5 Truths About Making Money with AI — Full Transcript & Summary

[00:01] make you rich. Buy this tool, use this prompt, be a millionaire by next week, but it's all bull I've built and scaled dozens of AI companies to over a million dollars in less than 6 months through my company

[00:13] Martel 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 five truths on how to actually get rich

[00:25] with AI that no one will tell you. Starting with truth number one, 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

[00:38] then essentially you're just whacking at a wall for no reason. make money with it? AI hasn't changed what makes you rich, you get rich by changed how fast you can get there, but the fundamentals haven't changed. You

[00:53] still need to know how to apply AI. Focused operators with real skills that know how to do with AI makes them unstoppable. Having no focus all over valuable, AI [music] will just burn you, burn your bank account, cause you to

[01:08] 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. [music] If you have a business, it can help you grow faster, but it can also help you

[01:20] 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 two, AI isn't the problem. Nobody woke up today and said, "I need more AI. Who got AI? Can you sell me

[01:33] some AI?" Nobody woke up and said that. They woke up and said, "Oh, this is a problem still. [music] 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

[01:48] 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,

[02:01] a problem. Now you need to figure out what nail is the right one to hit. called the gain matrix. Essentially, you have things that are easy for computers, hard for computers, hard for humans, easy for humans. And

[02:15] 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

[02:29] these small little things that you could do that most people don't give up look at this as the first place like nobody should be doing this in the world of AI. So these are things like data entry,

[02:44] right? We've got other things like simple calculations. where it's hard for humans, but really easy for computers. This is where real think about buying back my time. That's

[02:59] 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 [music] the pattern in this."

[03:11] 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.

[03:25] And this is where you take hard for computers and hard for humans, and you collaborate [music] together, and you create new things that otherwise you couldn't do. Think about like creative tasks. Like, yeah, you can get it to

[03:38] 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. Often times when I'm working with AI, I can't tell you what I'm looking for, but I know it when

[03:51] what I'm looking for, but I know it when see it. So, think creative tasks. Like when I'm building new companies, often times I need to see the whole

[04:05] thing. The AI gives me options, but me and my team, we look at it and we go, 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.

[04:18] It's not about the right thing, it's about doing the right thing in the right order. And often times, that's hard for me to even know what are the pieces. AI know what sequence cuz it doesn't have the sensibility of a human, and together

[04:32] 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 This is where we go full freestyle, full old school, called no AI, right? Because

[04:45] 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 behind the keyboard and get AI to do this for me." No. This is where the

[04:58] 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 with conflict. AI can't deal with leadership. AI can't understand the

[05:12] complexity of the human experience to be able to resolve situations. I spend my 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

[05:25] 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 got to think about. Like things like EQ,

[05:37] teach my kids. Leadership. How do you show up for your being led by an AI. Sure, they'll follow tasks, but being inspired, that's a >> [music] >> Intuition, resolving conflicts,

[05:52] 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

[06:04] essentially all different kinds of nails, screws, thumbtacks, and they all 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

[06:19] find me on Instagram and just DM me the word YouTube [music] stack and I'll send Now, I know what you're thinking. I figured out the problems to solve, now how to do I use AI to solve? Truth number three, don't use AI. I

[06:34] 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

[06:47] to understand the steps, what works and what doesn't before you ever introduce AI. My favorite story to tell is listening to anytime Elon Musk has run into an issue and he says, I just went down to the place where the issue was, I

[07:01] 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

[07:15] 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 want to

[07:28] I'm like, AI can help you write the there's a problem to solve. So, my favorite thing to do is launch a page, to them if they have the problem, then they go, "Yeah, I have the problem."

[07:41] Cool. Manually solve it. It's called Wizard of Oz-ing, where you have you're behind the scenes, you onboard the customer, you look at the data, you They think it's AI, it's not, it's a person. And because of that, you're not

[07:54] the problem, you're wondering if the problem is solved the way the customer pre-validate. Before you sit there and thousands of dollars, trying to build a prototype before you even know if

[08:07] of friends that have been doing this lately. And they call me up and say, prototype?" I go, "That's cool. Where are the customers?" You learn so much more having real customers pay you real money to solve their problem in a real

[08:19] 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

[08:33] feet. If you got to go out and do something, do that. Deliver the service yourself. That way, you can understand the whole workflow. Second, document

[08:45] 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 specs. I actually wrote it out already. The AI can take that and build

[09:00] something. The third, and only once you do one and two, 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,

[09:12] AI. And then the last step is we got to scale. Once we know what the customers want, we've documented 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.

[09:25] And that's how we scale, but that's the last step, not the first step. Most people start at step four, go back to step one, and work your way through it. So, now you know that AI is just a tool. You know that solving real problems is

[09:39] 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 four, AI does not replace people. Everyone in the future, if they

[09:54] >> [music] >> 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

[10:07] traditional way, okay? One person for each one of these roles. Think creative director to come up with the strategy, script writer, you've got an editor, you need somebody to post the video. The agentic way, which is the agent on the

[10:20] loop, is one person owning the workflow. That's where it's changed. And then the agent, 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

[10:33] 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

[10:45] where the world's going, didn't upskill their team, didn't get them ready for 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?

[10:59] 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 two whole days and I taught every single person how to code. And we

[11:12] ran a contest for two 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 themselves, somebody else is going to do it. They want to be the person that

[11:26] 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

[11:41] just draw a T-chart just like this. On one side, write AI, okay? Follow along at home. I'm watching. Think of all the tasks that need to get done for a specific process to actually [music] get done. On the A side, what

[11:56] 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

[12:10] research, right? You can have copywriting. >> [snorts] >> You can create ads. You can do emails. You can do analysis of the workflow.

[12:30] 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 making sure that they happen. On the human side, this is very special cuz now

[12:46] 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 that says, "I am accountable for that output." The AI is not accountable. Guess what? No AI is

[12:58] going to jail. Human will. I think about vision. about the future that doesn't exist yet that should, okay? And that is a human thing to create. Then we have taste, right?

[13:11] "Taste isn't something you can buy. It has to be learned." That's a human thing. We have directing, directing other humans. really talented people are not going to sit back and be directed by a computer

[13:26] 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?

[13:39] 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 teach somebody. Most of them you don't have to do anymore. But, does the human

[13:52] know how to manage the AI? That is the agent operator and those are completely 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

[14:07] become better humans, better interactions. The person that used to 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

[14:22] 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 five,

[14:35] 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

[14:48] fundamentals of building a business has never changed. Customers have problems, they want the problem solved. Bigger the problem, bigger the business. The more the solution, the more the customer's going to love you. AI doesn't replace

[15:02] 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

[15:14] 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

[15:26] tool I use to run my $100 million business, it's free. Just DM me YouTube stack on Instagram and I'll send it right over. Now, if you want to learn video here and I'll see you on the other side.