Dominate Content Game Using Multiple AI Models | Dustin Stout

Ryan Hanley: It's a land grab right now, and they want to build their brand as the best of the best AI model. They're going to build their little cages around their products and try and pull people into that ecosystem, which is fine. It incentivizes them to make the better model because there's heavy competition. OpenAI needs people like me to create these multifaceted, complex, comprehensive systems that utilize their technology because that's where their real profit is.

Dustin W. Stout: I was saying it's similar to, you know, in the acting world, you kind of get pigeonholed into you do this one kind of role, right? And I've always fought back against that. I mean, there are some actors who break out of that, right? They do such a wide range of roles. But like even in the professional world, you get pigeonholed into one thing. And I've never been—I've been multi-interested, interest-diverse. I never wanted to be pigeonholed. I wanted to have multiple businesses. So when I tried to make that pivot, it was astonishing how many people were just like, "No, stay in your lane, dude."

Ryan Hanley: I get this all the time because most of my career has been in insurance. And while I have developed an arcane set of skills and knowledge and experience that is highly relevant to the insurance industry, like you said, I've always had bigger—bigger is probably the wrong word—a broader set of interests and things that I wanted to explore. A lot of my success in the insurance industry has been exploring other industries and other ideas, and then bringing those ideas back.

One of the things I find so interesting about that type of take that people will give you—and I completely understand where you're coming from and agree—is that if you only sit in your little insular world, and this is all you ever do, all you ever talk about, all you ever think about, you're actually diminishing yourself. While you may develop a tighter and tighter skill set, I feel like you're also creating a level of brittleness in your business or in your methodology because you're not exposed to new ideas. There's no cross-pollination.

Dustin W. Stout: Yeah, it becomes rigid. That's why people get so locked into "this is the way we've always done things and we're not going to change." We're not going to advance. That's why so many businesses are still struggling with AI—because they do this this way. They've put themselves in this box. They're not going to branch out. I remember sitting in a church where a pastor was like, "You know, I don't read other pastors' books." And I'm like, "So you're just narrow. You don't hear anybody else's perspective but your own." That was a red flag to me.

I think it was probably 10-plus years ago I wrote an article about how if you're not growing, you're dying. Everything in life is that way. Every living thing is the same way. You look at vegetables in the garden—the minute that vegetable stops growing, it starts decaying. I've always felt that way. I need to grow. The minute that I jumped out on my own to be an entrepreneur, I had a little side hustle going on, but I had a full-time job at a t-shirt printing shop designing t-shirts. The minute I realized, "Oh, I'm not going to grow here. My salary might increase a little bit, but I have no growth opportunities. There's no role above me. It's just me and the owner. I'm not going to grow here. I need to leave right away." So if I ever feel like I'm not growing, I go into panic mode. I'm like, "How can I start growing again?" Because I feel like I'm dying at that point. Humans were not made to be static.

Ryan Hanley: I think your point on the pastor and on others who flex that idea—I've heard comedians say it, I've heard authors say it, I've heard other speakers say it. I know you speak a little bit, and I have for 15 years. I'd bump into speakers on the road and they'd say, "Oh, I don't watch other speakers." And I'm like, "I don't understand. How do you find new things? How do you come up with new ideas? How do you expand your game?" Can you imagine a basketball player being like, "I don't watch other basketball players. I don't study a football player. I don't study the other team's plays." What? It makes no sense. It's ridiculous to me.

I know for me, I always felt uncomfortable up on stage. Here I am speaking professionally, getting paid, but standing on a stage always made me feel uncomfortable. Then I saw a good buddy of mine, Marcus Sheridan, speak for the first time, and he works the crowd. It was like, "Oh wait, you mean there's no rule that I have to be up on that stage? I can get down with the people?" Unless it's in my contract that I have to stay on stage for some reason, I'm down in the crowd. Even then, I'm usually lobbying to figure out how to get down there because that just works for my style. But if I hadn't been open to looking at other speakers—in this case, Marcus—I would have never seen that and implemented it in my own work.

That, to me, is one of the things I see with AI. And why I was so excited to chat with you today, especially having lived in the social media world, the design world, having that actor training, and now you're developing this highly successful AI app and doing incredible things. When you're running into people who are hesitant to engage with AI—maybe they're interested, maybe they followed you for a while, but they still have that hesitancy—what are the obstacles? What are the questions? What are the fears that they're presenting you with that you're seeing most commonly?

Dustin W. Stout: Well, the number one fear is people think AI is going to take their job. To me, it sounds ridiculous at this point, maybe because I've explained it so many times, but that fear is real for a lot of people. Back in May, I was speaking in Branson, Missouri at a conference to journalists—media entities, magazines, newspapers, online news blogs. These are people who've been in the media industry for decades. Many of them were embracing AI already, but there were still quite a few who either never sent their first prompt to an AI model or were completely opposed to it. There was a small fraction who were AI hostile. That was an interesting conversation.

But the number one thing was, "AI is going to take my job. I'm going to be out of work. I'm going to be fired because an AI is going to replace me." I think it's such a natural thing to think, especially with all the AI influencers out there talking about automation, AI agents, and how you can revolutionize your business with AI—really just talking a bunch of theory instead of pragmatics. But if you sit and think about it, the AI has to be prompted by someone or something. AI is still not at the point where it can be completely unmonitored. You still have to check its work pretty thoroughly because it still hallucinates, it still makes stuff up, it still gets things wrong. Even if you feed it a source of truth where it can reference the information, it can still get stuff wrong. It can make the wrong conclusions that you're not looking for.

So you have to have a human telling it what to do, prompting it in some way, or even setting up the automation. Even if it's a human setting up the automation, there have to be quality checks along the way to make sure the end product isn't completely off the rails. You have to have a human in the loop to a very good degree. I don't think that will ever completely change. Sure, maybe one human will do more monitoring of more AI systems, and there will be more AI systems doing more things. But still, there's going to be a human at the end of the day having to check the work and make sure it's still doing its job the way it's supposed to, or refining that job. Maybe they find some inefficiencies in the job as the human put it together, and now they have to make some changes.

I think it's still pretty irrational, having looked at the whole history of technology. Our generation in particular has gone through so many paradigm shifts. Think all the way back to when the internet came online. This is something I talked about with Brad because it hits my heart so much. There was a business paradigm that hit the world. Nobody saw it coming. The businesses who fought against it, who resisted it, who said, "No, we've always done business this way. Our brick and mortar is the way that business is done. This internet thing is a fad." Those businesses are gone today because they refused to adapt. They didn't have the access to knowledge or learning or teaching. They didn't have anyone giving them a helping hand, walking them through that. I don't want to see that happen again.

I think this fear may be based in a lot of the fiction that we've been fed about AI, but also maybe some of these paradigm shifts that we've seen over the years where people have gone out of business because the age of the internet took over. All that to say, I think there is truth in the fear, but if you dig through the rationale, at the end of the day, humans are still needed—critically needed—to make sure these AI processes are working. The only way to truly get past that is to just dive in and start learning AI, exploring AI. The cliché that I've used probably a hundred times now is that AI is not going to replace you. Somebody using AI is going to replace you. So unless you equip yourself to be that person using AI—and this is why we fight so hard and work so hard at Magi to make our tools easy and accessible, and every single week we're doing a live training, teaching something about AI, giving people pragmatic use cases of how to work with these AI models and understand how they work so they can innovate and iterate from there—that's the key.

So yeah, that's a long way of answering your question. The number one thing? People are still scared it's going to take their jobs.

Ryan Hanley: Yeah, so I have a slightly different take that I would love for you to get your thoughts on. I actually wrote a post a couple of weeks ago that went fairly viral on LinkedIn. It was directed at insurance agents, but basically I said, "Some of you are losing your jobs. AI is going to take some of your jobs." I get the "AI won't replace you, humans who use it will replace you" thing, because I think that's mostly going to be true. But I also think in pivotal transitional moments with technology—which we are absolutely in—what ends up happening is the businesses that weren't really run well to begin with get exposed.

Dustin W. Stout: No, absolutely.

Ryan Hanley: That happened with the internet. It happened again with APIs, VoIP, that digital era from 2010 to 2020. And it's happening again now. Companies that were able to leverage their brand, their legacy, or their relationships, but aren't run particularly well—when they hit these transitional technology moments, they get exposed. Most of them, it's not that they couldn't adapt or start using a tool like yours, but they don't have the decision-making process. They don't have the systems. They don't have the people. They don't have the infrastructure in place to even consider these things. And they just get mowed down.

What was funny was I expected when I wrote that post to get a lot of people being like, "Oh, this is just another BS technology thing." And I was shocked at how many people were like, "Yeah, I think there's a lot of people missing the point here. If nothing else, no one's going to be growing headcount." There might be more smaller businesses leveraging this tech to do more, but companies aren't going to be putting on headcount. Why would you put on headcount when—we were talking about it before we went live—well, we are actually at this point putting on headcount, but we're going through an extreme growth phase.

Dustin W. Stout: Yeah, I'll clarify and validate exactly what you said. I wrote a blog post a while back around the time there were a bunch of big companies laying off massive amounts of people. They were blaming it on AI, saying, "Hey, we're laying off all these people because of AI." I think the real truth behind that is not that they're replacing them with AI, but those businesses were failing already before AI. There were inefficiencies. There was over-hiring. We saw this. Far be it for me to bring up a touchy subject, but Elon Musk went into Twitter, fired 70% of employees. Everybody's like, "No, it's going to die. How is Twitter going to stay online with only 30% of staff?" Well, guess what? It stayed online. I don't want to say how well it's running, but it's running, and I love being there.

I think the truth is, to your point, they're realizing they don't need as many staff as they've already had. They've maybe overshot their staff, or maybe numbers are down because the economy has been doing this thing for a little while as we stabilize into this new administration. But yeah, they're using AI as an excuse. At the same time, you're 100% right. They're not hiring now because they realize, "Oh, these two employees who were doing five hours of work can do that same five hours of work in 30 minutes now. So we could increase the workload without having to hire more staff." So yeah, you're 100% right with that.

I also want to clarify my statement. I do believe AI is going to eliminate jobs. But my point in saying "someone using AI is going to replace you"—whether it's your manager replacing you because they learned AI and you didn't—that is going to happen. There's going to be fewer jobs that are AI-able, that are accomplishable through AI. But the point I really try to emphasize is that if you learn, if you grow, you can be the master of your own destiny. You don't have to be a victim in this AI paradigm shift. You can learn those skills, become a valuable asset in this new AI economy. Equip yourself with the knowledge so that when somebody is hiring for a new prompt engineer role or a new AI administrative role, you have those skills and you can accomplish that job.

One more little history lesson. Back when sewing machines became a thing, seamstresses were the only way garments got made. Then sewing machines were invented. There was a whole panic in the industrial industry because all these seamstresses were like, "We're going to lose our jobs. These machines are going to take our jobs." And they absolutely did. But not in the way that the seamstresses never worked again. Their jobs just changed. They became more efficient. The quality became easier. It just shifted. I'm not saying it's exactly the same parallel, but we've seen this through multiple industries. Whether it's the seamstresses or the printing press, scribes and transcribers—their jobs changed. Many of those jobs went away forever. It's just a matter of human beings being adaptable if you let yourself be.

Going back to what we started talking about: if you're not growing, if you're not advancing with the technology, if you're not advancing with the culture, then you're going to get left behind. As long as you're growing and equipping yourself, you can become a valuable part of the next phase of our economy.

Ryan Hanley: I think you brought up a really interesting point about the victim mentality. When we hit these transitional technology moments, it seems like people become very polarized. I don't mean that necessarily in the political sense, although obviously we're there as well right now. But more in this idea of you get people who are Machiavellian and you get people that are Marxist. It's either "I'm a victim, I need to be taken care of, this new technology is going to push me aside," and they tend to go towards the Marxist ideas. And then you get the people who are driven, who are like, "You know what? I'm going to start my own company. I'm going to learn how to take my expertise, dump it into a GPT so I can pump out content. I'm going to get after it." You get this very polarized nature between hardcore Machiavellian capitalists going out and creating things and building and taking market share, and those who are willing to coast along—or maybe were able to coast along because of some simple skill set or a position they had—tend to get replaced and get pushed towards this more Marxist side.

One of those yields positive results for us. One of them clearly doesn't. So if I'm sitting in a company from where you're at, and I don't want to be replaced, I'm looking at this going, "This is a huge opportunity." I'm 44 years old. I've got another 20, 30 years of career left. I want to make sure I'm capitalizing on this. What are the things that I'm looking at that I have? Is it my knowledge? Is it my network? Is it my system process discipline? What parts of my skill set should I be cultivating that fit with AI that allow me to launch faster, if that makes sense?

Dustin W. Stout: It's a great question. I think the most valuable thing that we have as humans is the thing that AI will never have. That is our unique combination of predispositions, experiences, and the way that we see the world. From the day that we're born, we're being influenced by our parents, our relatives, whoever we're growing up around. The TV shows that we watch, the books that we read, the teachers that we have—all of it is shaping us and molding us in a way that's so unique that there will never be another human being that is as uniquely put together as you. It's for that reason that AI can never match you in terms of how you see the world.

AI's greatest strength is that it has absorbed and been trained on billions of parameters. It sees so many different perspectives. But in that great strength is its greatest weakness: it doesn't have an opinion. You can make it sound like it has an opinion. It will fake an opinion, but really all it's doing is filtering and sifting all its data to give you an answer that kind of matches what you're looking for. The way that you view the world—if you're using your critical thinking, your wits, your wisdom, and everything that you've grown into as a human being—that will be your greatest strength in the AI economy. When you bring your expertise and your perspective to your work and augment it with the infinite knowledge of AI, that's when you have real synergy and real results that can't be replicated by some predetermined process. That's where your unique ability lies.

Ryan Hanley: I love this idea. I was listening to Dan Martell the other day—if you guys don't listen, it's The Martell Method podcast. He was talking about this process that I've seen other people go through, but he was breaking down how he did it: taking all the content he's ever created and putting it into—he didn't exactly say what model, but we'll just say a custom GPT. He put some documentation together around his personality and how he viewed the world and all these different things. Now he could ask this thing questions about things that he had forgotten. He's like, "I might've said something three years ago that would really work for this argument I'm trying to make today, but am I going to remember that I said that three years ago on podcast 172?" Now the AI can start to prompt out these similar things that our brains aren't set up to catalog and reference.

We all know that with every moment, our memories become a little fuzzier. When you imagine yourself as a child athlete, you hit 27 home runs and were the captain of every team, even though you didn't even make your modified baseball team. We start to get a little fuzzy. What AI can do—and this was his point, and I thought it was a wonderful one—is it can take your work experience, your work thoughts, your beliefs, your content, and now you can remember it in its crispest and clearest form and reference it into your future work. He said he's able to build on his work faster today because he can accurately reference what he did in the past. I was like, "That makes a ton of sense. I need to start doing this."

This is a project I'm actually working on behind the scenes now. I've done thousands of podcasts, thousands of blog posts over my career. You've created so much content too. I'm struggling with how to get some of the social media content in there, working through it. But this idea of being able to reference ideas I was talking about on X topic five years ago—how much faster can I move in building on those ideas today because I'm not guessing at what I thought five years ago? It's right at my fingertips. As a leader, as someone who likes to create, if you need to do SOPs, best practices, systems—all these things inside your business—having all that at your fingertips means you're basically the collective knowledge of your professional life at your fingertips. That's a competitive advantage that I don't even know you could throw a value on yet today.

Dustin W. Stout: That makes me think of—are you a big Netflix watcher? Do you watch a lot of shows?

Ryan Hanley: Unfortunately, I can be sucked in. What is it called? Death stream? Instagram and death scroll. I can death stream episodes of shows. The only way to turn off my business mind is to go head first and lose myself in a TV show or a movie. That's my de-stressor.

Dustin W. Stout: Recently, one of the hardest things about Netflix—and I equate this to why we created Magi—is you go in and you don't know what to watch because there are too many options. One of the things I love doing is finding a show that has a lot of episodes so next time I log into Netflix, I just know, "Oh, I'm just going to grab the next episode." No thinking, just turn it on. I found a show recently called Rust Valley Restorers. Have you heard of this one?

Ryan Hanley: No.

Dustin W. Stout: The premise is there's this guy named Mike Hall from BC, Canada. He owns a huge plot of land with dozens of old junk cars. He started a car restoration business. He's going to restore all these cars. But the plot of land is massive, and he has all these—he calls them treasures—but it's just junk everywhere. Dozens of old cars, frames, pieces, parts. He's got containers filled with new and old parts. He doesn't know where anything is at any given time. Half the show is him rummaging around with his partner trying to find these parts.

What you said is really funny. That feels like how our brains are. We've got all this treasure in here that we've accumulated over the years—wisdom, knowledge—and accessing it becomes so difficult because you're rummaging around. "Where did I put that? What did I say about this thing? When did I do that other thing?" How great would it be if Mike could suddenly have an AI catalog all the stuff, all the junk, and he could say, "Where did I put that fender for the '67 Chevelle?" And it would go, "Oh, in this place over here." Brilliant. He wouldn't have to rummage around. There would be no show anymore because half of it is just them hilariously stumbling around this junkyard.

But imagine that for our brains, for our body of work. How many times has somebody said, "Hey Ryan, you said this thing in this podcast that one time that really blew my mind," and you're like, "I said that? I can't even remember that." It happens. I do this sometimes with certain shows. If I picked up a show 100 episodes into their podcast, I'll go deep cuts. I'll scroll into the archives and find an old episode with a guest from three, four, five years ago. People do this. A lot of podcast listeners find a show, like a couple episodes, and then go deep cuts. When people email or DM about it, I sometimes am like, "I don't even remember what planet I was on three years ago when I was talking." You just don't remember it. It's crazy.

But one thing I think is really interesting is I see the potential for a really interesting counter movement as well. AI takes this idea of creating a second brain that we can easily reference. We'll put that over here as AI. And then I think there's a really interesting counter movement around consciousness and clarity and really expanding our own minds and what they're able to do. For a while, I was microdosing psilocybin once or twice a week. People would ask me, "Why are you doing that?" One, I like to test everything that I don't think is going to kill me, and I was pretty sure it wasn't. It's not addictive, so I wanted to give it a try. What I found was, as long as you didn't overdo it—there was a zone of genius where too much and your screen got a little funky, and not enough and you didn't even know you were taking it—you felt an unlock in your brain.

Now, granted, I'm using a chemical to get there. But I do think, as much as there is absolutely a clear value from an industrious standpoint to creating this second brain idea—using these tools to reference things and create interesting things—one thing I worry about in that effort is the loss of serendipitous ideas. You're a believer as much as I am in Christ and God, and there's divine inspiration. If everything is mechanical in an AI, if you live solely in that world, then I wonder if you lose that serendipitous muse—the divine, however you want to define it. Do you lose that? Or does it amplify that?

Dustin W. Stout: I mean, because some of the ideas that sculpt the world, when you listen to the inventors or the individuals who crafted these ideas, oftentimes they don't have a clear answer as to where it came from. I think we have to be careful of over-indexing on the computers and over-leveraging them. We've actually seen some studies already that show individuals who rely too heavily on AI for all of their creation are actually losing the ability to create when they're not using it. Where do you see that transition, or how do you marry that idea in your own life? How do you make sure you're not losing some of your natural skills by over-indexing on the AI so that you can still keep that human spark?

Ryan Hanley: Yeah. I think it first starts with an awareness, a desire to grow. I think anybody who does want to grow will be highly sensitive to that. I know I am. But think about it almost like our physical world. I could sit here all day and be great. I've worked from home since 2014. I could stay in my house all the time, but there's a part of me that starts to get antsy, a part of me that's like, "I got to get out of here. I got to stretch my limbs. I got to go to the gym." In fact, I'm missing my gym workout time today to be here with you. Not that I can't do some pushups together on camera.

Dustin W. Stout: Yes, if you want.

Ryan Hanley: No, I'll go after this. But I start itching, right? I start to get that feeling because I want to be growing. I want to keep my physical strength. I want to stay physically fit. And I can tell when I'm not. Same thing is cognitive. When I'm being lazy, mentally lazy, I can feel it. I can start to feel my brain getting squishy. I have a sensitivity to it. Some people may not. One of the things I think is very true is that lazy people are going to be lazy. They're going to find more ways to be lazy, whereas people who want to do their best work will find ways to do their best work. So there's definitely an awareness that needs to happen. It can be a crutch.

Dustin W. Stout: Back in the day when we had to memorize everybody's phone number, how many phone numbers do you have memorized today?

Ryan Hanley: Probably not that many.

Dustin W. Stout: Not many. I realized the other day, this is so interesting, I know the last four digits of a decent number of phone numbers because sometimes they come up. But I could never tell you the full phone number anymore. I recognize the last four digits because that's what the iPhone will show next to someone's name. But I couldn't tell you what their phone number is. My ex-wife is 3631. My dad is 9-1-1-3. I honestly couldn't even tell you what the first three numbers of their phone numbers are today. I was like, wow, that's a really weird thing that developed with the technology.

Ryan Hanley: Yeah.

Dustin W. Stout: So back to what I was saying, as long as we keep our wits about us, we keep our critical thinking hats on. That's the most important part of it—critical thinking. Going back to this idea that AI makes mistakes, AI hallucinates, AI isn't perfect. We have to keep our critical thinking hat on. And as long as we're doing that, and we're realizing that our most valuable asset is our unique combination of experiences that leads to those serendipitous moments that God has only built us for. I'm also a firm believer that God created us for a purpose on purpose, and that there's nobody else in this world that could fulfill that purpose the way that he built us to. So knowing that, as long as we keep that at the forefront of our minds—that we're here to be uniquely us and AI can never be uniquely us—we can fight that urge to be lazy and fight that urge to use AI as a crutch rather than using it as a stepping stool.

Ryan Hanley: So I want to talk about your transition. You wrote this incredible article like two days ago. I was pulling up your website because I was learning about Magi, and I want to get there because there's a bunch of really interesting things that you've done that I'm really intrigued about. But one of the things I thought was really interesting in this article—I'm going to link it up in the show notes, everybody, so whether you're watching or listening, just scroll down on whatever platform you're on—one of the things you talk about is this capture. You had always been a social media guy, a design guy. That's what your audience knew you for. That's why they followed you. And now you see this opportunity, you're called to it, you fight it, but you can't get away from it. You decide to make this move into becoming an entrepreneur in the AI space and create this tool. You talk about it in the article, and I think you do a wonderful job. The friction of people had always seen you as X and you're being called to become Y. There's a lot of friction there. It creates doubt, frustration, and fear. How did you fight through that? We talked a little bit before we went live. I've experienced a little bit of that in my own life. One of the places is taking this podcast from being an insurance-only podcast three years ago to expanding it out into broader topics. I've had a lot of people email me and say, "I loved your podcast more when it was just insurance stuff." And it's like, yeah, except over a decade, I had basically said everything I could and wanted to say on that topic. I needed to expand. Your jump is probably even more powerful because you're becoming an entrepreneur. Your career, your income, your ability to provide for your family is now in this company. How did you, one, what were you really dealing with, and two, how did you fight through that fear, confusion, and frustration to make the transition to where you are today?

Dustin W. Stout: How long we got? Do we have time for the lifetime movie of my life? I'll try to keep it short. The harsh truth about being a social media expert is that many of the social media experts you know are broke because there's not a ton of money in being a social media expert. There are a fair few who become super influential and have figured out how to monetize their expertise, but the vast majority of social media managers and consultants are not valued as much as they should be. People don't want to pay them what they're actually worth. It's a real struggle to make a comfortable living in the world of social media marketing and consulting. Many have done it, but many, many have not done well. I found myself always an entrepreneur. Back in 2014, I started the Social Warfare plugin with a couple of partners that did fairly well. That was my first successful SaaS business. Around 2020, my partners and I had grown apart. We weren't agreeing on pretty much anything, so I decided to exit. I had a couple ideas of two products that I really wanted to build, both in the realm of social media. One was an app that would produce social media graphics quickly and easily in every size you need—think of it like Canva light. The other was a way to create articles or turn long-form content into a bunch of social media posts instantly. This was all before the onset of AI. In my mind, I wanted these apps to be AI-oriented. This was 2020. It wasn't until November 2022 that ChatGPT hit the scene. I knew AI was starting to become a thing. We had some copywriters out there, the Jaspers of the world, which back then were called Conversion AI, and then Copy AI, a bunch of clones. I thought to myself, I want to create an AI app that will generate images for people and one that will generate copy for people at scale for these social media jobs. Long story short, I had to raise money to build these apps because it was expensive. I didn't get anywhere close to the AI features because it just wasn't accessible then. I would have needed $100 million to make these products the way I wanted. I didn't have $100 million. I had about $30,000. So the MVPs came out. We built them. Took us about nine months. $65,000 later, I'm broke. Nobody wants these products. I'm probably in the worst mental, spiritual, and financial state I've ever been in my life. I've got a wife and three kids to take care of, a mortgage that I don't know how I'm going to pay. I realized my career up to this point had been great until it wasn't. Everything I was doing seemed to be failing around me. Then ChatGPT came around. It was one of those moments where I used it for the first time and I thought to myself, this is going to change everything. I hate to be overly charismatic, but it was almost like God brought me to my lowest point. I was suicidal many times. I thought I had nothing to give to the world. I was praying that God would take me home. It was in that moment that I used ChatGPT that God almost gave me a vision of, "This is going to change the world. Here's what it's going to look like in about five years. You need to pay attention to this." I had such clarity in that moment. I had taken a couple clients. I was doing some web design and social media for them. So I started using ChatGPT. As I used it more, I realized, "This is great, but why doesn't it do this? Why doesn't it do that? I wish it did this better. Why do I have to have five other subscriptions to have these image things and the video things and the audio thing? Why can't they build?" It was almost like God said to me, "This is how I built you—to find all the gaps, to find everything that's wrong, and to build something better." So in eight weeks, when I finally decided I had this idea for Magi, I built it start to finish by myself. No capital, no team, no resources. Just me sitting at my desk going, "I got to figure out a way to pay my mortgage next month and make sure my kids don't go hungry." By the grace of God, I'm not a developer. I know enough code to be dangerous. But it was like when the student's ready, the teacher appears. God put all the teachers in front of me. I learned what I needed to learn and built the first version of Magi in about eight weeks. Launched it March 31st, 2023, just four or five months after ChatGPT hit the world.

Ryan Hanley: Dude, it's incredible. You're in very good company. I had something very similar happen to me with my last startup. I founded an insurance agency, grew it, sold it. Unfortunately, I sold it to the wrong people. I watched my baby get torn up and shredded. I made good on the numbers I needed to make good on, but the first moment I could hit an exit, I exited. It was this moment where I was used to having this company with 25 employees and making money, and now all of a sudden I had a little bit of money in the bank but no job. It was the first time in my life that I ever woke up and didn't know what I was supposed to do. It felt the same thing with marketing, even as a CMO. I've been a CMO a couple of times. You're always put a peg below because you're the marketing guy. I got into marketing because I'm charismatic, willing to create, and it felt like an easy path to move up the rungs. The problem is, you get pigeonholed as a marketing guy. I'm not even a good marketer. If you were to put me head to head with a good marketing person, I would get slaughtered.

Dustin W. Stout: I really can't worry about myself.

Ryan Hanley: I love that story. I want to get into some of the technical aspects of what you're doing because I want the audience to take some technical stuff away from this. I think your approach is really unique and interesting. But I just want to sit here for one second because I think too often, whether we're entrepreneurs, sales professionals living that salespreneur life, or true entrepreneurs, we look at these moments and feel like we're being punished. That's the way I felt. I had these enormous plans for this company and it just didn't happen. I was like, "Why would you do that? I gave up two years of my life. I got divorced during this time, not necessarily because of the startup, but all these things were happening. I was like, 'What the fuck? I try to be a good guy. I'm a believer. I pray. I try to live a life that I believe Jesus would be proud of. If I have to stand in front of St. Peter, I can justify it. Why is this happening?'" You go down this spiral. This is why I advocate for having a relationship with God. In that time, if you're willing to open yourself up, you start to hear things. Maybe it's God. Maybe praying creates space in your brain for you to actually have some original thoughts or get to the core of who you are. What I heard was, "You're not a marketer. You're a leader. You need to get better at the business of leadership so that you can do this again for another company." That's what I'm doing now. I'm the CEO of an AI startup in the insurance industry. Different from what you're doing, but interesting. I just hope, guys, if you're listening, you listen to Dustin's story, you listen to mine. We all have our own. Even God loves you, whether you believe in him or not. Even if you're an atheist, creating that space and acting as if—Jordan Peterson said it best, "Act as if." There's a lot of opportunity for us to hear and find what we really want to do. So you find this idea of God telling you that you're here because you see the gaps, you see the spaces, and you create Magi. One of the things I was immediately captured by is this concept of, in context, the ability to use different models. I'm very interested in where that idea came from. Can you expand upon the power of being able to do that? What is the actual power of being able to start in OpenAI, then touch Gemini 2.5, then move to Claude, or whatever process makes sense? Where did that come from, why does it matter, and how does it add value?

Dustin W. Stout: It's funny transitioning from the pigeonhole conversation. I'm getting ready to pigeonhole some of these AI models. To speak to that a little more, I think anybody who's listening feels like they have this pressure from the people around them to stay in their lane. Just know that sometimes you have to make the decision to remove those people from your life and stop listening to the people who want you to stay in your lane. That's what I had to do. People wanted me to stay in my lane were keeping me broke, miserable, and not fulfilling my purpose. You really have to have that bravery to jump out of that pigeonhole and say, "Who do I want to be?" In our case, "Who does God want me to be?" Listen to that voice rather than cave into the peer pressure of who people expect me to be. To answer your question, AI models do have very explicit strengths and weaknesses. The more you test them, the more you explore them. This is another reason I created Magi—I wanted people to be able to explore. It's so difficult to have to switch to this tab and try this one, then switch to another tab and try that one, then switch between the tabs and compare back and forth. At the same time, the underlying technology is not giving you a fair shot at actually exploring their capabilities because they're all doing backend engineering and prompts that you can't see. You don't get to explore. But when you do get to explore, you get to have a baseline for all these models. You'll find very quickly that you like how one model does this type of prompt versus how another model does another type of prompt. You'll have favorites and preferences. For me in particular, I love GPT's creativity. I think it has the most out-of-the-box ideas. Whenever I'm looking for a perspective I can't get to on my own, or an analogy that I just need a better one because the one I'm coming up with is not hitting, GPT comes up with some really great creative thinking. When I'm writing marketing copy or sales copy, GPT falls kind of short. I just never really buy into it. But I hand that same task over to Claude, and Claude writes copy better than I ever could. There are definite strengths and weaknesses of every single model. Google Gemini is all about structuring the internet, so it makes sense that they've engineered it to be really good at structural stuff. When you find these different strengths and weaknesses, you realize you can, for a blog post for example, brainstorm the titles with GPT because it's super creative, then brainstorm the outline with GPT. But once I have that outline and I want to do some actual writing, I don't want GPT to do the writing. I want to switch over to Claude. How would you do that without Magi? You'd have to copy that outline, head over to Claude, log in, start a new chat, paste that in, and say, "Hey, we're going to build it," and give it all the background. But with Magi, because we've put them all in one place, you can essentially say, "Thanks, ChatGPT. Now I'm going to bring Claude into the room, and Claude's going to take over from there as if it was in the room the whole time." Think of it like having a room full of experts just sitting there waiting to help you out whenever you need them. You can say, "You're in." It's almost like a sports team. "Hey ChatGPT, you're on the bench. Claude, come on in. You're up next." That gives you a more seamless, unbroken experience so you're not breaking up your flow. What's really fascinating is that these models, without going into super technical how it works, when you start with one model and bring in another one, the new model sees the entire conversation from you and the other model. It's almost like it learns from it. Claude can actually learn from the creative choices of GPT earlier in the conversation and becomes more creative. The more you pull in those abilities, the longer that conversation goes, the better these models get. You can even use a dumb model near the end, one that's not very sophisticated, maybe an older model, and it creates the same level of output almost because it's learned from the earlier parts of the conversation. It's really fascinating to see how all these models can not just be leveraged in ways that bring out all their strengths and none of their weaknesses, but they actually enhance one another as the conversation progresses.

Ryan Hanley: This to me is the future of creation. I completely agree. I started deprecating them only because before I knew what you were up to, and this is going to be my go-to tool now. 100%. I've been playing around with it already. I was going ChatGPT, then I would do research in Gemini before deep research with ChatGPT. Then I'd pull the research in. The titles and some of the hooks that GPT creates are phenomenal. But I agree. You get into the body, and unless—I feel like GPT has a really good feel for narrative design, but marketing copy, sales copy, email copy, it's kind of blah. It doesn't hit. I played around with Grok for a little while, but Grok before the latest release of Grok 4 was iffy. Grok 4 seems a little overtuned for personality.

Dustin W. Stout: Grok 4 is wild. I think they may have swung the pendulum a little too far the other way. We'll see.

Ryan Hanley: I agree. But I do think what you're describing, this workflow of using—it's like anybody else. If you have a plumber come over to your house, it's not like they have one wrench that does every function they need. They have a screw gun, a wrench, a socket wrench, a pair of needle nose pliers. For what they need to do, they're pulling out of their tool belt the best tool. To have one place where you can pull them all together is an absolute no-brainer. This is where we have to go. Do you see a time when—it feels like we're in an expansion phase of AI. To me, it's obvious that right now we're in pure expansion. New models popping up all over. Entire countries creating new models. It's really wonderful and wild. It's a true FAFO moment for the world. Do you see where we start to come back in and these models actually natively start to work together? Or do you think the business of AI will keep that from happening?

Dustin W. Stout: I think the business of it will keep it from happening because these companies are all trying to—it's a land grab right now. They want to build their brand as the best AI model, so they're going to build their little cages around their products and try to pull people into that ecosystem. That's fine. It incentivizes them to make the better model because there's heavy competition. Well, when I say heavy, there's really like four competitors. There's four top ones. China out of nowhere comes up with a new DeepSeek model that is more efficient, less costly, and can do just as well as the GPT models at a lower price. So we have real competition in the market. That's great. The thing is, these companies are losing money hand over fist on subscribers. Your ChatGPT subscription, your $20 a month, OpenAI is losing so much money on these subscribers that they have to find other ways to monetize their models. That's where apps like Magi come in. Magi in relation to OpenAI is pure profit for them. Every time one of our users uses a ChatGPT model, we have to pay for it. We are paying for every single transaction. OpenAI needs people like me to create these multifaceted, complex, comprehensive systems that utilize their technology in a way that's 100% pure profit for them. It's a really interesting ecosystem. They have to build their own little castle on their own little hill, but at the same time, they have to make it friendly with working with other apps because that's where their real profit is. In terms of capabilities, it is rapidly expanding, but the truth behind the scenes, if you talk to any of the AI engineers, is that the AI model growth trajectory is actually slowing down. Once you've trained on all of the world's data, how do you get smarter? How do you make a smarter model on the same data? Now they're talking about creating synthetic data—data that's fake, created by AI. Even with this, you're watching these capability charts shoot up real quick, and then it starts to plateau out. I think we're seeing a slowdown of model releases and model capabilities. There are rumors of GPT-5 coming out before the end of summer. That might happen. But I don't think it's going to be the mind-blowing hype of the first version. It's going to be an increase in capabilities, but it's going to be slowed down. I think that means this Wild West is starting to get a little more tame. It's starting to stabilize. I think that's a good thing for everyone.

Ryan Hanley: I agree. The raw hype cycle all the time would just burn us all out. That stabilization allows entrepreneurs like yourself to start to create the towns, the meeting places. If we're using the Wild West analogy, you're able to actually put down some roots and build something because now the models aren't shooting off in every direction. The iterations have less deviation in them, which is a good thing. The last episode of the All In podcast, the week before we're recording this, they talk about this idea of synthetic data. I know we're getting up against a number, but I just want to put this in front of you and get your thoughts on it because you're so deep in this world. The idea of creating synthetic data is exactly what you just said. ChatGPT and OpenAI have indexed almost all of the knowledge they can get their hands on today. There are pockets that are still hidden, but for the most part, they have their hands on everything that's available digitally. They've consumed it, and they're consuming as new is created as well. Just read your private API contracts if you don't think that's happening.

Dustin W. Stout: Unless you're a Magi user, then it's all private.

Ryan Hanley: Yeah, that's good. Some of these tools, you've got to be really careful because there are different versions of the API. Some people don't realize what they're putting in. That being said, the idea of synthetic data is that they start creating data that has no physical or any basis in the real world in order to train these models on increasingly difficult and diverse problems to give them things to train on. My question for you is, is that a good thing? How should we feel about synthetic data? I caught ChatGPT in a lie the other day. I asked it a question about where it gathered a specific type of data that was relevant to our tool. It gave me an answer which I knew at face value was false. I pressed it, and it gave me this whitewashed version of the answer. I pressed it again, and I got the real answer. The real answer was a little scary. It doesn't matter. But if we're training on synthetic data that is false to begin with, or just not based in reality, how do we as business professionals consider that? Should we consider models that are using massive amounts of synthetic data? Where do you see that part going? Because I do think that's a real question, especially for regulated industries. This is a big problem in our space, right?

Ryan Hanley: Like, insurance is highly regulated, both at the federal level and individually at every state level. Right now, insurance carriers cannot use AI algorithms to do any kind of underwriting. They can train models today, but they can't deploy them in actual underwriting. So a lot of carriers are starting to play with models as test data, but they can't actually use them. And the reason is hallucinations and all this kind of stuff.

Dustin W. Stout: Sure.

Ryan Hanley: But the only way—and this is kind of where this question comes from, a little selfishly—is there's been a lot of talk specifically in the insurance industry around the use of synthetic data, because everyone's policy information is proprietary and is in these private vaults. It's their competitive advantages: who bought what, for how much, and how much did they buy, etcetera. So if everyone has their little private pool and there's not one singular place for it all to come together, the thought process has been the only way to really get more sophisticated, more accurate, and deliver faster results is to start to create synthetic data. But if you do that, are you corrupting the underwriting models? So where are you on synthetic data? How do you see this being used? And maybe if I'm a business owner who's all in with everything you've said so far, how do I navigate models that are using this synthetic data?

Dustin W. Stout: I think it's really hard. And one thing you'll never see me do is pretend to be smarter than I actually am. At least I try not to.

Ryan Hanley: I do that all the time, so if you did, you'd be fine.

Dustin W. Stout: I really try not to jump to conclusions, because experts have been wrong before, I've been wrong before. I really can't make a decision on whether synthetic data is bad or good because we just haven't tested it yet. So far, there have been some new models that have come out—the new Claude models have come out, the OpenAI GPT-4.1 models have come out—and they've been trained on some synthetic data. So far, so good. So I am optimistic about it, but I'm optimistic because I have this emphasis on critical thinking. Going back to this idea, we need to use our brains. We need to not just take what the AI gives us at face value. You immediately saw when it was wrong because you were looking at it critically. I think as long as we keep that critical thinking about us and we analyze everything that it gives us with a critical eye, we should be fine. In my optimistic outlook, I think the synthetic data will be mostly fine. But I don't know. Could be terrible. We can only see because it's completely new territory. We just don't know. I don't know enough about what kinds of synthetic data they're creating, what it looks like, what it reads like, how it works. So I'm going to remain optimistic, and I'm going to remain the advocate for: think critically, don't take anything at face value. Assume it's going to lie to you if you're not careful.

Ryan Hanley: Trust, but verify, right?

Dustin W. Stout: Trust, but verify.

Ryan Hanley: Dude, it's been so great to reconnect. I'm so excited for what you have going on. Fan of the tool, user. Where can people dive deeper into—and we'll have links to anything that you mention here, especially Magi—just where they can go and sign up, et cetera. But if they're just interested in your takes and staying with your ideas and getting deeper into your world, where should they go?

Dustin W. Stout: Well, you can visit my personal blog, DustinStout.com. I'm pretty inconsistent on there. I've been trying to be more consistent writing recently now that I have a little bit more margin. Things have gotten a little bit crazy with my last podcast interview. But yeah, I'm trying to write more. You can find everything about me there. Links to Magi as well. You can go to magi.co—M-A-G-A-I dot C-O—to learn more about Magi.

Ryan Hanley: Dude, appreciate the hell out of you. I love what you're doing. I really love your story. So good to see you again.

Dustin W. Stout: You too, bud. Be good, man.

Ryan Hanley: It was great.

[Both laugh]

Ryan Hanley: Good. Let's go. Yeah, make it look easy.

[End of interview]

Ryan Hanley: Thank you for listening to The Ryan Hanley Show. Be sure to subscribe and leave us a comment or review wherever you listen to podcasts.