A (5:00)

Just to point people to a resource. On that advisory point, I had somebody named Jeff woods spelled with a G, G, E, O, F, F Woods, who wrote the book AI Driven Leader and has a mastermind to that effect. But he shared in the first 15 minutes of the Unemployable podcast that he was on. I don't know what episode number it is, but just go to Unemployable wherever you get your podcast. Put in Jeff woods on the Unemployable podcast with Jeff Duden. The first 15 minutes of that. If you're a nascent AI user, if you don't have, if you're not building things already, or even if you are, this crit methodology that he does, which, which stands for context, role, interview and task. And he teach. He taught us in the first 15 minutes of that podcast how to use in any AI model, this methodology to basically create an advisor. And then he went on to create, you know, he has an advisory board, his future self. I think he's got Steve Jobs on his advisory board. So he basically has an entire cadre of personalities that he's engaged with, and it creates just great outcomes. So he shared a couple things too, about how to run your annual planning using these tools where everybody's using the methodology all at once. And, you know, it's just. It was a really fascinating podcast. It's one of the most shared that we have. I sent it out to all Homefront Brands employees and all Homefront Brands franchisees, and I challenged them to use the methodology to come back to me as to how they're solving business problems. And the responses that I got were amazing. So now that's interesting though. But we moved forward in AI as an organization as a result of that one thing that we rolled out. Now when I interview our employees, they will say, you need to tell me what's next, what to use, where to use and how to use it. So I'm going to kind of get to a. I'm going to do an interesting question. I don't want to go too deep on it here, Jeffrey, but at what point do employees, developers like you might have, coaches that we might have, at what point do they say, if I continue to develop in this AI, it's clear to me that I am building my replacement and, and at some point they stop, you know, doing. Using the technology to do the work out of survival mode or or whatever it is. And I think I, I actually, you know, as I, I thought about that last night in anticipation of our meeting here today, of our, of having our conversation and I thought, you know, as I think we just had the CEO of Microsoft on talking about what percentage of white collar jobs are going to be gone over the next 18 months, I think it's going to be a more and more common thing where people are looking at it and they see the writing on the wall where 80% of what they were doing they're now putting into the AI and they're seeing their roles become maybe less relevant. They get concerned about that. Are you seeing that in your development teams? How do you deal with that? Or is everybody just like, this is going to make our life better, easier, it's improve our utility of our product? Tell me what you're seeing there.

B (8:20)

Yeah, so I won't, I won't sugarcoat it. I'll just say it as it is. Right. So the first thing is if you're doing a job or role where the task is repetitive, you know, I do the same thing all the time, or I'm writing, you know, like a junior developer, I'm going to write, you know, like simple code, right? That's simple things. Those things are probably going to be replaced by AI because somebody above you or, you know, somebody more senior is going to be able to replicate that and is not going to need a junior, a junior developer. I mean, like one example was, I think like Elon Musk. There's a story where, you know, he had this executive assistant and she wanted to go on vacation and then, you know, she came back and then, you know, she wanted a raise and he said to go on vacation and come back. And then he said, hey, I don't need you anymore because I'm able to do this on my own, right. With tools. So in some cases, depending on what you're doing, I think you could be replaced. But what I'm also seeing is that if you are creative and you have ideas, it was being held back by development or by held back because it was this friction point of like, how do I go from what I have an idea for to what I'm going to create? That's not going to be replaced by AI because AI, Remember when we say generative AI, it doesn't come up with new ideas, it comes up with suggestions and things like that. But you still as a person still have to do that execution. The other thing is in franchising, we talked about engagement and other Things, the human relationship element is really important. I don't go to a doctor because I couldn't upload the file and kind of self diagnose myself. I go to the doctor because I sort of trust that person and I recognize what they're trying to do. So I think when technology initially comes in, we focus so much on what the technology can do and then we sort of extrapolate that hey, it'll finally be able to do everything. But the fact is that it will not be able to do everything and then we will see the limitation. Remember, full self driving like you know, we'll always keep getting closer to it but it'll be very. But the last mile problem is a real problem. So I think like if you are a person in any job or anything that you do, if it's creative, if it's design oriented, if it's something where you, it's relationship based where you know, you have to gauge the empathy of somebody else and like, and interact with them at an emotional level, which is what makes us make society what it is. Cannot be replaced by AI because AI can pretend to have emotions, but at the end of the day, even when you type in something to AI, it converts it to zeros and ones. It converts it into a token. And what a lot of people don't realize is that when an AI is responding, it actually doesn't know what the next word is going to be. It's based on a probability theory, it uses probabilities and then says constructs things together. So it sounds really smart and really interesting. So I think if you are, you know, if you do repetitive tasks, obviously that's a workflow, it'll be, you know, automated. But if you, but if you are, you know, dealing with people, creative, solving problems that are innovative and those, I think you will still need people and AI will make them better. So the speed of innovation will improve because of AI.

A (11:47)

AI, yeah. It's interesting that there was such a movement towards the analytical, the technical education, coding tech, people making money in tech and all that. And now because that's more easily automated, it's kind of the rise of the creative and the, the person who can ask, who can see the problem clearly, who can ask the right questions and at some point I don't know how a calculator works, I just know that

B (12:18)

it does and you use it. It didn't make you any less valuable than before. This is the same thing with when printers came along. It didn't mean that it reduced people working in offices. You still use printer. I think that's the thing with AI. I wrote an article recently which says AI makes people into builders. And that's what it is, right? It's moving the managerial class into builder class. So if you're just managing people, that's the other area I think that AI will probably get rid of unless, because even if you're managing, you still have to be using AI and building ideas and concepts that, so it'll create a society probably more of builders and less of managers and less of people doing the same tasks over and over again, at least on the white collar realm.

A (13:07)

And I'm hopeful that franchising is an area that's going to be more insulated. And the reason for that is one of my basic premises when I talk to people about franchising is that franchising works best when a product or service needs to be delivered locally by a human. So by and large that's what franchising is. If somebody, I've had people come to me with franchise concepts that were based on a technology or based on something that was going to be shipped and I'm like, that's not Amazon proof. I said that's not that you can't, that's not going to be need to be done forever. It can be done by Amazon or if it's a technology, you just do it centrally. So there's some businesses, there's some organizations that just lend themselves to be managed centrally. You don't need a franchise system because at the end of the day the local execution of the introduction of the product, the delivery of the service, the fulfillment, fulfillment of it, the personal touch, the analysis, we're going to paint this, we're not going to paint this. We're going to move this furniture, we're not going to move that. You know, all of the things, you know, up until this point in time, those are perfect franchise models. So now we're sitting here and it's always worth putting the date out there. So we're sitting here in February of 2026 and there's mid short videos all over the Internet about Chinese robots that are dancing all over the place. And I think Elon Musk just decommissioned a couple of his Tesla models to allocate those 14 million square foot factories to Optimus production of Optimus robots. So any, he expects that Optimus robots are going to be in consumer production by the end of 2027. So you know, that being said, a humanoid, you know who I, you know, most of the, most of the conversations that are going on right now are around the AI replacing our thought work, our white collar work. Okay. But shortly after, you know, after that, if you're paying attention, then what's going to happen to the blue collar work? What's going to happen to the service delivery? Are we really going to have a crew of robots jumping out of a self driving car with painters overalls on coming out and painting our house? I'm not sure. I don't know anymore.

B (15:34)

Yeah, so I think this is, this is another interesting question. When I talked about the last mile, last mile problem where if it's repetitive or it's mostly repetitive, I think AI can do it or whether human interaction doesn't matter, AI can do it. So I think, you know, drones, good example of AI anything with military, like, you know, you don't need to put people to fight wars for you. You can have, you know, an army of drones or you can have like, you know, these robots go and do that for you. I think like, you know, like fighter pilots. I don't know if you need fighter pilots. At some point AI can actually, you know, probably, you know, you can use that because there's no human, you're not engaging a human being on the other end. Right. And even for constructions or any of these other manual tasks like where if I pick a brick here, put a brick there, like car assembly line type stuff. Assembly line stuff, yes, you can do that. Because we've been trying to build robots that can do complex tasks and think about it like rearrange your home and all very hard to do. Yeah. There's one thing to say, I have a vacuum cleaner that goes and vacuums out stuff, but it's not mission critical. Right. If it misses a piece of dirt, nobody really cares about it. All right, but what about a robot doing surgery, like a heart surgery on you? Right. Like, like, like some people might, you know, be okay with it at a really low cost, but most people are probably going to still want to have a surgeon associated with it. But I'll make another, what's called argument that if you a AI fi or robotify human interactions, it can actually hurt your brand. So think about it. And I always think about say Starbucks, right? So what made Starbucks special was that you could walk into a Starbuck and there was a human being and they would, you know, know your name, write your name, you'd sit there, you know, you could, you know, it was a meeting place for people. They looked at the data and said, you know, how do we make Starbucks more efficient and they looked at all of this data and analytics and said, you know what, we're going to build this app and you're going to open order in advance and you know you're gonna get all that stuff. We're gonna do drive throughs and all of this other stuff. Remember, like they went through it. As a result, it lost its character of what it was. Starbucks no longer focused on the human interaction. It was more about efficiency. Once it became more about efficiency, it became just like another fast food place that you go to and for efficiency. And if I'm trying to pay a premium, why would I just go to Starbucks? So that's another example of like, even though it was nothing to do with AI, but what it was is that when you move from human to mechanical, you lose something in the process. For some businesses it might be a positive and it's okay because that's what you're trying to do. Right. But for some businesses, you know, the reason you have customers is because of that human touch.

A (18:20)

Right.

B (18:21)

I may order a pair of jeans from Amazon, but I don't think I'll order my daughter's wedding gown from Amazon.

A (18:27)

Right.

B (18:28)

You know, like that's the thing. Right, right.

A (18:30)

So might order the husband from Amazon

B (18:36)

or he's from Amazon. My wife worked at Amazon. Aws. Yeah. So anyway, so that's the way I think about. Right. You know, I think AI is a great technology, it's very capable, but we always have to keep a balance of where it is. So I think on the development side, like, you know, I do a lot of work on like, you know, things I can do now I couldn't even think, think about in 2024. And I know that things we can do in a few more years can even not even think about what, you know, today. But still there are so many unknowns and how societies work. Right. So maybe AI will change society completely. But often we overestimate the impact of technology. Like we sometimes underestimate as well, sometimes we overestimate what technologies can do because we get blown away by the initial and we think, hey, we're going to have flying cars. Remember in the 60s people thought we could have had flying cars by now.

A (19:31)

Yeah. And look, this technology is different because. And there's several becauses there. Right. But to your point, I mean, the vast overwhelming majority of people, people by population anyway, aren't really paying attention because we believe that our future is going to be some small deviation of the past. You know, if you talk to, if you, if you read anything that Ray Dalio talks about. It's like people. You, if you have to look far enough back a hundred years to understand the cycles, and once you understand the cycles, then you're going to understand are they going to come faster, are they going to come slower? But there's always a cycle, right? So this is a technology that is different because it has the ability to evolve on itself. So think about this. You've got, you know, the ability. Today, robots in automotive factories are basically single modality tools. They're screwed to the floor. They're an army. They pick up a piece, they put it in. The next robot comes in with the screw gun, screws it down and the car just moves along. And there's a thousand of these single modality robots that are not mobile and they're not really learning anything. They're executing on a set of code to do what they're doing. Sure. Do they have sensors that tell them if something's off and you know how to get the screw right in the hole and sure they do, but that's certainly not intelligence. Now you take AI and you put it into a mobile multimodal humanoid robot. And now not only does it have the network that it's connected to that it's getting smarter, it has some proxy of visual. So it's not, it's, it's not only getting, getting smarter from the network, it's also getting smarter from its environment because it's seeing and it's observing and it's taking that into account. And something that it learns is getting learned by the other robot. And then at some point when things are learning so fast, while it may be programming, it looks different to us because we don't have the ability to understand it as quickly. So that's, I think that, you know, so the change is, it's, yes, it's, it's a, it's another technology. Look, you know, we went from whales to whale oil to steel to tech to, you know, you know, all of the things. Right. Or you wrote. There was a great book I read years ago, I think it was called the Big Switch. And it went from the, the evolution of the, of the fact, you know, to get power you would have to put a factory on a stream. And then when the industrial revolution came, you had to build a power plant in each factory. But when they built a, when they built the network of electricity, the infrastructure, then you could have a centralized power plant and then you could power everybody. And then that led to a big thing. Right? And it was the same thing with the Internet, when the Internet happened. So you have this cycle pattern of basically networks, these are different types of networks that are technology based that basically create a new normal and then everybody has to adopt and all the jobs need to change and then it runs like that for 30 or 40, 50 years and then the next thing comes. The difference in this is just the freaking rate of change. And it's at a rate of change that we are going to struggle to adopt. Because you could create a new iPhone model every day now, but what good would that be? Because you can't manufacture it fast enough and we can't adopt it and we don't need more tools on our iPhone. It does plenty.

B (23:30)

You can build new apps. I think I'm not disagreeing with any of this. I think AI is.

A (23:37)

Well, you probably, if you knew my iq, you would.

B (23:40)

So no, I'm not disagreeing with the fact that AI is, you know, is a huge disruptor more than anything else we've seen in the past. In the same way that I think, you know, the Internet was a huge disruptor before anything else before. If you think about now, like without the Internet, the AI would not, you know, would, would not have been possible. Right. It's, it's, it's, it's built on it. Like we stand on the shoulders of giants, as they say, and technology works the same way. And I think AI is, there's a lot more to come with AI. But what I was referring to mainly is when people think of AI today, they're thinking of large language models. There's a lot more AI that's happening beyond large language models. And I think what we will see in the next few years, this is just my, my instinct is that we will start seeing the limitations of a large language model based AI. But there is other AIs being delivered and I think we'll see the next generation of AI and you know, and AI will, you know. Right now the bottleneck really is on the computation side. They're building these large data centers and it's processing because AI, if you give it enough time, with enough data, enough parameters, it can basically answer any question on anything based on any prospect. But there's the limitations on processing capabilities. So that is going to change and I think we are going to get, obviously I like Ray Dalio as well, the rate of change is going to get faster and we don't know what's going to happen in the next few years, but we have to be ready for it.