• 14:40Speaker 00

  We were declining a lot. We just didn't want to do these things. Yeah, it was stupid. So, but we did like, we did cover all of our costs going through her. We didn't make a lot though. Which is why we came off of it.

• 14:50Speaker 01

  It was a terrible deal because her people promised the world.

• 14:53Speaker 00

  Yeah.

• 14:53Speaker 01

  And they didn't deliver on much.

• 14:55Speaker 00

  I'll say about them, then I want to come back to what you're saying too. And I'm starting to forget what you're going to say too, but like, um, what were you just talking about before I cover that? AI costs. Okay, so we'll come back to AI costs. So, um, so the partnership, so what had happened, Neil, was I was talking to a bunch of people and a lot of people had a lot of followers. And even when I talked to the HubSpot team, that team, like when they heard about this, um, this team, they're like, oh, like, I'm like, why do you, why are you guys reacting like that? It's like, it's, it's not good to work with it. Like, and everybody I've talked to, it's like, it's not good to work with these people. So we tried it, didn't work out. You know, we have our own experiences, but we'll leave it at that. So AI costs. So on the AI cost side, what we're doing is, um, one of, um,

• 15:34Speaker 00

  because we're putting everything into Nemo Claw, right? Which is the enterprise grade version of Open Claw. And, um, we're saying, okay, we want it, we want the agents to help with performance intelligence, which is where it will coach people. Okay. It will see how they're using it, how they're asking questions, um, how often they're asking questions, how, how it's, how, how it's getting coaching and all that. And how productive they're being with this in general, right? So, you know, in my mind, I'm like, okay, if you have this world intelligence, this single brain, and I think every company needs a single brain. Every, if you have the single brain, it understands the entire company, all of the goals, and it's, it works with every single person, it coaches them up as well. Then everyone should grow. And then also it's like, okay, based on how you're working with all these, these people, what, how, in what ways are we using this in a stupid way?

• 16:15Speaker 00

  And how do we save on costs? And then you can have the agent itself improve on saving you money. That's how I look at it. Because I'm constantly asking, there's a, there's a command, Neil, called slash cost. You would run this all the time. It just tells you how you're spending your money and how to optimize it.

• 16:30Speaker 01

  Yeah. I didn't know Nemo Claw was out already, the Nvidia one. It's already out. Yeah. When did it come out?

• 16:36Speaker 00

  Like a month? Like, when, when he released it, it was already like coming out.

• 16:40Speaker 01

  Oh, got it. I heard the announcement. I didn't know that it was already out.

• 16:43Speaker 00

  Yeah. So that's why I have Nvidia infrastructure. I'm like, oh crap, I need to buy a lot of more of these DGXs.

• 16:49Speaker 01

  Nvidia is just, their chips are so expensive.

• 16:52Speaker 00

  Yeah. So I, just for two of them for myself, it costs 10 grand for, for, and here's the crazy thing, Neil. These DGX sparks, originally they were, um, $3,900. Now they're 4,700. So I think the pricing on these is gonna continue to go up.

• 17:08Speaker 00

  Over time.

• 17:10Speaker 01

  Yes, I think they're gonna go up. Over time, I think you're gonna continually see costs.

• 17:14Speaker 00

  And it's the weirdest thing to me, Neil, because when I was nine years old, I bought an Nvidia chip. I bought a GeForce for my computer, because this was during the internet boom and during the gaming boom, okay? Thirty years later, I find myself buying Nvidia chips again during another boom. So, everything kind of comes full circle.

• 17:30Speaker 01

  Yeah. So, what else do we have on? Oh, the four levels of AI marketing. I was curious on this one, I haven't read this one yet.

• 17:36Speaker 00

  So, this one is from Anthropic's single employee. Remember, they had that single growth marketer? So, he has mapped out the four levels of AI marketing use. So, most people sit at level one, automating what they already do. So, level one, Neil, automate what you already do. So, reporting, copy, data pulls, like using it at a pretty rudimentary level. That's level one. Level two is you use AI as a thinking partner where it's better than you, okay? So, you might ask about tax situations or tax laws. I might ask about those as well, right? Or I might ask about, you know, certain implications around doing work, right? Level three is do work that was below the ROI threshold before. So, an example of that might be performance intelligence, which I just mentioned. Like, it's too much work to have to say, oh, Neil, how did you? What questions do you ask today? How'd you work? How'd you use your token today? Da, da, da, da, da.

• 18:21Speaker 00

  You couldn't do that before. This work is now all doable, right? A lot of these edge case scenarios, you can do now. Level four, build custom tools only you would ever build, okay? So, level three is work that never existed before. So, stuff nobody did because the manual cost was never worth it. So, mining negative keywords across every ad group, checking your full site for broken links daily. Same logic applies to content research, QA, competitor monitoring, and work that existed in theory, but nobody had the hours for, which is kind of how we're using our thing for. Level four, which we just talked about, is where the ROI compounds. So, there are hundreds of AI marketing skills and plugins floating around GitHub right now. Most of them work in theory, but fall apart in practice because they are built for general use cases, not your case.

• 19:03Speaker 00

  Your business has specific data, specific workflows, specific edge cases, that no generic tool will ever cover. The people building custom tools around their own problems are the ones pulling ahead, which is similar to what Ramp is doing with Glass. They don't want to use any off-the-shelf software. They're building it for their solution. Their single brain version is that we have our own single brain version, and then we're working on selling that. But I think every company has their own institutional AI that they need to have.

• 19:28Speaker 01

  I believe you level one, the automate what you already do, reporting, copying, data pulls, etc. I don't think people will be using the L L Ms directly for that. I believe they're gonna start using most of software companies for that, cuz it'll just be cheaper and more efficient.

• 19:42Speaker 00

  I think they're gonna be using a lot of these Chinese models, I'll tell you that much. So the Chinese models are really good.

• 19:47Speaker 01

  And they're really cost effective.

• 19:48Speaker 00

  Quinn, Kimmy, uh, they're all amazing. A Gemma, even from Google, Gemma's amazing. You can run it on like a crap computer and it's amazing.

• 19:56Speaker 01

  Yeah, but I, I, I really do believe people are just gonna pay for the software solutions.

• 19:59Speaker 00

  Yeah.

• 20:00Speaker 01

  Cuz some of these software solutions are like ten, fifteen bucks a month, or even freemium. And it's just cheaper to do that cuz they'll perfect it for that specific task or the, those marketing functions that you have.

• 20:11Speaker 00

  Yeah.

• 20:12Speaker 01

  And it's just easier than you having someone internally using A I to do it and maintaining it and making sure it's doing it accurately. Uh, did you see the Alibaba news, how they're funding a real world version of A I?

• 20:24Speaker 00

  No.

• 20:25Speaker 01

  So Alibaba, I believe, funded two hundred and something million dollar, uh, round with a Chinese A I company. Where it's deciphering what's happening in real world and videos and all of that kinda stuff to make A I way more sophisticated. So instead of just text based, it's trying to analyze real world stuff based on how we interact as humans.

• 20:45Speaker 00

  Yeah.

• 20:45Speaker 01

  Cuz the way you read text is very different than how a human interacts with each other in person or through video.

• 20:50Speaker 00

  Yeah. Dude, this is funny. Okay. So you're, you're talking about this, right? Like, you just got me to think about how crazy people, I'm, I'm Chinese, right? So, look, so people in China, they're all lining up in public for Open Claw, to learn Open Claw. I don't see any of that happening in America. Where's that happening right now? Right? Like, th- th- this is like embedded into our culture. It's like, oh, you're gonna make money for it? We're gonna line up for this stuff.

• 21:14Speaker 01

  What's interesting is the narrative in the U S is there's gonna be a lot of job cuts, A I's gonna create a lot of displaced.

• 21:20Speaker 00

  Bad, it's so negative.

• 21:22Speaker 01

  Yes.

• 21:22Speaker 00

  Yeah.

• 21:22Speaker 01

  In China, I've seen, and all the articles I've read, it's actually a very positive sentiment. People don't worry about job displacement. They worry about, hey, how can I learn all this stuff and adapt so then that way I can be better for the future?

• 21:35Speaker 00

  So let me give you the numbers here, Neil, cuz we like numbers, right? So Chinese public sentiment towards A I is significantly more optimistic and trusting compared to the U S. What do you think the number is percentage wise, optimism in China?

• 21:46Speaker 01

  Ninety plus percent.

• 21:47Speaker 00

  Close, eighty percent. That's, that's like having pocket aces, okay? Like, you're, you're good, right? Now. What do you think it is in the US?

• 21:55Speaker 01

  10%.

• 21:56Speaker 00

  35%. Because you and I are pretty, I think Noah is pretty optimistic about it too. I am optimistic about it. I'm like short-term doomer, long-term optimistic, right? Which is like, it's, a lot of it's politicized here. It shouldn't be politicized. This is like, intelligence in your hands.

• 22:11Speaker 01

  Wait, you know, Noah, this just made me think. You have a business where you pay people to help you create content. Why don't you just use AI?

• 22:19Speaker 00

  How could you not have thought about this already?

• 22:20Speaker 01

  And AI just create the content. No, no, for him, for his business.

• 22:23Speaker 00

  I know, but how could, this is obvious to me like in the beginning.

• 22:26Speaker 01

  Yeah, but he's not doing it.

• 22:28Speaker 02

  The, the difference is that the customers don't want that.

• 22:32Speaker 00

  They don't want AI.

• 22:33Speaker 01

  Really?

• 22:34Speaker 02

  My, I would have to get a whole new set of customers.

• 22:35Speaker 00

  See, this is like our customers that want manual content only. Human, human-generated content, human-generated content.

• 22:42Speaker 01

  Yeah.

• 22:43Speaker 02

  So it's just, yeah, it's a future path, but it's.

• 22:46Speaker 00

  I think it depends on the user, because there are customers, there's a dot AI for that with the word, okay? And they, they do well, right? Yeah, I, I think it, it depends, Neil.

• 22:56Speaker 01

  Yeah.

• 22:56Speaker 00

  Yeah.

• 22:57Speaker 01

  Yeah, I, I can see it. We work with a lot of companies and even my own company, I don't want AI content for my own business.

• 23:04Speaker 00

  Dude, look at this. And now I'm gonna move over to the next thing. So look, they're, they're literally in the park, okay? You have people in China in the park, they're all like huddled over like these laptops. People are on their phones, they're all trying to learn open call. I bet you this is during the weekend too. How do you beat this?

• 23:20Speaker 01

  Society-wise, it's really tough.

• 23:22Speaker 00

  They're just, they're all hungry.

• 23:23Speaker 01

  Majority of the people here that I've met are not that hungry, sadly.

• 23:28Speaker 00

  I bet you they're like this in India too, your, your people.

• 23:31Speaker 01

  Yeah.

• 23:31Speaker 00

  So that is it for today. Please don't forget to rate, review, subscribe, and we'll see you tomorrow.