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

0:00Eric Siu: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. So he made 800 plus Facebook accounts for fake doctors advertised on Facebook and went on to build a GLP one telehealth company with just$20 ,000 to start with AI and only one full time teammate, his brother. So 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 the assets running. I don't think so. I mean, this GLP One that he's doing, a lot of people are doing it. They're basically like affiliates for this GLP One company.

0:36Eric Siu:And he's just going hard on the doctors. And 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.

0:45Neil Patel:I don't think that's okay. Creating fake doctor profiles. Typically, when you can make money in marketing that fast, something's wrong. Easy come, easy go. Yes, and it's going to get shut down. But if you made your money really quickly, great for you. But me personally, I wouldn't want to do something unethical like create fake doctor profile.

1:02Eric Siu:I think we're going to see more, maybe not exactly like this business model, but I think we are going to start to see more one person, billion dollar companies with one employee. Like because he used AI to write the code, which isn't really that sophisticated. Produce the website, copy, generate the. I really think his main wedge was he pushed hard on the AI ads piece because 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. And that's what you need to do as an affiliate. You need to be hardcore. That's how the biggest affiliates win.

1:31Neil Patel:Yes, but you also have to be careful because if you're super aggressive, you can get sued too because you're probably making claims and promises that you shouldn't be.

1:37Eric Siu:Yes. And so we're not saying you should do that, but I think we're saying be aggressive

1:41Neil Patel:and you'll be able to do well. Or let me rephrase what Eric is really saying. He's not saying be aggressive from the aspect of creating false promises. Yes, they do that. He's saying be aggressive with AI and have it help you scale up faster.

1:55Eric Siu:Correct. Sorry for interrupting. No, 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. I'm like, I really like how they do their charts. Their blog is just all these, you've seen these, right? Yeah. So, OK, 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. OK, so the tractor decimated farm employment, but led to the greatest expansion in U.S. history. OK, so when you look over here, you have 12 million agricultural workers in the beginning of 1900 and the manufacturing starts to take off.

2:34Eric Siu:OK, and then this guy Keens, who is the economist, we are 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. OK, 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 percent of the workforce from 41 percent to 2 percent. But what ends up happening, Neil, is employment actually goes up. So job displacement happens, OK, from this period, 1970 to 1940 ish.

3:14Eric Siu: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 sure, there's some job displacement, but after what happened, more banks opened, which created more employment. So I think short-term, yes, fear. Long-term, everything's going to be okay.

3:34Neil Patel:I'm with you. And I think Marc Andreessen talked about how he believes that we're going to see a massive boom because of AI. And I agree with that. We're seeing it actually create more employment opportunities than it did before. Yes, it's also reducing employment, but it's about how can you shift people from a job that can easily be replaced, retrain them and put them into something else?

3:57Eric Siu:Here's what I'll say, Neil. This is just my observations. I will say that, you know, everyone on my team is 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 their eyes hurt. Right. and so I actually think I have two NVIDIA DGX Sparks arriving today so I'm going to 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 going to go way higher because everyone's starting to use it like this and so what's going to happen is I was doing the math, I'm like man maybe even 36 months out I'm going to need the power of 336 H100s from NVIDIA and by that time it's going to be something else but I'm just, it's things called Jevin's Paradox when electricity came out people started using more internet came out people started using more more ai came out people are going to want to use it more and more so our costs it's i think it's going to skyrocket it might even be equal to or more than our headcount costs yeah have you mapped

5:02Neil Patel:that out yet for your company no i'm sure your people have they may have i have no idea honestly if they mapped it out or not yeah 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 is really useful in corporations because of agents everyone talked about agents and how they're going to change consumers and oh they're going to shop for you and do all this stuff i think the big revolution with agents is not going to be the consumer side i actually think it's going to be the corporate side on the consumer side, yeah, people want an agent to be like their little mini assistant.

5:42Neil Patel:But on the corporation side, I think it's just going to 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.

5:59Eric Siu:And that's the mentality that I think is the correct approach. That's the vibe. So like one of my friends messaged me, he's like, 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 going to 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 um and i just by the way i've been mapping out these charts neo check this out so uh here's here's the infrastructure scale check this out neo

6:33Eric Siu:this is the infrastructure requirements for single brain if we experience hyper growth 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 going to need and by that time it's going to be something else because the chips are advancing so quickly we're probably going to rent this infrastructure and you're probably going to have to rent so which is why i'm like oh man maybe we should buy core weave stock not financial advice but they have all the infrastructure.

7:01Eric Siu:I think a lot of people are going to be renting this stuff.

7:05Eric Siu:Yes.

7:06Neil Patel:Sorry, my bad.

7:07Eric Siu:Someone was texting me.

7:08Neil Patel: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.

7:17Eric Siu:That's, do I know this person?

7:19Neil Patel:Yeah, you know him and I know him and they're a good friend. Oh, are they in Orange County? 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?

7:29Eric Siu:Yeah.

7:31Neil Patel:So, but yeah, I was like, what can I do? What can you do? 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.

7:42Eric Siu:Oh, that means it's okay for me to poach from Neil. Just kidding. Just kidding. No, you do whatever works for your business. No, I don't do that. That's, that's screwed up. Remember, we, we have, we know someone that has done that to you multiple times. And that's not cool. Cause this person came to you for advice. and was your friend. That was employees. Yeah.

7:59Neil Patel:No, no, but this person didn't. He's pissed off that I took his client. I know, but I kind of look at them

8:05Eric Siu: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? Yes. So, yeah. But by the way, 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. Yeah.

8:30Neil Patel:Yeah. Anyway, you can pay for it. I'm just hoping all these costs start going down because we're starting to see our financial bills or we had an internal meeting about reducing our AI costs. Like it's getting out of hand.

8:42Eric Siu:But why would you reduce it if you're paying for intelligence that can do more for you and the costs are going to continue to come down?

8:48Neil Patel:Not necessarily. Just because AI is going to be more efficient And just because the costs for using these platforms and technology is going to come down, there's efficient ways to use it and there's inefficient ways to use it. That you should reduce. 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. Like, dude, you know this. There's a lot of things you can do on premise on your own machines or by machines. And it's just way cheaper than paying some of these guys money. so it's just like okay do we want to do we want to end up putting in all this effort uh 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

9:38Eric Siu:just pay for this 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 how 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've 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.

10:10Eric Siu:And if it sucks, just cancel. But I don't think you will. Back to the show. I'll explain it this way. 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. 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 normal questions, like basic queries, like going back and forth. Maybe sometimes I might ask some stupid questions. That goes at 85%. The 15%, the Ferrari budget, that goes into you actually having the model think for you and code for you.

10:44Eric Siu:Okay. and that's how our infrastructure is like 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's like me code this now. Me need this. I'm not even joking. Like it's like 50 to 70 % of costs. I'm not even joking. Yeah.

11:13Neil Patel:It probably is. I haven't actually looked at the breakdown, but it probably really is. 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.

11:24Eric Siu:Oh, here, I have an example. So there's this gal, Claire Vo, that shares this on her Twitter. So her open call is full caveman right now. So here, check this out. Oh my God, she tweets a lot. Okay, here we go. Check this out. Need fine files.

11:55Neil Patel: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, they aren't using it because they weren't happy with it.

12:36Neil Patel: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?

12:55Eric Siu: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.

13:03Neil Patel:We have been for a while now.