Brutally Honest Advice For Someone Trying to Make Money with AI

Everyone is telling you that AI will make you rich. Buy this tool, use this prompt, be a millionaire by next week. But it's all bullshit. I've built and scaled dozens of AI companies to over $1 million in less than 6 months through my company Martell Ventures. I work with founders building AI companies every single day, so I've seen exactly what makes people money and what makes them fail. So in this video, I'm going to give you the 5 truths on how to actually get rich with AI that no one will tell you. Starting with truth number 1: AI won't make you rich. Here's the way you need to think about it. AI is like a hammer, and without a nail to hit, then essentially you're just whacking at a wall for no reason. So if AI is just a tool, then how do we make money with it? AI hasn't changed what makes you rich. You get rich by solving problems. It's just changed how fast you can get there. But the fundamentals haven't changed. You still need to know how to apply AI. Focused operators with real skills that know how to do shit. With AI, it makes them unstoppable. Having no focus all over the place with no real skills that's valuable, AI will just burn you, burn your bank account, cost you to waste a lot of tokens. And right now I'm seeing a lot of businesses that are spending money on AI that haven't seen any of that come back in income. If you have a business, it can help you grow faster, but it can also help you get broken faster. So if AI is just a tool to make money, then how do you make sure you actually make money with it? Truth number 2, AI isn't the problem. Nobody woke up today and said, "I need more AI. Who got AI? Can you sell me some AI?" Nobody woke up and said that. They woke up and said, "Oh, this is a fucking problem still. Why is this still an issue? This sucks." They have a problem. The question to ask isn't, "How do I use AI in my business?" It's to ask, "What problem do I even solve in the first place?" When AI can solve every problem out there, And it can. The problem to solve is knowing what problem to solve. Remember the nail and the hammer? So now you know you need a nail, a problem. Now you need to figure out what nail is the right one to hit. Here's a framework that I like to use called the GAIN Matrix. Essentially, you have things that are easy for computers, hard for computers, hard for humans, easy for humans. And that's why we want to focus on the things in the top left corner. Okay? That is the give. And with give, these are all the things that you could do. It'd be easy for you to do. Think about it. All the stuff like data entry and research and all these small little things that you could do that most people don't give up because it's not that hard. I always look at this as the first place, like nobody should be doing this in the world of AI. So this is the things like data entry, right? We've got other things like simple calculations. So the next one is accelerate. This is where it's hard for humans but really easy for computers. This is where real leverage gets created. This is where I think about buy back my time. That's where I'm looking. These are tasks that would take hours and AI does it in minutes. And some examples are deep research, right? Like giving it a bunch of documents and being like, find me the pattern in this, right? Or you have data analysis. I do this all day long where I'm looking at information, data points, research reports. Like I need to find the pattern in the data. The next part of the matrix is about integrate. And this is where you take hard for computers and hard for humans and you collaborate together and you create new things that otherwise you couldn't do. Think about like creative tasks. Like yeah, you can get it to create a bunch of Facebook ads, but without a human you wouldn't be able to know what's a great one. And then you need to collaborate to have the volume to be able to see it. Oftentimes when I'm working with AI, I can't tell you what I'm looking for, but I know it when I see it. So think creative tasks. The other one is like innovation, right? Like when I'm building new companies, oftentimes I need to see the whole thing. The AI gives me options, but me and my team, we look at it, we go, oh, boom, and you feel it in a meeting. Have you ever felt it where you're like, oh yeah, that's awesome, right? Or even strategy. Okay. And strategy for me is sequencing. It's not about the right thing. It's about doing the right thing in the right order. And oftentimes that's hard for me even to know what are the pieces. AI can do that. It's hard for the AI to know what sequence because it doesn't have the sensibility of a human. And together we co-create the right sequence of strategy. Last but not least, we have hard for computers but easy for humans. This is where we go full freestyle, full old school called no AI, right? Because AI isn't what is needed. When you have problems in that quadrant, show up. I can't tell you the amount of times people think, I'm just gonna hide behind my keyboard and get AI to do this for me. No, this is where the humanity shines. This is where things like EQ, emotional intelligence, it's what's needed. Guess what? AI can't tell you if the joke's any good. AI can't even deliver the joke. AI can't deal with conflict. AI can't deal with leadership. AI can't understand the complexity of the human experience to be able to resolve situations. I spend my whole day doing things AI can't do. AI gives me more bandwidth. Using these quadrants, I'm able to move faster, but AI doesn't have my intuition. AI doesn't have my vision. AI doesn't have my taste. It doesn't have the care that I have. It doesn't, it doesn't know how to show up for people. And that's what you gotta think about. Like things like EQ, emotional intelligence. This is what I teach my kids. Leadership. How do you show up for your team? They're not listening to an AI and being led by an AI. Sure, they'll follow tasks, but being inspired, that's a human thing. Intuition, resolving conflicts, understanding how to communicate when emotions are involved. So think about all the tasks you do and place them in this matrix. That's how you know how to use AI for each specific problem. Now, each one of these problems are essentially all different kinds of nails, screws, thumbtacks, and they all require different tools. So if you're a business owner with a team and you want to get everyone using the right tools on the right problems, I've got my free AI tech stack for companies trying to get to the next level. If you want it, go find me on Instagram and just DM me the word YouTube stack and I'll send it right over. Now, I know what you're thinking. I figured out the problems to solve. Now, how the fuck do I use AI to solve them? Truth number 3: Don't use AI. I know! Who abducted Dan? Why is this guy here? I thought, I thought you were the AI guy. I can't tell you how much I hate when people default to AI when they should just go figure out the simplest step to solve the problems. See, you need to understand the context. You need to understand the steps, what works and what doesn't before you ever introduce AI. My favorite story to tell is listening to any time Elon Musk has run into an issue And he says, I just went down to the place where the issue was. I looked at it with my own eyes. I sat back, I analyzed it, and then I decided what needed to be solved. I didn't run to an AI and do a simulation and figure out a whole model. AI is like fuel. It can be used to power an engine to move things faster, but it can also blow up in everybody's faces. Broken systems with AI thrown on top of it will burn bright. Solid systems, you put in some AI will power a rocket. When people come to me and they're like, I wanna build some software to solve a problem, I'm like, AI can help you write the software, but first figure out if there's a problem to solve. So my favorite thing to do is launch a page, have people sign up for a waitlist, talk to them if they have the problem. Then they go, yeah, I have the problem. Cool. Manually solve it. It's called Wizard of Oz, where you, you're behind the scenes, you onboard the customer, you look at the data, you answer it, you give it back to them. They think it's AI, it's not, it's a person. And because of that, you're not worried about the technology to solve the problem. You're wondering if the problem is solved the way the customer wanted it. It's a way to pre-validate before you sit there and burn a ton of tokens spending tens of thousands of dollars trying to build a prototype before you even know if anybody's going to use it. I got a lot of friends that have been doing this lately and they call me up, they say, hey, Dan, you want to see my prototype? I go, that's cool. Where's the customers? You learn so much more having real customers pay you real money to solve their problem in a real way. They might think it's AI and then Eventually you can use AI to build the solution that they're already used to. So this is exactly what you have to do before you start implementing AI. First, solve the problem manually. I'm talking with your fingers, I'm talking with your feet. If you gotta go out and do something, do that. Deliver the service yourself. That way you can understand the whole workflow. Second, document what's working. Create a process, create a checklist. In real time, as I'm simulating the solution, I'm writing down the steps that made the thing happen. That way, if I go to build software, I have the specs. I actually wrote it out already. The AI can take that and build something. The third, and only once you do 1 and 2, do you go to an MVP, what's called a minimum viable product. And this is the most basic version. This is almost sometimes like it kind of works, maybe the heavy lifting doesn't, but it's the most basic version using AI. And then the last step is we gotta scale. Once we know the customers want, we document the steps and we've built an MVP, then we feed the playbooks into AI, then it can deploy the agents, then it can build the code, then it can manage the whole process. And that's how we scale. But that's the last step, not the first step. Most people start at step 4, go back to step 1 and work your way through it. So now you know that AI is just a tool. You know that solving real problems is where it's at and how you get rich. And you know you need to understand the process before adding AI to your business. Now you're probably thinking, how do I scale this? Truth number 4: AI does not replace people. Everyone in the future, if they choose to work, will be an agent operator. Everything in the future business will change things from today being a role-based org chart to a workflow-based org chart. So for example, creating a YouTube video. The traditional way, okay? One person for each one of these roles. Think creative director to come up with the strategy, scriptwriter, you've got an editor, you got a thumbnail designer, and then you need somebody to post the video. The agentic way, which is the agent on the loop, is one person owning the workflow. That's where it's changed. And then the agents, each one of them own each role within that workflow with the person making sure that the whole process is being managed. So humans will own workflows, not roles anymore. That's the difference. My philosophy is that AI should make your team 10x better, not replace them. If you have to lay people off because of AI, that's a leadership problem. That's a leader that didn't see where the world's going, didn't upskill their team, didn't get them ready for this. And now that you're watching this, get ready yourself. Do you think companies would rather have a person with 10 AIs or 10 people with one AI each trying to coordinate all the mess? You want to talk about token maxing? You're burning massive tokens with 10 people. In 10 systems. I believe in this so much. A few weeks ago, I shut down my company for 2 whole days and I taught every single person how to code. And we ran a contest for 2 days and did a hackathon. And at the end of it, we had dozens of AI tools that people built to essentially replace themselves. They realize if they don't do it to themselves, somebody else is going to do it. They want to be the person that manages the system. They don't actually need to be the person doing the work. So you still need people with AI. So the question should be, who do you look for when you're hiring? Okay, so try this. I call it the AI role audit. So just draw a T-chart just like this. On one side, write AI, okay? And on the other side, write human. Follow along at home, I'm watching. Think of all the tasks that need to get done for a specific process to actually get done. On the AI side, what are the tasks that AI can do? On the human side, what are the tasks that only a human can do? For example, on the AI side, you can do planning, right? I sat down this morning with my assistant. We did some massive planning. You can do research, right? You can have copywriting, you can create ads, you can do emails. You can do analysis of the workflow. Okay, what else can AI do? Communicate. Okay, I have my AI process all my Slack messages, all my email, route things, manage things. All these things used to take me days a week. Now it takes me minutes and I'm the human on the loop making sure that they happen. On the human side, this is very special because now we go to what can only you do. That's where you have ownership. Okay? This is where you essentially own the workflow. This is the person says, I am accountable for that output. The AI is not accountable. Guess what? No AI is going to jail. Human will. I think about vision. You know, vision is having a belief about the future that doesn't exist yet that should. Okay? And that is a human thing to create. Then we have taste, right? My buddy Hollis says it best. He goes, taste isn't something you can buy, has to be learned. That's a human thing. We have directing, directing other humans. Look, AI is starting to do this, but really talented people are not going to sit back and be directed by a computer or a robot. They're going to want to have a relationship with somebody that they trust, and then they're going to use the AI to scale their output. We've got decision-making, right? This is strategy. This is sequence. This is being able to overcome problems. So when you're hiring, you need to make sure that the person knows how to do these things, the human stuff, all the AI stuff. These are like skills you can teach somebody. Most of them you don't have to do anymore. But does the human know how to manage the AI? That is the agent operator. And those are completely different skills. And if you have a team already, I would encourage you to look at every role that you have and figure out how do you upskill them? How do you get all their stuff done by AI? Train them on the soft skills so that they become better humans, better interactions. The person that used to get paid a lot of money to manage ads and sit in the basement and not talk to anybody, that person now needs to show up on the team, let the AI do the ad buying, and they need to be there and have vision and taste and care about people. So this is the shift. Stop asking, how do I replace my team with AI? And start asking, how do I use AI to make my team unstoppable? Truth number 5: Humanity is the advantage. Here's the thing. AI is not going to take your job, but somebody else well integrated with AI will take your job, will take your business, will compete against you. AI is reshaping everything, but the fundamentals of building a business has never changed. Customers have problems. They want the problem solved. Bigger the problem, bigger the business. The more elegant and beautiful and interactive the solution, the more the customer is going to love you. AI doesn't replace humans, it just removes what's been keeping them apart. The more you integrate it into your business, the more human your business can show up. You leverage AI to help move faster, and that's the only way you can really get rich with AI. Winners won't be the smartest, they're the ones who took action. So comment below, let me know what's the one action you took away from today's video. And remember, I put together my entire AI tech stack, every tool I use to run my $100 million business. It's free, just DM me @YouTubeStack on Instagram and I'll send it right over. Now, if you want to learn why I'm going all in on AI, watch this video here and I'll see you on the other side.