EP 225: Use AI To Break Things with Entrepreneur Magazine's Jason Feifer

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Should we be breaking things with AI? Well, our guest today thinks it's a good idea and I think I'm probably going to agree with him. So we're going to talk today about how and maybe why you should break things that are already broken and how artificial intelligence could help us rethink how we operate our businesses. All right, I'm excited for today's conversation and thank you for joining us. My name is Jordan Wilson. If you're new here, welcome to Everyday AI. This is a daily live stream, podcast and free daily newsletter helping everyday people like you and me not just learn what's going on in the world of AI, but how we can all actually leverage it to grow our careers and to grow our businesses. So as a reminder, if you are joining us on the podcast, thank you as always. Check out your show notes, the description in there. We have a lot of additional resources for today's show. If you're joining us live, don't worry, it's technically a pre recorded. Don't worry about that. You know, with going 7:30am Central Standard Time, we can't bring all the smartest guests in the world on live at that time. I'll still be there live hanging out in the comments. So please, if you do have questions, get them in now. I'll be interacting. But enough about that. Let's talk about how we can break things, right? I love breaking things with AI. So I'm excited to have this conversation and let's, let's do this. Let's go ahead and bring on and welcome on to the show. There we go. Jason Pfeiffer, who is the editor in chief of Entrepreneur magazine, author, speaker, startup advisor, everything. Jason, thank you so much for joining the show.

Hey Jordan, thanks for having me, I appreciate it. And hey everybody, I'm sorry I can't be there with you live, but as you watch this right now, I will be transporting my children to school. That is the reason we had to prerecord this. But you can always reach out to me and I will respond.

I love it. Also seeing into the future, this is good. That's what we're going to be doing on today's show, right? Talking about how we can see into the future with AI and maybe break things before we get there. Jason, I'm sure like if you follow business building, if you follow entrepreneurship, you definitely know Jason. But maybe for those of you that don't, Jason, just tell everyone a little bit about what you do at Entrepreneur magazine, some of the other ventures that you're involved in, because I know your. Your hand is all in the business building world.

Yeah, I appreciate that. I'll keep it real brief. So I'm the editor in chief of Entrepreneur Magazine. That means that I oversee all the editorial for the brand, and I'm the guy out in front of the cameras talking to people. And I absolutely love it, because the thing that I love most more than anything else is just talking with and working with entrepreneurs. I think the entrepreneurs are, at their heart, problem solvers. They are incredible creative thinkers. They often feel alone in what they're doing, even though they're all doing the same thing together. And my job, as I see it, is to recognize patterns, to bring people together, to have important conversations, and to bring us all into a space where we can solve problems together. And that is definitely what we're doing here on AI.

I love it. And maybe let's. Let's start at the top, right? Let's start. So what does it mean, Jason, to break things that are already broken?

Yeah. So this is a phrase I came up with that came out of a moment in which I was standing in front of a bunch of lawyers. One of the things I do is I travel around, I do a lot of corporate speaking. So a law firm had hired me to speak at their convention. And out of this experience came concept that I call break things that are already broken, which I think is how we need to understand AI and the opportunity that we have. So let me tell it to you really briefly. I was on stage. I give this talk about how to manage and navigate change. That's my. That's my subject area. And afterwards, we got to Q and A, and all of these lawyers start asking me questions about ChatGPT. And. And I didn't expect that, frankly, from a bunch of lawyers. And so afterwards, I found the CEO of this law firm, and I said, you know, it was so interesting that all of your lawyers are so focused on ChatGPT. And he said, I'll tell you what they're thinking, but they wouldn't have said out loud what they're thinking is that ChatGPT or something like it can make motion writing more efficient. And lawyers work on billable hours, so if their work becomes more efficient, then they're not able to bill as much, and that's what they're concerned about. And I said, well, that's fantastic.

Right.

And not in an anti lawyer way, but in a who likes billable hours? Kind of. Who likes billable hours? If we were all together in a room right now and I said, raise your hand if you like billable hours, no hands would go up because it is an all awful detestable way to pay for an incredibly expensive, important legal service. I mean, a professional service. It doesn't make sense that you would be paying your lawyer on the seven minute mark to respond to some emails. But that's what we've had. Why? Because that's what we've had forever. And there was never an incentive for a law firm to say, you know what, I have a different way of doing it. There was really no reason why anybody would do that. It would feel too risky. But now, but now AI is going to break this thing that is already broken. You know, when something breaks in our homes, we throw it away. When something breaks in our lives and our businesses, we tend to keep it. Why? Because it's just too scary to come up with something new. So here we have this opportunity, this opportunity to say this thing that we have, it does not work. It has not worked for a long time. We will finally break it because at this point it doesn't work at all. And somebody, somebody is going to be incentivized to come up with a system that actually works. For now, that's what it means to break something that's already broken. That's what I said to the law firm CEO and he said to me, that is exactly why we just hired a head of AI. And then he laid out an interesting scenario for me. The interesting scenario goes like this. He says, okay, imagine that we do start using ChatGPT or something to write motions and that work does become more efficient. Do I start laying off all my lawyers? No, because now I have an ability to provide legal services at a fraction of the cost that it used to be. And therefore that actually expands my marketplace because right now I can only serve clients that can afford our very high legal fees. But what if instead, now I'm able to customize offerings for people who have smaller budgets? This expands, expands my market reach. This maybe is a reason to hire even more lawyers. This doesn't shrink the business, this grows the business. That's what he saw. And I have found that as I apply this idea of breaking things that are already broken to every arena where I am hearing concerns about how AI is disruptive, I'm seeing it. Jordan, I'll give you one more example. I know I've been talking for a while, but I have friends who are professors in academia, and they're concerned that ChatGPT is now going to be used by. Is going to be used. Is being used by the students to write their essays, and they're very concerned about that. To which I say, fantastic, because student essays were always a terrible way of assessing whether or not students absorbed information. It was always bad. Always. You, Jordan, I guarantee you cheated on tests. I did. And I, and I'm a professional writer. I cheated on so many of those essays. And that was back in the 90s. There is no reason why this is still around, except that nobody had been incentivized to introduce a different system. We will now break something that is already broken, and then we can build something better.

I love it. I. Yeah, actually, Jason, I just wrote other people's essays. I think I was the slower precursor to ChatGPT, you know, expensive. Yeah. Hey, you did it for free. You know, back, back in those days, you know, it wasn't, it wasn't worth a lot. But, you know, I was smiling when you were talking about, like, who doesn't, you know, like, who, who, who doesn't hate billable hours? Right? Like, I would. I have some friends who are lawyers who love billable Iowas. But, you know, it, it like, reminded me when, when I was hiring a new lawyer for Everyday AI, one of the first questions I asked different lawyers as I was interviewing them is, how do you use AI? Right. Like, obviously, I'm a big proponent and I wanted to hear it, but it almost seems like this, this concept that you're talking about, you know, breaking things that are already broken. Do you feel that ultimately AI is going to start exposing just these antiquated business processes just across, you know, across the United States economy? Is this going to be what kind of, you know, shines a light on this, this bad habit of just doing things the way they've always been done for the sake of doing them for the way they've always been done.

I think it's entirely possible. And look, I, I want to. I want to. Before I fully answer that question, I want to nod to that. Breaking things isn't always easy and it isn't always good.

Right.

We shouldn't just go around smashing things just to smash them. I know that that is a tenant of Silicon Valley that people really hate is. This is just this feeling that there's a better way to do everything, and that means that everything that came before it is stupid. That's not what I'm Saying. But what I am saying is that when systems that we're familiar with are challenged, it's important to step back and say, am I being protective of this system because it perfectly operates or just because it's what I happen to be familiar with? And if it's because it's what I happen to be familiar with, then it's worth examining. Well, what are the downsides to this? What are the things that don't work? And is there an opportunity to. To break this thing that is not perfect and then reassemble something that takes the best parts of what I used to do and marries it to some new ways of doing things that enable me to improve the work that I do? So here's a great example. I spoke last year at a customer conference for a company called Appfolio. Appfolio makes software that helps. Helps property managers manage their properties. And so, you know, so if you own or you manage a large apartment building, then you might use Appfolio software to help manage everything. So they did a survey of their property manager customers, and in that survey they asked them, what is the part of your job that you hate the most? And the answer is, as you might expect, data entry and all this kind of very tedious management stuff. What's the part of your work that you love? They asked. And the answer was people working with people, working with tenants, helping solve problems, building relationships. This is the stuff that they love. Now, their line of work requires a balance of both. And every time that they have to spend an hour doing data entry is an hour that they have to steal from engaging with people. And when you introduced new AI tools, which is exactly what they, they did. When I was at their customer conference, they were rolling out all sorts of really interesting AI tools. Simple stuff like, for example, let's say that the elevator in a building breaks. Well, they can now have the property manager immediately, very quickly, with using generative AI, draft a email about that and then have it sent in everybody's native language so you don't have to now kind of figure out how to write them in multiple languages and translate the figure like it automatically does that. And that takes so much tedious time away from, you know, that, that, that allows people to shift the time away from the tedious tasks towards what I think will be more valuable tasks. It's not like we just eliminate work. We don't do that. It's not like this work becomes more efficient, and therefore these property managers have nothing to do. What will happen instead is that they will fill that time with more value. Because we are value driven creatures. We innovate, we grow. That's how we serve ourselves and we serve our communities. And so I believe that when these property managers are liberated from doing all the tedious work, they'll start to build even stronger relationships with tenants. They'll start to be around and be more accessible. That leads to stronger growth for that community. Because now maybe the tenants are happier to stay longer because they feel like the property manager really understands them and is taking care of them. That's better for the bottom line of the business. This is the kind of stuff that I'm seeing and that I'm talking about. It's not to say that there aren't situations where that kind of shift is going to be more disruptive, but I think we need to be open to the reality that the thing that it's disrupting wasn't perfect to begin with, you.

Know, and that that was literally a fantastic example of businesses and, and startups using AI and, and actually, hey, make sure everyone check out your show notes because we did have cat all day. The head of AI from AppFolio on.

Oh, funny.

Yeah, if, yeah, if you're interested in more of the stories on how they're using it, you, yeah, make sure to check out that episode in the show notes as well. You know, Jason, one thing you said there is talking about this, this concept of value, right? And everyone values something different, but it's also how we grow, right? Like depending on what you value, you will probably use that to grow or you'll grow in that direction. So I'm curious, how are you personally even using generative AI to grow or are you like, what's your own experience been like?

So at the beginning of the generative AI, boom, boom, which wasn't that long ago, at least as far as we're talking about kind of mass, mass access to it. I'll be honest, what I heard primarily was a lot of predictions, oh, AI is going to change this. Everything's going to be done by AI now. And I always tune that stuff out because if it's one thing that human beings are truly, truly terrible at, it is predicting the future. We're just awful at it. And so I'm not all that interested in people's prognostication because it's generally always wrong. So I had tuned that stu out. I played around with ChatGPT. I found it interesting, but not all that immediately useful for me and the, you know, the image generation with things like Dolly and Mid Journey was cool. And I did find. I found one immediate application, which is that I write this newsletter, which you can see right there down below. So it's called One Thing Better each Week. One way to be more successful and satisfied at work and build a career or company you love. And I. I wasn't sure what to do about the art at the top of it. And I started playing around with Dolly and realized that if I typed in one line drawing of. So one line drawing of a person trying to enter a door, one line drawing of a person trying to climb a mountain, you know, these things that are kind of broadly representative of the things that I'm writing about, that it would produce this kind of wonderful, simple style that fit really nicely with the tone of what I was writing about and the way in which I was trying to focus on the one thing. And so that has now become the illustrator for my newsletter. And I don't feel like that's taking work away from human illustrators, by the way, because I would. I don't have the budget to pay a real person to do that. So I would have. I don't know what I would have done. I probably would have used stock photography, which was boring. So instead, I'm adding value, and I'm not taking away value now. Or you bring. Are you bringing something up here?

There we go. That's.

There we go.

Right, That's. That's the. That was you're referencing there. It's a drawing done by. In Dolly.

That's right.

And.

And then I get to have fun with it. So if you scroll down a little. A little further. So. So this newsletter was. Is about how to build your network. So at the start, I have that one there. And then. And then I have a metaphor right there about. No, no, go back. Stay on the tv. That's what I wanted you to go to. So then I have a metaphor about how I think about my life in terms of TV seasons and people are characters and tv. And so, you know, then I took. I did that myself manually on Canva. It took just a second, but I, you know, I took this Dolly drawing and then I used it in my own context. And I do a lot of that. And I. I play around. It's really, really fun. But I've been slowly exploring other tools. The other one that I really love is AI note taking inside of meetings. I use Fathom. That's not the only one out there, obviously, but it's the one that just somebody introduced me to. And I tried and I'm Very, very impressed with. And so these things here save me time. They allow me to focus more on the things that actually matter. Right. So if I'm in a meeting, I don't have to worry about taking notes anymore, which means that I get to engage more clearly with the person I'm talking to, which is a more important task. And here I have to the newsletter. I have to think less about the art for the newsletter. I know I can take care of it in about a minute with Dolly. And so that means that I have more time to spend on the thing that really matters, which is the writing of the newsletter. And these are the kinds of things that excite me about my own personal work.

Yeah, I think that right there is such an important takeaway for people is to, you know, shrink away the mundane and to be able to focus on the meaningful. And Jason, I'm sure you've like. I mean, if you've read anything in Entrepreneur magazine, you know, Jason is interviewing some of the smartest people in the world. Some people using AI, some. Some people not. But I'm curious, you know, how has the conversation shifted around AI? And do you think that maybe, you know, entrepreneurs or business leaders are trying to force it in too much? You know, everyone's just trying to, you know, sprinkle AI into everything, maybe to raise more money. Like, how has the conversation changed? And what are you starting to see just from, you know, being so connected in the business world and into entrepreneurship circles?

So it's a great question because we have to be really careful about the things that we're looking at. I think that there are companies that are genuinely identifying new opportunities using AI that are going to increase value for and save time for and make better the work that their clients and their customers do. I think there are also a lot of people who just feel a tremendous pressure to say that they have some kind of AI product and they're rushing something to market, and it's maybe not all that thoughtful or useful. And that isn't just an AI problem. That is an everything problem. We saw it to a lesser degree because I think that the value proposition was less clear, but we saw it to a lesser degree with web3 like a year ago. And you just see these kinds of things constantly crop up. And I think that that's fine because the market ultimately shakes it out. And it's true that also, I'm sure a lot of venture capital firms, the Andreessen Horowitzes of the world, are probably seeing an absolute rash of startups that are AI oriented that are looking for funding, and that the driving force behind some of those startups was simply that they assumed that there's a lot of venture money out there for AI and so why don't we go put together something AI oriented? And again, I think that the market shakes that out. As a, as a consumer, you have to be focused on what is genuinely going to be useful to you. And as an entrepreneur, I think you need to be very focused on how are you ultimately solving the problem problems of your consumer. That's where you really need to live. And if you understand what your consumer's problems are and most importantly, the outcome that they want because of your solutions. So for example, at, at property managers, property managers are not waking up every day and just saying, you know, I, what I really want are AI tools. That's not what they care about. What they care about is the outcome. What they care about is what I really want is to be able to spend more time with my tenants. Ah, okay, so let's work backwards from that. Let's work backwards from outcome. If that's what they want, then how can we start to develop systems and tools that are going to enable them to get that outcome? And does AI play a real, real role in that? I think sometimes the answer is yes, sometimes the answer is no. We're so early days and you know, as, you know, and I'm sure you've probably talked about on the show a million times, you know, the very famous Gartner hype cycle goes like, you know, there's some new thing that's introduced and we go up very quickly where it's, it's very hyped and everybody's talking about how this thing is going to change everything. And then of course it doesn't change everything because nothing changes everything. Which then leads to this crash where people say, oh well, this thing was stupid and it doesn't change. And then finally, finally we kind of curve back upwards and we get to the place where it actually has tangible, very real value in the right use cases. And that's the thing that people need to understand. I like to equate AI to a microwave. So a microwave is incredible technology. Let us stand for a moment in appreciation of the absolute radical innovation that is a microwave. It is out of box. It's a, it's a sure dead. It's a box in your kitchen that heats things up through magic. Right? That's, that's what it is. Try to explain about, try to explain a microwave to someone who lived A hundred years ago. It's crazy. But just because it's amazing technology does not mean that you make everything in the microwave. You don't make gourmet meals in the microwave. You don't cook everything that you make at home in the microwave. It has specific use cases. And during the lifespan of the microwave or the life cycle of, we have experimented. Does this belong in the microwave? Do we make this in the microwave? And we've, you know, as a culture decided these are the things that are good in the microwave, these are the things that are bad in the microwave. The same exact thing is happening in conversation right now about AI. I find it very, very interesting and exciting and I think that if you and I spoke in five years, the way that people understood AI and the purpose of it in their lives and in their businesses would be very different than it is today.

Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on Genai. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft and Nvidia have partnered with us because they trust our expertise in educating the masses around generative AI AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use gen AI. So whether you're looking for chat, GPT training for thousands, or just need help building your front end AI strategy, you can partner with us too. Just like some of the biggest companies in the world do. Go to your everydayai.com partner to get in contact with our team or you can just click on the partner section of our website. We'll help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on Gen AI. Can we all disagree though, that pizza is not best in the microwave? I just, I don't know what it is, but people putting pizza on the microwave, I just don't get it. I'm just more of a toaster oven guy.

That's fair. That's fair. I would, my counter argument would just be time. If I've got one minute to eat that pizza, then the microwave is where it has to.

That's true. You know, Desperate times. Yeah. You know, Jason, so one thing I have a hot take here, you know, and it's, it's, it's been on my mind for a while and you know, I, I know a lot of times people don't like to talk about AI and job displacement, right? We just, just talked about this with the, the CEO of AI for good. But one thing is, we've seen so far in 2024 a lot of tech layoffs, maybe a lot more than people were prepared for, given the overall positive state of the economy. I've always thought, okay, this is going to be the signal or the rise of the entrepreneur, right? When you have these brilliant minds in tech, you know, the ones that are working at trillion dollar companies and multibillion dollar companies getting laid off, and these are in some cases the people who are helping build and implement generative AI. Do you see a scenario where over the next, you know, 6, 12, 18 months, can you see these kind of like, like a perfect storm of this AI and entrepreneurship and these companies, you know, think of like an anthropic, you know, going from, from 0 to 100 so quickly, do you think that that has the potential to be happening just with all of these different circumstances brewing?

So I want to address that in two to three different ways. Number one, let's talk about economics. Number two, let's use media as an interesting example of disruption because it's important to talk about this. We have so far just had a very positive minded conversation about AI. AI is not the only driver, but it's certainly a driving force of large disruptions. It's happening now across industries and that is going to lead to changes. And, and some of those changes are going to result in things like job losses. It will happen, it is happening. And so I don't want to be cavalier and say that every change is just net good. I do believe that over the long term, change generally is net good, but in the short term I understand that if you got laid off, it doesn't feel net good and it may not feel net good for a while. So it's important to recognize that. Look, let's talk economics first for a second though. There's a great economic theory called the lump of labor fallacy and the lump of labor fallacy challenges a fallacy called lump of labor. Lump of labor is the idea that there is a fixed. Imagine a fixed lump of labor, a fixed amount of people to do work and a fixed amount of work to be done. That's, that's the belief and that is often the operating principle that people have when they're concerned about disruptions in a labor economy. So if you believed that there is a fixed number of people to do work And a fixed amount of work to be done, then you would be very concerned when technology starts to, for example, do some of the work that humans were doing, because that now reduces the amount of work to be done, but you have the same number of people doing the work. Or if immigrants are added to an economy, because now you have a fixed amount of work to be done, but more workers because more people have been added. These are the driving concerns that people often have. The reason that it's called the lump of labor fallacy, though, is because there is not a fixed amount of work to be done and there are not a fixed number of people to do the work. In immigration, for example, it's been shown over and over and over again that immigrants don't take jobs from people. And the reason for that is because they are also consumers. They're not just workers. So they come and they need to also consume, they need to buy things. They create a larger economy. And then also the same is true for technology, that when new technologies are introduced, even automated technologies, what we end up with isn't a reduction in work to do. What we end up with is a shift. Shift in the work to do so. A classic example from early parts of American history is that once farming in the 1800s became autumn became more automated, there was a disruption in that there weren't as many jobs for farmers anymore. But because people were now able to earn more money more efficiently, and also food became cheap, cheaper, because it was becoming more automated, there was now suddenly more money for a certain number of people to spend, and therefore an entire leisure economy developed to serve those people. The reason why we have entertainment, the reason why you and I are able to do the thing that we're doing right now, which is functionally to inform and entertain people, the reason why we have professional sports, the reason why we have movie theaters, all came out of that shift in economy, where suddenly, because people didn't have to farm anymore, they had other ways to spend their money, and people created new products and services for people to spend that money on. That's what happens, and that's what has always happened throughout history, is that we don't just eliminate jobs, we shift them and we create entirely new industries and economies that serve new needs. You see this very interestingly now in a nice little microcosm way, in the way in which kiosks are being added to, like ordering kiosks are being added to fast food restaurants. So you would think, for example, that if you put a bunch of kiosks into a McDonald's then you just lay off a ton of people who are at the front of the house who are running the cash registers. But that actually turns out to not be the case because what happens is that once you have the kiosks in, ordering becomes more efficient, which means that order volume actually goes up. And then also you add in the. The ability for people to customize their orders, which means that making the food becomes more complex. So you don't actually have. You don't actually really get to eliminate your staff. What you do is you shift your staff where there now has to be more people in the back making more food. And also you need more people who are cleaning because there are more people who are coming through on a regular basis. Right? So again, you're not reducing work, you're actually just shifting the work. So that's something to think about. But that doesn't mean, of course, that those transitions don't happen and that people don't lose their jobs and that they need to be reskilled and all of that is very, very hard. I want to acknowledge that. Very, very hard for individual people. But now let's talk about, like, what happens as a result of that. Here's. I work in media. Media is under siege. Worse than tech, right? At least tech has a lot of money coming through it. Media has considerably less. I don't worry about this. I really don't. And the reason for that is because when I look around in my industry of media, what I see is an industry that at this point has been built largely on economic opportunities that are shifting. So why do we have the number of digital publishers that we have? Why are. Why is there a million digital publishers out there? The reason was because there was a great golden age in which traffic was easy to get and Google and Facebook and the like were just pumping new viewers into these digital publishers. And entrepreneurs realized there was money to be made in creating efficient digital publishing models. Now that is changing, and as a result, a bunch of those publications are going away. But I would argue that a lot of those publications weren't all that additive anyway. You don't need 5 million stories about the same thing that Elon Musk did, right? Like if Elon Musk farts in the woods, you have a bazillion publications writing the same exact story about it. That's not useful. That's just people taking advantage of an economic opportunity that happens to be shrinking. So will these sites go away? A lot of them, yeah, they will. And will those young, generally very young, fresh out of college underpaid writers have to find other things to do in different ways to develop their skills. Yes, but I would also argue that a lot of them aren't developing great skills being aggregators for the Internet anyway and that this change will lead them to more fulfilling, more long term jobs. Just because something exists doesn't mean that it should or can exist, exist forever. It exists in a certain period of time based on economic opportunity of that time. And then we're going to move on to other times. We're going to find more economic opportunity. You and I, Jordan, we're in a moment of shift right now and we're going to see a lot of that shift and some of that shift is going to be scary and it very well could impact me and it hasn't in already many ways and it impact you and it's going to impact the people who are watching this. Our job isn't to figure out how to hold onto the thing that we used to have. Our job is to figure out how to be useful in the next phase of growth.

I don't know how, you know, you must have a background in telling stories or something because somehow you gave a perfect three tiered response to a very complex question sprinkled in with stories and made it all made sense and made us all that much smarter. So we can't keep this conversation going forever because I would want to talk to you just for three hours about the economic impact. Right? I could dork out on that, but yeah, so I mean we've covered a lot of things. So I mean we've talked about how AI can break things in a good way. You know, equating, you know, a microwave to kind of that, the black box of gen AI and kind of this, this lump of labor fallacy. So, so as we wrap up here, Jason, what is maybe your one piece of advice? You know, there's a lot of, you know, entrepreneurs, business leaders, you know, tuning in. What's the one piece of advice that you have for people specifically maybe on how they can go use this AI, use different, you know, generative AI tools, software, etc. To go break things, to go change the way that business has always been done. What's your one piece of advice?

One piece of advice is this. Don't think about AI as special. It's not special. It's not. It's just an incredible new tool. But throughout human history, we have always, everybody, everybody who has ever been alive has lived in a moment of an incredible new tool. And sometimes that tool was was the printing press. And sometimes that tool was planes, and sometimes that tool were telephones. And I seem to have frozen on my end. I don't know if I'm frozen over on yours, but now I'm back, and today it's AI. But ultimately, ultimately all of these great new tools were for the same purpose, and that was to serve genuine human need, to create economic and social and emotional opportunity for people. And if we can remain focused on that, if you can always be thinking, what do people need? And how can I use the best available tools to deliver what they need? AI becomes possibly a very powerful tool for you to explore, and you should do that. But you have to start with them. Don't start with the AI. Don't start with, oh, well, this is amazing. So let me just make something with it. No, no, you're going to be. You're going to lose with that. It starts with what people's problems are. It starts with what people's needs are. You start with them and you build a bridge from them to you. And that's how you win.

We have the game plan. We can. We can stop right now. Let's go. I love it. Hey, thank you. Thank you so much. So, Jason Pfeiffer, editor in chief of Entrepreneur magazine. Jason, thank you so much for joining the Everyday AI Show. We really appreciate it.

Hey, thanks for having me. And like I said, if anybody wants to reach out, you can Find me on LinkedIn. You can subscribe to my newsletter and respond to any of the emails. It goes right to my inbox. Either way, I'd love to hear what you thought.

Hey, speaking of that newsletter, make sure you sign up for yours and then we will show you Jason's as well. Yeah, you know, even we are referencing, you know, some of the cool art that he created within Dolly. We'll be sharing, you know, a lot of that, you know, Jason's book, his podcast, everything in our newsletter. So make sure to go to your Everyday AI dot com. Sign up for that free daily newsletter. We'll be recapping today's conversation and, you know, yeah, you're going to get your dose of fresh AI news as well. So thank you for joining us and we hope to see you back tomorrow and every day for more Everyday AI. Thanks, y'.

All.

And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit youreverydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next time.