The Digital Economy and Its Impact on Productivity

Dean: This call may be recorded or transcribed. Mr. Sullivan.

Dan: Who is that person that gives the directions when we start the podcast?

Dean: Well, I'm not sure. The one that says this podcast. Maybe this recall.

Dan: Maybe you are the first one on this conference spoken call. Oh, my goodness. Who is she? Who is she?

Dean: She's. She's a bot. She's not real.

Dan: She's not real.

Dean: She's not real.

Dan: She doesn't sound. I've heard worse sounding bots, Dan.

Dean: I have been experimenting, playing around with ChatGPT4O, and I use it primarily in voice mode, meaning, you know, I just say things to it. And it has an amazing Scarlett Johansson, like, voice that has zero. Not at all like Siri or Alexa, you know, where those voices definitely sound like they are bots. This my GPT4O. I think her name's Juniper is the. The voice that I chose. She sounds like a real person, I mean, and has like, real tone, real inflection, real, like, conversational feeling to it. And I realized that we're. I don't think we really understand what we have here. You know, Like, I mean, I, I look at it and I think, you know, imagine if that was a real person.

Dan: Now, when, now when you. Now when you say we, who are you talking about?

Dean: I mean, the collective royal we. I. Yeah, I'm starting around.

Dan: Yeah.

Dean: I just think we as. When I say we, we as a society, are we as the people collectively using this. It reminds me of this Seinfeld episode where Kramer got this or Jerry got his dad this, you know, wizard organizer. And they always use it as a tip calculator, like the least of all the functions that it has. They're just excited that it's a tip calculator. And I feel like that's the current level of my adoption of Juniper, you know?

Dan: Yeah. I think the big thing is what you. Let's say a year from now, you're using Juniper for a year. What do you think will be different as a result of having this capability? New capability?

Dean: Well, I think it's operator. You know, I think it's operator dependent. You know, I think it's up to me what I think if, if you said to me, listen, I'd like to introduce you to Juniper. You're going to come here and she'll be within. To follow you around. She's going to be here within three feet of you, or just discreetly out of sight, whatever you. But whenever you call, she'll be right there. She is a graduate level. She's a graduate level. Student. She could pass the bar. She knows everything that's ever been recorded. She speaks every language. She never sleeps. She can write, she can draw, she can do graphics, she can do coding. Whatever you like. And she's yours. 20amonth. Have fun.

Dan: Yeah. Do you think you'd use it?

Dean: Well, that's my question is that I. It feels like I'm not using it and I have it. You know, that's exactly. That's essentially what I have. I've got it in my pocket. You know how they said, you know, the ipod was launched with the promise of a thousand songs in your pocket? Well, I think this is really like, you know, an MBA or a PhD or whatever you want in your pocket is essentially what we have. And it's. Find it very. I find it very interesting.

Dan: I think I. No, I think it's unique, you know, and it's brand new. But what problem did you have that this solves?

Dean: Well, I think that's. I think that it's not per se, a problem, but I think that we're. I really have been observing and thinking and I've said it, you know, in, in lots of our conversations that I think that 2020, if we take the 50 year period from 1975 to 2025, that we've pretty much set the stage now for a new plateau launch pad. Kind of at the same time, I think that once we understand and people. I think it's almost like the iPhone has had the app store that became what Peter Diamandis called the interface moment. Right. That was the, you know, that, that allowed, once people realized that the capabilities of the iPhone to both measure geographically where you are at any. Precisely at any moment. The gyroscope thing that can detect movement, the sound, the camera capabilities, the touch screen, all of those things. Well, people realized what the baseline capabilities of the phone were. They were able to architect very specific, you know, starting with games, very specific ways to use the capabilities that are built into the phone. And I think that right now it's almost like it can do anything. And I think that we need to figure out the very specific use cases. And I think we'll see.

Dan: You keep saying we, but I don't think we is going to do it. I think you. I know who we are. Do we have a cell phone number? Do we have a street address? You know, fair enough, fair enough. I think you're having a very interesting personal experience with a new technology. Yeah, I don't know if, I don't know if anybody else is going to be in on this, you know, but the big thing is how are you going to set it up so that you can prove that this is valuable? I mean, let's say three months from now, time you come back to Toronto for your next strategic coach Free Zone workshop. What let's say three things. You're going to test out and see if the inclusion of this spot with a very sexy Scarlett Johansson voice. This isn't the, this isn't the issue that she sued somebody for, was she? She had a big lawsuit going.

Dean: I mean, I think it's. Yeah, I don't know. Actually this voice is. It's not exactly her, but it's, you know, it's that tone and things. So. Yeah. So I don't know that it very. It's a pleasing voice. Much more pleasing and personal than Siri or Alexa, for instance.

Dan: Yeah.

Dean: But yeah, I think you're absolutely right. It does come down to. And I think that's where the paralysis of, you know, the. It can do anything.

Dan: But, you know, you know, where my mind goes, it's which. How that I already have. Am I going to assign this capability to. So that I don't have to spend any time whatsoever interacting with. With this Bob. But my. Who's a, you know, who's alive human being working for a strategic coach? Would that person actually work do this? You know, and actually, yeah. And I tested out for three months. What are you getting done faster? So, for example, we have an AI newsletter that rewrites itself every two weeks and chooses new content, designs it and goes out and it uses up one hour of my. Linda Spencer, who's one of my team members on the marketing team. And it's very interesting. I mean, we have about 2,000 people who read it and they grade it and everything like that. But the only thing I have to do every two weeks, she said, here's the news, here's the results from the last newsletter. Here's the design and contents of the next newsletter. Yes or no. And I'll go through and I say, yeah, looks good. Send it out.

Dean: Right?

Dan: Yeah. Now that's not freeing me up because we never had this capability before. It's a new capability. Right, okay. And it's been going for. It's been going for about nine months now. And people will talk to me about it and, you know, everything like that. But I haven't seen that it's made a huge difference in the crucial numbers of strategic coach, which are, you know, marketing calls. Are we generating great leads that people are talking to Us about are they signing up for the program? Are they, you know, whatever. So the normal measurements. So I think with any technology, I. The first thing I would establish before I got interested in the technology is what are the crucial numbers that we have that tell me that our business and myself are moving forward? And then whatever I'm going to use the new technology for, it has to have an impact on those numbers.

Dean: Yeah, I think that's. Yeah.

Dan: Because you know, the amount of productivity. I'll use the United States as an example. You mentioned 1975-20, 25, 50 years. The level of individual productivity in the United States was much higher in the 50 years before 1975. Since it has been for the last 50 years since 1975, even though there are these amazing, you know, books and that about how productivity is going through the world with the microchip. But the actual numbers which are, you know, gathered by the US Government, the US Treasury Department, US Department of Labor, indicates that the level of individual productivity has actually gone down in the last 50 years, even though the excitement level of productivity has gone through the roof.

Dean: By what measurement? What are they deciding is product dollars

Dan: per dollars of economic activity proved per hour per worker? Okay, that's, that's how productivity is measured. The number of workers you have, the number of hours they work and the number of the amount of economic dollars that their hour of activity produces. The productivity was much higher. Total, total for the entire. All workers.

Dean: That is it all productivity or personal productivity?

Dan: Like, are you saying no all productivity? No, the entire cash. The GDP of the economy measured by the number of workers, by the number of workers is going down?

Dean: Is down.

Dan: No. Yeah, since 1975. It's not as great as it was from 2019. 25 to 1975. So that 50 year period, the productivity levels in the United States were bigger than the last 50 years.

Dean: Wow, that seems. That's surprising. What do you think that means?

Dan: Well, a lot of people are really excited and involving themselves in technological activity that produces absolutely no productivity. Yeah, they're very, very excited. They're very excited and they're getting very emotionally connected to this activity. But you know, I'm not saying that's not a great thing. I'm not. Maybe they're having more fun. Maybe they're does, you know, maybe they

Dean: have what actually counts as gdp?

Dan: Well, GDP is amount of sales.

Dean: Okay, so would the advertising sales that Mark Zuckerberg makes for Facebook count as GDP or is it only in physical, like, you know, shippable goods or whatever?

Dan: Well, whatever you have a dollar spent on something that constitutes a sale.

Dean: Okay. So any. So advertising. So Google and Facebook and Netflix and all of those things count as gdp?

Dan: Sure. Okay.

Dean: All right, then that seems impossible.

Dan: It seems impossible, but it's true.

Dean: That's pretty wild.

Dan: Yeah, yeah. We're not. I'm not saying that Mark Zuckerberg isn't making a lot of money. I'm not saying Mark Zuckerberg isn't productive. My feeling is that the technology is created makes a lot of other people non productive.

Dean: Yeah. And I wonder, I mean, that's a. Do you think, you know, if you measured that in terms of the total population versus the workforce, is that what. You know, I'm just looking for some explanation of this. Right.

Dan: Like somewhere along. Yeah. Somewhere along the line there has to be an economic transaction for it to constitute and everything else. And see, this is the difference. China talks about its gdp, but they don't use the same term that everybody else in the world uses. They use the economic value of what they've produced. Okay. So they can produce a million machines and they're sitting in a warehouse and they count that as gross G. Gross domestic product. But there was no sale. It's, you know, they spend it. It was an economic activity. There was a transaction there, but there was no sale. Okay. So I think that's the big thing. It doesn't count unless there's a sale. GDP doesn't. It doesn't count as GDP unless there's a sale, somebody makes money. Yeah, okay. Yeah, yeah, yeah.

Dean: I mean that. It's pretty.

Dan: No, I'm not saying it's not exciting. And here's the thing. Maybe, maybe it's a. An A and I. It's what I would. R D stage. The last 50 years have been RD R D stage for the next 50 years, which are going to be a hundred times bigger of gdp. Okay, that may happen almost. Yeah, that's not happening yet. Yeah, yeah.

Dean: I mean it's pretty. Yeah, it's pretty wild. I mean, you can definitely see like the capabilities of. You know, you can definitely see this replacing many customer service interactions, for sure. For instance, it's like a. You can definitely see that going away. That there's no. Not going to be a need for humans manning a customer service telephone center for. I don't know, you know.

Dan: Yeah. I mean, if it's good. I mean if it's good and you know, it depends upon the service it's being. Being talked about, but if it's good, you know, maybe it does the Efficiency is not effectiveness, you know, and effectiveness is that you made a sale. Efficiency is we took all the activities leading up to a sale and we made them more faster and easier.

Dean: Yeah.

Dan: Process less. The question is, did you get a sale out of it? Yeah. So I don't know, but I think there's some bit of a magician show going with a lot of different kinds of technology. You know, I mean, it was like somebody was saying, you know, they were talking about EVs and specifically they were talking about a Tesla. And he says, do you know how much faster 0 to 60 is in a Tesla than any gas powered or, or, you know, And I said, to tell you the truth, I don't know to tell you, you know, you know, all the things I've been thinking about since last Monday, that. I'm sorry, I just didn't get to that one anyway. And he says, well, it's easily a second faster. I said, good. I said, now where do you do this? There isn't any way. Where in Greater Toronto, the area of Greater Toronto, six million people, where you can go from zero to 60 on a city street in three, two seconds, you know, and everything like that. He said, yeah, but, boy, you know, you know, I mean, just think of that, how much faster you can go. And I said, yeah, but Teslas don't go any faster in Toronto than any other car.

Dean: That's true. It is.

Dan: And usually they're stopped.

Dean: Yeah, that's exactly right.

Dan: Yeah. So I think the tech magic show, I think it multiplies people's imagination, but it doesn't multiply their results. You know, I think there's. There's something about. And I think this is great. I mean, what you're telling me. And I've had some really boring people on the other end of a phone call and Scarlett Johansson would really, you know, it would liven it up a little bit.

Dean: Absolutely. Yeah. Yeah, exactly.

Dan: Yeah. I was noticing in Cleveland hired Jack Nicholson and they still use it. It must have been 20 years ago. All the announcements, the regular announcements, you know, like, don't leave your bags unattended and things like that. There's a whole bunch of just what I would call airport announcements. And they have Jack Nicholson doing it and you stop and listen every time it starts. You know, it's very effective. And I'm sure. And I'm sure Scarlett. I'm sure Scarlett Johan could do a good job too.

Dean: Absolutely.

Dan: Yeah.

Dean: Yeah. It's so, it's so funny. I mean, that seems. I'm just dumbfounded by the fact that productivity has decreased in the 50 years that we're talking about here.

Dan: Yeah, well, think of the 50 years, though. And you gave me that great book. Yeah, you know, it wasn't. It was. You gave me the book that was 1900 to 1950. 1925, but 1925 to 1975, the entire country was being electrified. You know, that they're laying in lines and everybody was, you know, the farm that I was on, I was born in 1944. That farm was electrified in 1928. So it was only 16 years that they had electricity.

Dean: Right.

Dan: And, yeah, they were putting in the entire water systems. The Tennessee Valley Authority was putting in all these dams and the electric plants. You know, Lake Mead, as a result of the Hoover Dam, they were putting in all those dams. And that. That just produced enormous jumps. And, you know, and the cars were going in, the gas systems, you know, all the infrastructure for gasoline was going in and everything else. It was just a monstrously productive period of time. And then all the production that went into the Second World War, which they then had as productive capability after the war stopped. And so they had all the manufacturing capabilities, you know, and, you know, and so. But there's. See, the thing is, the real jump that's happened is the jump in computing. There's no question there's been a monstrous jump. It's a. You know, it's a billion times since 1970. It's a billion times, but doesn't translate into money. And money is what productivity is based on. How much more money are you making per hour of human labor now? Maybe somebody will say, well, we got to start counting the robots in our gdp. Something is doing work.

Dean: Yeah, Just. I mean, wow, wow, wow.

Dan: The only problem with you, you know, the only thing about robots, though, they're shitty consumers.

Dean: Yes, exactly. That's so funny.

Dan: Yeah. They don't buy anything, you know.

Dean: Yeah.

Dan: A computer is a good worker. You know, it doesn't take breaks, doesn't get sick. You know, doesn't form unions, anything. But no, it doesn't go home. It doesn't have. It doesn't have a house, doesn't have furnishings, you know, doesn't need furniture, doesn't go out to eat, you know.

Dean: Right, right.

Dan: It's a.

Dean: You look at. I. I mean, we're definitely in a stage right now where there's such. There's opportunities more than ever for economic alchemy. Creating money out of nothing, seemingly compared.

Dan: I'm not sure how that happened.

Dean: I think since in the digital world, we're essentially creating money out of ether, you know, out of attention even in a way that if we just take the attention economy or the portion of the money that is derived from the advertising world, where it was print ads, television ads, radio ads, those were things that were kind of happening in 19. Right. And, but they were selling sort of physical goods. Whereas now I remember having a conversation with Eben Pagan about this when I did the book stop your divorce in 1998, when it was when PDFs were just coming to be a thing where you could create a digital document that didn't require printing a physical book and you could email that or somebody could download it. And I just realized that, you know, in that we've literally sold $5 million of a picture of a book, not physically printing these thousands and thousands of books. It's literally no zero physical good. That's why I wondered about whether the GDP is only measuring, you know, physical things. But because we're in a, we're definitely in a time where you can, you know, create money from nothing. And the way that was driven was from.

Dan: Well, you can't create. You can't create any. You can't create any. I don't think you can create anything from nothing there.

Dean: No. I mean, nothing.

Dan: Okay. Nothing physical.

Dean: Okay, that's what I mean. Yeah. Like you look at it that the book, you know, we created the book and turned it into a PDF that was put on a website that there's no physical manifestation of. It's only digital. You can only see it online. People would search on Google for save my marriage or how to stop a divorce or any of the keywords we could magically get in front of those people on their screen. They could click, oh, stop your divorce. How do I do that? They click on that. They read this digital. It didn't cost anything other than what was paid for was that we paid Google for the, you know, for sending that, you know, the ability to display that person, that opportunity to somebody. We paid Google every time somebody clicked on that ad and then they would buy the book and it would automatically take them to a page to download the book. There was no inter, no human interaction and no physical exchange. It was all 100 digital. And that was where, you know, I started referring to that as alchemy. Really, like creating money out of, of bits, you know. Yeah, yeah, yeah.

Dan: I think there's no, I think there's no question that we've moved into a, what I call a non tangible realm of creating value, creating property and everything else. But at the end of the day, it all adds up somewhere where this constitutes an economic transaction. And as far as the accountants care, they don't care whether it was something physical or sold or everything. And, and, you know, and there, there's taxes that are taken out of that, you know, and. Yeah, I don't see that. I don't see the remarkable difference. You're using a different medium to. But there is work that goes into that. And you had a big payoff with one, but there were another thousand people right at the same time you were doing that. And their results, they put in a lot of work, they put in a lot of effort, and it didn't produce any money whatsoever. Okay. So their efforts go into gdp, your efforts go into gdp, and there's way more of them than there is of you. You. So it brings you the overall results down. And you know, so. And we kind of know, we kind of know that, you know, productivity numbers, you know, like on a year. I know people talk about, well, that productivity is going to go up by 20% as a result of that. Well, that may be true for a single company, but that's not true for the industry they're in because their new thing going up by 20% may actually make obsolete five or six or 20 other companies who have had productivity that a year before, but now they have no productivity at all. So their loss of productivity is balanced against the gain of productivity.

Dean: Yeah. That's interesting. I guess you think about that. That could be true in all the casualties of the digital transition here. Right.

Dan: Like. Well, certainly the advertising world. Certainly the advertising world. I mean, the before Mark Zuckerberg and before Google newspaper, like the New York Times daily edition was very thick. Yeah. Half of it was advertising. Now it's very thin. Okay. Because they don't have the same. Yeah, but there's winners and losers, you know, in this and you have a technological breakthrough, you have far more losers than you do winners.

Dean: Yeah, I'm looking at like, I'm with. I was just listening to an interview with, that Tucker Carlson did with someone. I forget who, some former CBS correspondent, you know, and they were talking about the new. You know, what's really changed now is the reach capabilities. You know, like Tucker really primarily being on his own platform. But using the reach of X has, you know, it's. The audience is accessible to everybody as opposed to him. In the beginning of their careers, the only way to get reach was to be signed to a digital or assigned to a traditional network where the eyeballs were. But now The. The eyeballs are accessible to everybody and it really becomes. These are my words. But it's more of a meritocracy in a way that you're, you know, that it's available for everybody. The cream definitely can rise to the top if you've got a voice that people resonate with.

Dan: Yeah, yeah, yeah. I mean, and Tucker's a star. Tucker's a star. He's got his following. He's got probably a couple million followers, whatever. He was big when he was on Fox and, you know, he had the top numbers on Fox and everything like that, but there aren't two of him.

Dean: Right. And you can't replace him with an AI either, you know.

Dan: No, but what I mean is we pick out the winners. It takes a lot of losers to get to a winner, you know, and. And I think this is more extreme in the Cloudlandia world than it is in the physical world, you know, I mean, I think the. There's a thing called network effect, and the network effect is you can only have one Amazon, basically, you can only have one Amazon because the nature of Amazon is to suck everybody's customers up into one destination. There aren't five Amazons competing with each other. And that's what digital, digital does. You know, A person like Taylor Swift couldn't have existed 20 years ago. They wouldn't have had the reach.

Dean: Yeah, it's true.

Dan: And she's got the reach today. I mean, she's coming on, you know, and she's got a lot of things going for her. She's very attractive, she's very productive. She pumps up. She pumps out songs all the time. And the songs seem to resonate with a mood in the public right now. And everybody's got their cell phones and everybody's got that. And I. And there. And what I'm saying is if you have one Taylor Swift, you can't have two.

Dean: Well, yeah, that's. I mean, it's. I wonder. You start to see that she's just a. She's one voice, right? Like I look at. I've been following rabbit holes like up the Chain, you know, and I start. So Taylor Swift is a good example that many of her biggest hits and biggest success have been in collaboration with Max Martin, who is producer, who I often talk about and refer as, you know, he's now moved into. He's the second. He's got the second biggest number of number one songs to his credit, right behind. He just past Paul McCartney or John Lennon, and only Paul McCartney is ahead of him now. He's about five songs behind Paul McCartney. What I realized is, you know, there's a way that it's kind of like you get Max Martin's voice is really what is, you know, behind most of the. The most popular music or much of the most popular music. And yet not many people could pick him out of a lineup. And then I went another layer up. It just dawned on me, like in the last couple of weeks here, that the real catalyst to Max Martin's success was Clive Davis. Who is. Do you know who Clive Davis is? The former or still record executive. He was the head of so far. Your records.

Dan: So far. So far. You're introducing me to a lot of new people. Okay, great.

Dean: Well, I just love this, that, you know, Max Martin. I've been saying as that's the thing. Like you think about one thing. Max Martin's one thing has been making hit records, right? That's all he's done making pop songs since 1996, or what is first number one. But if you trace it all the way back, the catalyst to it, because he was in Sweden, there was a group years ago called Ace of Bass and they had a number one song. But when you go all the way back to how that happened, it was because Clive Davis, who was the head of Columbia Records and all its subsidiaries, Arista and J Records and all of these things, he found that song. He's like a guesser and better. You know, like what you're saying. He was guessing that song is going to be a hit. And he signed Ace of Bass to bring them to America. So he plucked this obscure Swedish band out of and brought them to America and on the wave of that created the opportunity for Max Martin to work with all these great artists that happen to be under the direction of Clive Davis. And if you go even one layer beyond that, the guy that owns Bertelsmann, you know, G Music Group in Germany, they own a lot, almost all the record labels kind of thing. It's him seeing Clive Davis and putting up the million dollars for Clive Davis to start this record label. It's amazing that it all kind of, you know, goes back to, you know, capital.

Dan: But the big thing is none of that has to do with any productivity.

Dean: Yeah, that's what I. That's the thing. I wonder, you know, I mean that really.

Dan: No, I. Well, what you're talking about is you mentioned a name. Yeah, he does this and he's very successful and he's famous for being successful and. But at the same time that he was doing what he was doing. There were 9,999 who were waiting on tables and doing this on weekends and nights. Yeah, okay. And they weren't making any money at all. So what I'm saying is when you pick a winner out and you see, see how productive they are using new technology, you also have to account for the people who are using the new technology and not making any money at all. And therefore it's not more productive.

Dean: Yeah, yeah.

Dan: And I mean, you know, now our. We haven't talked about him for a while. Mr. Beast.

Dean: Yeah.

Dan: And people say see what, see what you can do when you're 18. You won't see anything because he's so unique and he had such a set of circumstances that there's nothing that he does that is repeatable by another person.

Dean: I mean, you know, he. Yeah, he just became. Just in the last.

Dan: We haven't. I haven't heard anything about him. Is he still doing stuff? I don't know. Is he still doing stuff?

Dean: Yeah, yeah, just. He just became.

Dan: Or is he retired at 28?

Dean: No, full Steven Head.

Dan: He's got a 300 foot.

Dean: He just became the number one. The number one subscribed channel on in the world. On. He was the number one individual. But there was this, you know, T series channel in India which wasn't a person, you know, a different thing. And now he's the number one. He's the number one thing. He's now he's working on an Amazon show. He's doing a. Taking his stuff to. To Amazon still full steam ahead with his, with his videos. But he's doing a big game show series in with. Under the Amazon banner.

Dan: Yeah, yeah, yeah. It's really interesting because you know, again, I go back that it seems to me that a lot, you know, and I've made this statement before, is that a new technology comes out or a new form of a new technology comes out and a whole series of people say, I'm going to create a new company based on this technology. And I want, you know, I need some early investors. I need investors to get. And so there's a whole industry for doing that in Silicon Valley and other places. And so billions of are raised not just for the one, you know, not one investment, but for let's say 50 investments. And none of them go anywhere. None of them go anywhere. You know, nothing happens. Okay. But people did make money because it's based on a Ponzi scheme kind of thing that the early investors get paid out by the late investors who end up nothing yes, Nothing. And everything else, none of that represents productivity.

Dean: Right.

Dan: Lot of action, a lot of excitement, a lot of money, but no product, no productivity. And we're seeing that with AI. Goldman Sachs, the big investment bank, came out that going on two years since OpenAI, we just don't see that there's any money to be made with this. Except if you're like the chip maker Nvidia, they make a lot of money and they're very.

Dean: Yeah, right, right.

Dan: And I think the reason is that, I think that AI, if I look at the next 10, 10 years, I think it's going to be, it's going to be very effective, it's going to be very useful and it's going to be very important for solving complexity problems that we already have on the planet. Okay. And you know, a great example is just large city congestion complexity like Toronto's, I, I think may have the worst traffic congestion.

Dean: I noticed as a, I did notice a big difference in that in.

Dan: Yeah.

Dean: Even in the five years since I was there.

Dan: Yeah. And the main reason is that they're making new cars, but they're not making new roads.

Dean: Yeah. And there's, you know, I noticed that they've actually, you know, they added a lot of bike lanes. Bike lanes too, which have taken out some of the actual lanes.

Dan: Yeah, yeah. So without some new kind of solution to congestion. And I think AI is the perfect tool for this and that all the traffic lights, all the traffic lights in the city are a single system and you're just changing the frequency of the lights changing and everything around the cat. And there's a sort of a master view how, you know, you can reduce the amount of people just stuck in the city by 40% if we just get all the lights. That's a complexity problem. You know, and for example, the other thing is they haven't, you know, for all the study of weather is probably the most complex system that we have on the planet. And to this day, they have no notion what effect clouds have on climate. You know, they don't. They really. Clouds are just very complex. So if you had the ability to, I mean, they know different types of clouds and, you know, different, different things that happen when you have different types of cloud. They know that, but there's no unification of their understanding of the cloud system and. Right. So you'd have to, you had. Apply it to that. Yeah. Now you're not creating anything new with this. You're solving an existing problem. My sense is that the best use of technology is always to solve Some problem that you already have, not create a new opportunity.

Dean: That's interesting. So maybe that's how.

Dan: I mean. Yeah, go ahead.

Dean: I was gonna say maybe that's how I should be thinking about my relationship with Juniper.

Dan: Yeah. What complexity problems. Yeah, what.

Dean: Exactly. What complexity problems do I already have that Juniper could solve for me?

Dan: Yeah, like getting out of bed in the morning. That's a complexity problem.

Dean: Yes.

Dan: Yeah. When does my first coffee arrive? You know, I mean, exactly.

Dean: Yeah.

Dan: Why am I still thinking about this? Why at this late date?

Dean: Oh, man, that is so funny. It is funny. Like, the funny thing is I posted up on Facebook right before we, before we got on our podcast today. I took a picture of my. I have these, of these four Seasons Valhalla coffee cups and I took a, I made a coffee before our here and I posted up a picture of it right pre podcast caffeination prior to the, prior to our podcast here. So I'm fully captured. I'm on the. I'm on the juice.

Dan: Yeah. I will tell you this. Chris Johnson, great thinker and the Free Zone program he's got, it's not his system. He, you know, he's licensed his system from someone else, but he had 32 callers to set up meetings with their primary salespeople. Okay. For his company. And he's in the placement business. He finds really good, you know, high level people to go into construction companies and, you know, engineering companies. And he was telling us that his 32 human callers could make 5,500 phone calls and produce a certain result in a day of phone number. And since he's brought in his AI system, they can do 5,500 in an hour and produce a better result of people agreeing to phone calls. Well, that's productivity.

Dean: Yeah, I guess so.

Dan: Yeah.

Dean: Pretty amazing, huh?

Dan: And he let go is 32. He let go is 32 humans.

Dean: Oh, my goodness. Wow. So these are, this is AI making outbound phone calls.

Dan: These are all AI and they've got complete voice. Voice capability of responding to responses and everything else. And then they get better every day. They have sort of upgrades every day for it. And that's productivity. That's productivity. That.

Dean: Yeah, there's. Yeah, that's a, that's an amazing story. I mean, you start to see, I just look at the things. Even when we had the, you know, the AI panel at Free Zone in Palm Beach.

Dan: Yeah.

Dean: You know, just seeing the things. Even what, you know, Mike Knicks is able to create and the things that Liora is doing and yeah, you just Think, man.

Dan: I think we're. I think we're. I think we're early.

Dean: Yeah, absolutely. We're early. And that's what.

Dan: Yeah, I mean, I think we're in the first or second year of the Internet with this, you know, like.

Dean: Right, exactly. I agree. That's why I say that's why in my summation here, I'm kind of thinking, you know, 20, 25, give it another 18 months. It's only 18 months old now, when you really think about it. Right. This is. It's 18 months and give it another 18 months and will see that people. You're already starting to see that people are taking the AI capabilities and they're honing it into an interface that is a logo maker, for instance, or AI. You know that it's already honed into the ability to specialize in making logos based on your prompt or. And I think that's where. That's what I meant by the interface moment is people are going to start carving out packaging very specific outcomes from the capabilities. Like, if we have these capabilities, what can we do and just deliver that specific outcome rather than the capability to create that outcome. That's why it's funny that that's kind of parallel to what I've been saying. I've seen people that are taking and training large language models based on your, you know, all of the, you know, let's call it all the Dan Sullivan content that's been out there and then touting it as, you know, having Dan Sullivan in your pocket that you can ask Dan anything. But I think the ability to ask you anything isn't as useful as the ability to have Dan ask you things.

Dan: You know, I think that's the question. No, and that's where. So in the. This, the last quarterly book and the one we're finishing right now. So it was. Everything is created backward. Where the tool we featured was the triple play, and then the next one is called Casting not hiring. Where the tool is the four by four casting tool. We call it the four by four casting tool. And this is where I'm asking them questions, right? Okay. I don't see any value whatsoever of them asking me questions, right? Because I'm not getting the best. I'm not getting the benefit of the question. Some software program is handling it. So I'm not learning anything. And I've got a rule that I don't involve myself in any activity where I don't learn something new. Okay, so there. So there's getting the benefits. But plus we'd be competing with ourselves. I love it.

Dean: All right, well, off we go.

Dan: I will phone you to the world next week. I'll be at the cottage. I'll be looking out at a mystic blue lake while I'm talking.

Dean: Oh, wow.

Dan: It's really good. Yeah.

Dean: Awesome. Well, have a great.

Dan: Okay.

Dean: And I'll talk to you next week.

Dan: Thanks.

Dean: Thanks, Dan.

Dan: Bye.