A (3:08)

Yeah, I know you're in manufacturer. I was thinking it's if you. Sometimes you see the person. Like, I watch a lot of forged and fire, and there's the person who has a ton of money and they buy every different thing for their forged, and they know a little bit about everything. And you can't. You don't master, so they can't really make anything. And it's the same thing where you have this temptation to go, I want every type of machine. And I make knives and swords and maces, and they're all different. And that's really the area I'm into, which is like, because AI has become so cheap and affordable now I can add in eight other tools and we forget. I think the thing people are really forgetting is to ask that critical question of, do we? What problem does this solve? What's the benefit? And then what's the learning curve? So with every new tool, there's a dip. Even if it's going to make you more efficient in the long run, there's a dip as people have to relearn a behavior, whether it's walking to a different station. We've all done that where we accidentally drive to our old job and we go, what am I doing? It's like a learned behavior. Or we. And then you have to retrain yourself not to do that thing. And it's this dip in efficiency that people are surprised by suddenly. And it's learning anything new. You're bad at first. Even though AI increases your efficiency or a new tool increases your efficiency, we have to learn the protocols and how it works. And there's always something that's a little different, whether the buttons are in a different place or it uses a different tool and as part of its process. And I think that's really where we're starting to see people pile up. Because you go, I can do a bunch of new things and why aren't I more efficient? You start to get, I think of sometimes that I Love Lucy Skitch, where the thing's going so fast and the chocolate's getting everywhere and the conveyor belt just goes faster and faster. And that's what it can start to feel like because you skip the strategy phase, which is very common now with businesses, especially digital type business, because you don't have to do a business plan. So if you want to start like a manufacturing business or get a bank loan, you have to show up with a business plan. Here's what we're going to do. Here's our strategy. If you're starting your own business, you can bypass that, which means you can start faster. But it's actually useful because you need those metrics. And to say, why am I doing this? And I often find when I ask people, they go, I want to do this. And I go, why? And they go, I don't know. Seems like it's like the most common answer I get is it seems cool or I like the person, depending on if I'm talking to a startup, I go, why? What problem does your software solve? Go, oh, we don't know yet. I'm like, okay, that's worrying. Or they buy a software because they like the salesperson. It seems cool. And I'm like, when you buy emotionally or when you add a strategy, emotionally, like the number of people who start a podcast. And I go, why? What's the end goal for it? It's so important because it changes your entire strategy and changes the type of guests you have. It changes the type of questions you ask because they just go, I just want one. Okay. It's like a Labubu. That's worrying. That's a worrying business. How can we with this temptation, right? It's like you have so many options and suddenly you become frozen. Too many options is actually a bad thing. So how can we pull back and become a little bit more lean in our decision making?

B (6:31)

Yeah, that's great. The too many options. I just had a conversation with a colleague about. This is like you go to the grocery store, like, how many options do I need? Need for toothpaste. It's like mint and 70 varieties of mint. Yeah. You can be paralyzed and AI, as it's continued to evolve, can do a lot of things. And then suddenly you're as the business owner and you're growing and you're Like I need to do all of these things. It's a great question. Why do you need to do each of those things? Every engagement that we start with. So if we're outside of AI and then bridging that analogy back into it is we start with the why. Like, why does this business exist? What are you trying to accomplish? And then what are the goals that you're falling short on? So if there's a specific goal in your business, I know your audience likes small, medium business that you're trying to accomplish, and you need capacity or throughput that automation and artificial intelligence can provide.

A (7:21)

Great.

B (7:22)

What are you trying to accomplish? Can you measure that so that once you deploy one of these tools, is it actually helping you? Is it actually saving you time? Or are you spending more time on the back end to filter through illegitimate leads to, to counteract, like comments on posts or posts? That wasn't exactly what you implied by that. So it's really important, I think, to start off with what am I trying to accomplish with deploying this particular tool? If we think about, I like to think about any type of AI solution you're putting in is like a team member. Granted, it's free or very little cost, but I'm going to bring a team member on that's going to do something for my business. What is the role of that team member? What are they supposed to deliver? And how will I meas measure whether or not it's being successful? So I love like these new tools and products. A manufacturer wouldn't just up and say, no market research, no direction. We're just going to start making something and hope someone buys it. And it can be a lot of the same thing that you're talking about. It's like we're. I think I'm supposed to put content on LinkedIn, so I'm going to have a bot to do it. Okay, what are you trying to accomplish by posting on LinkedIn? Awareness, reputation, thought, leadership, leads. Like, it's very different the direction that you're trying to head. And without that feedback loop on the back end of saying, is it accomplishing what I want it to accomplish? It's the same thing as saying, deploying a new physical product without ever thinking about, I don't even need to know whether or not there's a market for this potential sale. The other two things that you mentioned that are very important to think about. So one is just the metabolism that your organization has for change. So we're going to change the way we do things and automate it. Et cetera. Can we handle that much stuff going on? Because now that, yeah, I have all these AI automation workflows launched, who is keeping track of what's happening there? There's still some work on the back end to make sure it's working and it's working correctly and it's giving you quality outputs from that. So I think one of the most important thing is on the front end is thinking about that, that why that strategic element. And so that is a very lean mindset saying, what am I trying to accomplish? What is the output of this potential process? And then it's this feedback loop. We refer to that as the Deming cycle. So it's an acronym pdca, Plan, Do Check, act. So if I'm going to launch some sort of AI solution plan, what am I, what is. What do I not have the capacity for today or don't have the ability to hire, or what am I trying to accomplish? Then being very thoughtful about the implementation of the tool. It's not like the old infomercials with the ovens. Set it and forget it. It's be thoughtful about constructing that virtual team member. And then don't forget to check. Are you actually getting the results that you want? I know, I've listened to some of your other episodes and there's even large corporations that are getting in trouble by just launching stuff that's not filtered, checked for accuracy, checked for plagiarism, et cetera. But like, not only checking the content before it goes out, but then also checking the results. So that's Great. You're posting 17 times a day on Instagram or whatever. Is it moving the needle in the strategic direction that you wanted? Or maybe you need to spend some time and be a little bit more thoughtful about where you're spending the resources. And that's when the last step comes. Act. So take some action, adjust or whatever, change the plan and iterate. But in a lot of areas of business, not just AI deployments, we see our clients like really struggle with that check and adjust portion of. Because I can't check unless I had a goal that I wanted to accomplish. Accomplish in the first place.

A (10:57)

Yeah, I fear that there's this idea that more is the answer to everything. And more comments, more posts, more videos, more social media stuff. And I see this sometimes when I talk to someone, they go, what do you want? More leads? And I go, okay, let me say, let's say I get you a thousand leads and no one buys anything. Are you happy? And we have this sometimes we gamify ourselves. Like we don't say what our real goal is. And this biggest problem on social media is that we'll chase the wrong metric, which is like followers or engagement. And it's one of the things I've discovered is I had a post go very viral last year and it was the lowest ROI of any post I've ever done. So it had 400,000 views on LinkedIn, which in LinkedIn is insane. And I got 12 followers from it. And I was like, this is horrible. Basically it's a rounding error. And I realized that for something to go viral, it has to appeal to the masses, which means it doesn't appeal to your ideal customer. The more the broader it is, the less likely your actual customer will like it, which means it's actually negative impact on your business. And that's one of the problems with chasing the wrong metric. And I always say like when people say what's the most important metric to you? I'm like, dollars for sure money. I can't pay you in engage unless I can pay you in likes you want. That's the same metric you want and it's. That's important. One of the dangers or things I see with AI is that people start talk so much about efficiency. The problem is it's immeasurable. It's usually self reported. I feel more efficient or I feel less efficient or I got more done. It's not very easy to objectively measure unless you do something like data entry that's very measurable. Most people's tasks throughout the day are not that measurable. So it's like you couldn't tell like a 3% increase in efficiency. You would not be able to measure that very well because they just went to the bathroom one time less today and that threw off all the numbers. It sat crazy. And that's one of the problems is I see sometimes AI consultants like if you make everyone this much more efficient, you save this much money. I'm like, yeah, if you don't pay them for the two hours of efficiency, like you still have to pay their salary. The number doesn't change unless you fire someone or don't pay them for the two hours less a week they're working. And that's the problem there is that we, I think what happens is we get a new tool and we think it's going to make our lives better. And it doesn't at first it's hard. Learning a new process is hard. And there's that dip and you start to. Because everyone like is hyping. AI especially you start to think it's me. I'm actually slower because I'm trying to learn this and I'm not learning as fast as everyone else. And you start to enter this negative thought loop which is that this is. This works for everyone else, but it doesn't work for me. So there's something wrong with me and it makes it worse. And you can get in this like really negative cycle even as large as your business, right, where everyone is starting to feel like this working for everyone else. Why are we the. Why are we the one company that can't get AI working quickly or get that efficiency or everyone else? And this is this temptation. We have to compare our backstage to everyone else's front of stage. Like I have no idea what's happening to either side of your camera, but so I only see what's on stage, front of stage, the presentation period. Same for me. I set up the lights. We assume that someone would tell us if they're having a bad day. Like no one's gonna. No one on LinkedIn ever posts the truth. Me and my wife had a fight this morning. It was my fault. You never see that on LinkedIn. Nobody would actually post. Even though it's true. And probably most of us have had. Have said something like that dumb in the last month to our wives. So it's not that crazy. But we don't do it. And that's because it's. There's a performative element in the same way that reality television's not real. No one does those things. People, when there's a camera there, they act different or this person's. Make it louder, right? There's like a producer behind the camera. So there's. We. For some reason we think that Instagram is real or. And even if you like there's these at guy actors who like are ABS actors, right. They have to show their abs. Some of them have to plan the shirtless day six months in advance. So they diet Target. That's a nightmare. And then the day of the thing they only eat ice for three days. There's a. And we. But we don't see that, right? We just say oh, his abs like that all the time. And he's six months of hell. Three minute scene. And that's the backstage, right? That's the off camera part that we don't notice. We just see that one moment which is great because he worked towards it, I think. Great for him. Congratulations. The scene work. But it's like a huge amount of effort that we discount so then we try and do it for ourselves. We go, why is it working for me in one day? And I've never. I don't know about you. I've never eaten ice for three. Like, I've never done that. That's so tough that you're so hungry you're eating ice. It's so wild. And in the same way, we see other people using these tools, and I'm sure it's the same in manufacturing. Someone else gets. And I've had amazing guests who were like, have AI welding machines. And there's some really cool things there where a machine will start to tell you how it's breaking down. So some cool things AI can do is say, oh, here's what's. But it's still. It doesn't mean it's going to be easy. I can't tell you. I got into a raging fight with an AI today. Like I said, some really dark stuff, and it was completely wrong. And it would go, no, here's the new code. It would give me the exact same four lines of code. I go, you're insane. And it got really mad. I go, because if you keep giving me the same answer, you keep going, oh, here's a different answer. And then give me the same code. That's a definition of insanity. And like, it got mad. I really high. And it's like, the idea that things never go wrong, that's a misnomer. And that's why I try to tell those stories. No, I get into a rage with AI all the time when it makes a mistake and then it won't admit it. That's important to know. So what happens to you? But I think that a lot of it can happen where you add on a new project. You start to overwhelm yourself. It doesn't increase efficiency because you forget that time to learn it. Then you start thinking, oh, it works for what else? It's not working for me. So there's a problem with me. And so, like, now it's piling on. Now you have a physical and an emotional problem. So I want to pull back again to the core concept you talked about. And it's a core concept of your book, which is like, to less is more. And I think it's so important. Like, one of the ways I know a business is going to fail is if I say, who's your customer? And they go, everyone. I'm like, oh, that's the worst customer base you can have. Because everyone is different. And it's like, the more dialed in, it is the more likely you are to succeed because you know who you're talking to. How can people before AI, I always say, before you grab an AI, write down a plan, like know what you want from any tool or anything. How can someone pull back and go, okay, what is an efficient use of my time? Or what is the right thing to do? Because doing something just because you can often doesn't help your business.

B (17:45)

Yeah, you covered a lot there. I made some notes, a couple of points to hit back to. So, such good stuff. So you start off talking about how people feel like, oh, I'm falling behind, I need to do this AI thing right? So there is a barrier, but at the same time, it's cheap and easy to use AI, right? So we can just feel like, just deploy, but without thinking about that specifically. If we're talking about brand recognition, thought leadership, et cetera, of who's my audience I'm even talking to. So the concept of niching down and saying, are you speaking to one specific person's problem or are you just saying people have problems? And people are like, yeah, they do post, right. Like you were talking about 400,000 likes and 12 followers. So speaking to the specific problem that you're able to solve. But that takes some introspection, right? So the hard work is not just deploying the AI tool. It's sitting back and saying, what problem, what service, what product are we providing and who is our target market and what's our process for delivering it? So I work in the consulting space. I think there's this fear or it's been talked about in some spaces, like that AI is going to replace consulting or coaches, nutritionists, whatever you want to say. In some cases, yeah, some of that knowledge can be synthesized. But what's really going to eliminate your business is not AI in itself. It's bad scoping and weak process. And so if you don't focus on your scoping and your focus and your process upfront, and then say AI is a tool to accelerate that, maybe I can tell a story to illustrate that. When I was working with a public utility, so like natural gas and electric distribution, there was a push for data and digitalization. And one of the things they were talking about is they would get from the field. So they're going to come out, they're going to install a gas line or a distribution line for electric. And when you get in the field, like there may be a tree in the way, there may be a mail, there may be something there that wasn't on the map. Right. So you have to adjust it so you make an infield change called a red line. And they would get back field notes and red line changes and they're saying, oh, it's taking forever because it's paper based and it has to go back and we have to enter them. We're going to get everyone in the field tough books and they can put it in.

A (19:53)

Great.

B (19:53)

We gave everyone in the field tough books with very little training. And you know what we got? We got really crappy data a lot faster. It's still wrong. We automated it, but like, now we have a whole new problem to solve, right? So we didn't take time to invest in understanding the problem and the process that we were going after before. We put this, this efficiency acceleration on top of that. Because there's a quote from Peter Drucker, right? There's nothing more wasteful than doing efficiently, which should not be done at all.

A (20:21)

So great.

B (20:22)

You're blasting out social media content and people see that you're posting, but it's noise, right? It's not tugging at the heartstring of your specific client or customer's problem. It's just noise. You have a presence, but you don't have a following. And I think that's one of the big problems that we have is that this focus on more and more and more, whether it's in your business or we're talking specifically AI, but like, more of what, to your point? More of I want more leads, but if they're not qualified, they're not buying anything. Great. I want more likes, more views, more impressions, but it doesn't actually translate into whatever product or service you're selling. So I would pull everything back and say, you need to start up front with just saying, okay, so what is the strategy of my business? Who do I serve? What do they value? And then architect your processes for delivering that, and then maybe automation and AI can help you become more efficient. There was one other thing you talked in there about. No one posts on LinkedIn and Facebook, like a fight they had there with their wife or the other thing. Another thing, especially in my space, like coaches, advisors, consultants need to be careful of not creating this like, instau version of yourself, right? This Instagram version where, like, you are this lone stoic sage and you have all the answers and then they meet you and they're unimpressed. Wouldn't that be terrible? So you've synthesized all this knowledge together, you've pulled it together, but then like, you can't actually cash the check that you're writing like that's. That's something you have to look out for as well. So at least in the deployment of. We use AI in any content generation within our company, it's trained on all of our own ip, it's trained on my book, it's trained upon our blog post, it's trained upon our case studies. So I'm not going to go out there and promise people results that we actually haven't delivered. I'm not going to refer to solutions, methods, principles and tools that we don't actually use, because that's going to just create again, it's efficiency, efficiently generating a lot of stuff, but it may not actually turn into any sort of value.

A (22:28)

Yeah, I think you're so right. The danger is that it's so easy and that's the temptation. If it's. If it was really hard to generate trash content, people wouldn't do it. But you can push a button and make an AI image that looks terrible, but it's okay, and then write a post that's generic but not crazy, and then it's easier and easier. And I think that's something that we forget about is that, like, most bad stuff is easy, good stuff is hard in most cases. Right. And that's what happens is that you start to look at something like, social media is hard. It just is. It's hard to think of something to write. It's hard to write a post that goes viral. And you could put a lot of work. And I put a. It's happened to me with books. The book that I spent the most time writing people like the least, and a book that I wrote in one day people really love. So there's no correlation between your effort and people's response. And we can all see this because you can talk about. There's certain movies that, like, bombed and they go, but they spent four years making it. Yeah, I still don't like it. We don't respect their effort, that it was harder. And there are certain movies like Sorcerers, this movie from the 70s, which is a remake of a French movie. And it was like they shot it on location in South America and like, they all got cholera to make it real. Like, it was like, it's Notorious as being the hardest movie ever filmed because he did everything practical, including the diseases. Like, I think half the film crew had to go back to America because they were dying, like, hard. And it took four years. No one cares, like, other than other filmmakers and people like me, because it's very interesting to me and that's the thing we forget. And so then when we're making content, we go, if no one cares if I put in effort or not, I start to get lazier. And it's tempting. The thing that's dangerous is that if you are saying things, you don't know what you're saying, and if your AI's answering your emails, AI's writing your post and AI's answering the comments, you're gonna miss, like the warning signs if something's good or bad. People will tell you on social media if they like or don't like things early and you miss that and then you're not seeing it in your emails, you can push back how long until you get warned you're about to do a bad idea or that you should do something that's something that people want. So there's the reason it's valuable. And it's like, I've started to notice that more and more. It's this dead Internet theory, which is AIs are posting and AIs are commenting. And it's like, my engagement's up. It's like, yeah, but not with humans. You're doing great. For the bots, it's a distracting metric. And that's. It all pulls back to this. What is my goal? Who is my customer? What problem do I solve? And will this tool, or will this machine, or will this system or will this employee get me there faster? It's such a critical question. And most businesses really, especially smaller business or businesses get excited by tools. This can be really devastating. It's like, I bought this, now I have to justify it. So this is where you start doubling down on a bad idea. And it's, I bought this tool, I signed a one year license, we have to use it even if it makes things worse, because I have to justify the purchase and you can start entering this dangerous cycle. There's this pressure to decide very quickly with AI because you'll get left behind. And I've certainly said things like this before, but it's like any technology cycle, it's, you don't have a car phone, you don't have a pager, you don't have a fax machine. All these older technologies, half our listeners probably don't know what they are anymore. And it's like there was the same pressure, like, how can you be a business if you don't have this? There are huge businesses that do nine, 10 figures. They don't have a website. Not every business has a website. And there was this need maybe 25 years ago, 2000 to 2000. Every business, like, you have to have a website. And they say, why? How will the website help your business in particular? And you start to get this, like, keeping up with the Joneses. Like, everyone else has a website, so I need one. So now it's like, everyone else has AI, So I need it. That's. I think, this thing that pulls us in. It's. There's this old story of the farmer who. The consultant comes and is, I could do all of this stuff, and then it will take you 10 years to pay it off. And if anything goes wrong, you lose your farm. And so everything's already working. I don't think I need that. But it's a temptation to have the cool new thing, the cool new machine that could work out and could be high risk. And it's like the thing I always watch out for with my clients. I always say, I don't want to have to do a dramatic change to human behavior, because if I have to dramatically change how you guys behave in order for the system to work, I have to teach you to do tool. I have to teach you to do behavior. Then that increases the odds of failure because it's. Try changing a habit, right? Try changing someone else. Habit is really hard. And I've seen some of these tools, like even these AI note takers, there are some that you have to push a button at the start of the meeting. And like, never use those because you'll forget. You'll forget to push the button the one time you need those notes, right? It's such a small thing if you can't remember. And we all can't. I know because I've forgotten to hit the button. So I'm not judging anyone else. That's all it takes to have a problem. So if you can't remember that all these other behavioral changes where it's like, switch the tool you use, switch the questions you ask, switch your process, these are dramatic changes that can take an employee, like, six months to really ingrain a new way of doing things. And like, I grew up in Tennessee, so a lot of my friends are in manufacturing. My friend used to put in the back seats to Saturns. And if you change the order in which you assembled the car, it would be such a big deal if you said, oh, we do it now. The back seat's third instead of fifth. Huge issue, right? You have to move things around. Very dramatic. And we think it's a small change, but it's actually a really big change because he had he could do his job with his eyes closed because he'd memorize the behaviors, because he would bolt in the backseat the same way every time he put in, like, thousands and thousands of vaccines. So that's a lot of unprogramming to do when you want to change a behavior. Like, that's the critical part. So be very sure that there's a real benefit here and that you're willing to pay the price. Because with AI, it's not a price in money very much. It's usually a price in effort and time and efficiency things. Things like where you have to go through that dip before you get the result. And. And it still happens for me, every time I'm learning a new tool, there's a process. Like, I didn't use any AI tool besides ChatGPT for 2 years. I was like, I'm still getting good at this. When I. Trying to learn another tool, it's like trying to learn. Try to unicycle and trying to learn to juggle at the same time. They're both really hard. I can't do either. I can't do either of those things, but I would probably rather learn one and then the other as opposed to learning them at the same time.

B (29:03)

Yeah, you're full of great analogies today. I love the juggling and unicycle. Learn them separately. The interesting thing about, like, the AI note taking and things like that, and parallel to that is what I. What we run into with clients is like data generation, right? So we have data and then we have a data lake, and then we have these. All these servers of data. And so we generate AI notes and data and everything. Like, on the back end, you're like, who's doing anything with all this information that we're generating? Right. Oh, we'll just have AI analyzed. It's okay. But we're back on that topic of, like, more for the sake of more. It's more because we can. We're going to AI transcribe every meeting. It's like, all right, is anyone ever going to look at that? What are. Why are we doing that? Rather than because the tool exists, I think is really important. The changing behavior one is like, stuck in the back of my head. Because honestly, our company, that's what we work on a lot. It's like changing behavior, right? Changing our behavior as it relates to manufacturing. So the Saturn analogy is a good one. If you need to change a process like recognizing for that individual that's putting in the backseat. If we're going to change the bolt pattern. If we're going to change the sequence, like, that's going to be a big change. So they need to understand why we're changing it and have a little bit of input onto does this work for me, the operator versus at a top level in your business, depending on how big the business is just saying we're going to do this. And now I'm wrestling through that change curve myself. Then you get back to the more for the sake of more. You know, I oftentimes look at companies and ask them things like, what are we looking at in terms of strategy? I was recently working with a company, only about 160 members total. And like, how many strategic initiatives do you have going on? And they're like 12. And I'm like, all right, so as a leader, can you manage something substantial, changing your business every month? No. Okay, then maybe we should be focusing on changing fewer things right now. If you don't have on the back end to review, reflect, kind of that check and adjust we talked about earlier. Like, why are we changing all this stuff if we don't have the leadership capacity to manage the change as well? Again, I think we default to the fact that like, AI is cheap, AI is easy, and we can get back into this cycle of more for the sake of more generating junk that's just going to generate junk leads, junk impressions, junk clients, things of that nature. And so really thinking about the behavioral change of the organization I think is important as well. Like, it's easy to deploy. Again, we're talking about relative. It's relative. Relatively easy to deploy an AI solution. The hard part as a leader is making sure like the team's on board and we're getting the results that we expected out of it. Now, if we hold ourselves accountable to thinking a little bit more about that, maybe the AI solution for every facet of business doesn't make sense because we don't really understand why we'd be using it. And we don't have the capacity, the change metabolism to follow up with that and reinforce it. Like, it's a great point you make there. The other thing I had written down that I wanted to talk about is we talk about putting out junk content. You said, like, it's easy to put out junk content. And if junk content leads to junk clients, I don't. Whatever that means. Right. Not the clients that you're hoping to focus on. Then I really question, what are we. What are you trying to create in your business? So again, this is the hard, the kind of thinking part the introspection that you can't outsource to AI is like, why do you have a business in the first place and what are you trying to create? Great examples of saying there are businesses that are thriving and doing six, seven figures of revenue because they're passionate about what they're doing and they've niched down and they're exclusively on referral business, but that's what they want. So if you're like, growth more, because I think I'm supposed to grow because everyone else seems to be growing on LinkedIn, like, we can get caught in that trap of like, why not pause and hold back and say, what are you actually trying, like your business, what are you actually trying to create? Because if you just try to scale and scale and be everything to everyone, you eventually turn into a commodity. And if that's what you want, that's a different story. But I know that's not what I want for my business.

A (33:22)

I think that we get so caught up in the excitement of any movement or anything that we skip over a lot of the steps and we're seeing a lot of emotional decisions. I love that you brought up like that. It's very easy for you to change your process at the top if you're not the one who's doing it. But yeah, like I was just thinking about how we. When you're doing a physical task, like over and over again, you get very fast at it. If you have to change the pattern, you're going to slow down quite a bit, right? So maybe now instead of 50 backseats a day, you're doing 35. And eventually in six months you'll be back up to 50. But there is that slow down time. It's just sometimes people come out with a new pattern for a keyboard. Like they move all the letters around. Think about how long it would take you to relearn. And there's the promise of efficiency because there are versions where they put the most common letters near each other. And then they did all these studies. It doesn't make a difference. It doesn't make you any faster. And it's this huge learning curve that people put a lot of effort to find out. Like when they invented Esperanto, right? All this, like the universal language anyone could learn. No one learns it, but it's this idea that it would solve a problem. And yeah, we. What I see is that sometimes you decide to initiate a change and you forget if you don't have a measurable, like a measurement of success. This is a very common mistake. I see with people when they have their first hire, the very first person you hire to grow your company, you haven't written down your processes. You don't have any SOPs, you don't have any measurements of success. So they don't know what to do, and they don't know if they're doing bad. And that's if you don't know. And then of course, you go, they haven't hit the goal that I wanted, but did you tell them that was the goal? And so they're fired and they're surprised, as they should be. Very common with a first hire is that you don't have a metric of success and a metric of failure. And I see that happening where you implemented a new tool and you go, how do we know? How does the person using it know they've hit your goal of the increase of efficiency, the increase of results? It's very important to have a concrete number, because as a worker, whenever I'm working on a project for a client, I need to know what success looks like for them. Otherwise, it's so hard to hit. Like, sometimes someone will be like, I'll know it when I see it. I'm like, lynne, it's gonna be a very long project. That's gonna be years. Because that means I have to keep guessing. And I'm not good at guessing what you're thinking. No one is right. It's this very challenging place to be in. So I think that it's such a good lesson today to really sit back and, like, before you use the AI, before you use the tool, before you buy a new machine, before you hire someone to sit down and go, is this going to bring us closer to our company's goal? And I think that we, as I said at the beginning, because we don't write business plans as much anymore. We don't have our goal written down. Right. We don't have it really measurable. And I always see the people who, like, write down, I want to make this much money per month, like on a giant wall next in their room. I've seen a few people do that. They always hit really works. It's very big and whatever, but it works because they know how much money they need to make every month. They knew what metric they need. And they go, I want to make this much money. So I need this many clients. I need to do this many calls. And they start to trickle down to, okay, then I have to send out this many emails. So it's this. We start to, like we said, more and more grab these tools. But it's like, why? And the why is such an important question that we're just missing. And I think that I've, and I've seen it at very big companies where they do this massive investment and then it's why. Like I, and I've even seen small companies spend a money amount of money in AI that like my eyes water. And I go, why did you spend that much? And they're like, to do this, I'm like, oh my gosh, you spent like hundreds of thousands of dollars more than you needed to. It's that much money. And it's like mind boggling. And that's the thing is that we are not making a logical decision. We have to pull back and be logical for a second before we deploy something.

B (37:27)

It's, I think it's possible that AI is not necessarily changing that for companies. What it is, it's amplifying it because it's so fast and easy versus we could have done the same thing in the past, but you would have had to hire a bunch of people, make a department, et cetera, et cetera. And so if I could skip all of that and just deploy a tool for 1/10 of the cost, 1/100 of the cost, maybe I'm not doing a lot of that front end work. We think we started the beginning saying, how do we put some more lean thinking around AI deployment if you go all the way back through? So lean is based upon most of the principles based upon the Toyota production system. So Toyota is an auto manufacturer. But besides the production system, which is like how we do strategy deployment and continuous improvement, the Toyota way was continuous improvement and a little Venn diagram those also respect for people. So now we're, I'm wrestling with this in my mind hearing your last thought about oh man. Because AI can take the human out of the loop. Have we taken the human out of the loop here in the AI in terms of the change curve of what do I want my team to accomplish, what do I want to accomplish? And we're just deploying this bot and assume it's going to do whatever we hope to versus that other side of the continuous improvement means we need to have a strategy to deploy, we need to have a process documented to understand how to improve it. And we need some sort of daily management system. You mentioned like metrics on the wall, like what are we trying to hit? Or else we're like blindly throwing these AI darts everywhere and not being very respectful to our people. We're keeping Them busy generating the AI that's generating a bunch of stuff. And this more is now just amplified, I think more than a new problem. Does that make sense?

A (39:14)

Yeah, absolutely. I think that it's exactly what you're saying, which is that it just makes it faster, louder, bigger. So like cracks that were small now get really big are amplified and AI is just an accelerant. If you have a bad process, you just got to do it faster. They have a good processing it faster. And that's it's all come comes back to that, which is you don't want to accelerate something until you're sure it's a good idea. I think the first person who like tied a rocket to the top of their car and drove in the desert and then they just found them on the side of a mountain like a hundred miles away because rockets are very fast. It's like faster seems like a good idea. But you. There's a reason like there's a top land speed record because and same for boats. Above a certain speed, the machine just dissolves if there's a reason. And that's. There's an idea that faster is always better. So I really love this. I think that like just pulling it.

B (40:15)

Back and it's what I want to.

A (40:16)

Dial into is like this core concept of lean which is like, what are the things we need to do to get the result we want? And it's. If you don't know the result you want, then the formula doesn't work out the gate. And I see this so many times in so many different sectors with so many types of entrepreneurs and small businesses. I, when I was in doing a lot of authorship teaching, sometimes he would say, what I want to write is I want to write a children's book, then a book of erotic poetry, then a cookbook, and then like a mystery. And like anyone who goes to your author page is going to freak out if you what you're starting for businesses each time you enter a new market as an author. If you're writing children's books and then you start trying another genre, it doesn't cross over. Even sees authors who go from science fiction to fantasy. It's not the same people. You lose like 80% of your audience. If the same customer won't buy all four of your products, then you have four different businesses and it's that simple. Where you're driven by curiosity or passion. And it can be too disparate, where you start to go in too many directions because you can. So I think it's been really great and helpful for a lot of people, people who are very interested in the type of companies you help and the type of projects you work on. And maybe they just want to read your book, which is very excellent. Where can they find the kind of things you're doing online? Chad, the best place to find your business, maybe the best place to reach out to you.

B (41:35)

Yeah, the best place to reach out to me directly because we still do. Despite this being an AI podcast, we still do in person connections would be at our website, which is bereithergroup.com social media platforms. We're most active on LinkedIn, but you can find us on LinkedIn or Instagram and that'll get us back to the same point. But if you want to get in touch with me directly, third group.com there is on there. You mentioned the book. There's a free Download of Chapter 1 if you want to learn a little bit more about that and a contact page. You want to set up a direct call with me. So that would be the best place to go.

A (42:08)

Perfect. We'll put it in the show notes as always and below all the videos. Thank you so much for being here today for another amazing episode of the Artificial Intelligence Podcast.

B (42:17)

Thank you.

A (42:21)

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