The 4 Laws for Success in the AI Era with Isar Meitis

0:00Season three of the Built Right Podcast is right around the corner, but we've got one big change coming your way. The Built Right Podcast is now the Talking AI Podcast, and we've got a lot to talk about in AI. In the Talking AI Podcast, we'll be having in-depth conversations with both AI experts and early adopters of AI. That way you can understand how the technology works and how early adopters are beginning to implement and, more importantly, get value from AI. Our guests range from AI research scientists to founders of AI products to industry leaders putting AI to work in their business. While you're waiting for season three, go ahead and subscribe on your favorite podcast platform so you don't miss an episode.

0:41And make sure to leave us a comment about the AI topics that you want to hear about. So get ready to talk some AI in the new Talking AI Podcast, coming your way August 6th.

0:53Welcome to Built Right, a podcast by Hatchworks where we help you learn how to build the right digital product the right way. In this season, we're going all in on generative AI with guests ranging from international AI speakers, founders of Gen.AI products, experts in specific domains of Gen.AI, and leaders across industries. We're here to help you figure out how to take advantage of this new emerging technology so you can win in the market. So whether you're an AI techie or just AI curious, we got you covered. Let's get into it. Welcome, Built Right listeners. Get ready because our guest Isar Matas is bringing the heat today with four laws for success in the AI era.

1:32And we're going to go through these in detail today. And by the way, you're going to want to stick around because the last one is my favorite. So don't miss that. Isar is an AI implementation expert, four-time CEO, keynote speaker, serial entrepreneur, and even a former F-16 pilot to boot. And he's also the host of Leveraging AI podcast. Make sure you check out episode 56, where I joined Isar on the podcast, going deep into custom GPTs. But welcome to the show, Isar. Thank you so much. You know, after this kind of intro, I can only disappoint your listeners. I should have started with a lower bar, shouldn't I?

2:10I appreciate you. Yeah, no, this is great. I'm really excited about this one today because we're going to get into the tactical pieces, really kind of the approach with AI. But before we jump into it, I got to ask you, man, what was it like? What was your experience as an F-16 pilot and anything you learned from that experience that's kind of translated to business? Wow. It's an awesome question. So first of all, I had a blast, right? It's one of those things that in real time, as you're doing them, you're like, I'm so lucky. It was really, really amazing. But yes, a lot of things translate from being a fighter pilot to the business world and to entrepreneurship.

2:49And I've actually done a few episodes, mostly guests of different podcasts through the last, I don't know how many years talking about this, but the main things is, you know, preparation is one on how to prepare for things. This could be anything, right? It could be preparing for a mission, but it could be preparing for a talk or preparing for a project and so on. So preparation is a big one. teamwork of working with other people, both again, on the preparation and execution, sticking to the mission, even when things are tough and not giving up and just finding ways to resolve and achieve the outcome that you wanted to achieve, regardless of obstacles that you see along the way.

3:31Being able to, on one hand, be very detailed with your planning and execution according to the planning, but at the same time, know how to pivot very quickly when things change and know how to respond. So there's really a lot of things that translate from being a fighter pilot or probably anything military, like active fighting military to like the business world. Yeah. I think that explains a lot of your success you've had later on. Are you still a pilot today? Do you still fly? No, no. I have a private license, which I very barely use, meaning it's not current. So I get to fly with friends who have jets and stuff like that, but not on my own.

4:15Nice. That's awesome. All right. So let's not beat around the bush anymore. Let's get directly into the good stuff. So we have these four laws for success in the AI era. And what ISAR is actually going to do is bring up a visual for us to walk through it. And don't worry, those listening on the podcast, we will be very descriptive in what we're talking about. But I'm going to hand it over to you, and we're going to kind of go back and forth and give the audience a little bit of insight into these four laws for success in the AI era. Awesome. Let's do it. So I came up with these. I do several different things right now in addition to the Leveraging AI podcast, and a lot of it is consulting to different businesses.

4:55So I get to see the pre-implementation, during implementation and post-implementation of AI in various different companies, in different industries, in different sizes of companies and so on. And these evolved through that process of looking at the AI thinking more than anything else. Like how do you think about AI in order to really gain the most benefits out of it? Quick break in the pod. If you're listening to this podcast, chances are you've been thinking about how to actually use AI inside your business. And that's exactly why we built the AI Opportunity Finder. It's a free tool that helps you uncover high impact, tailored AI use cases based on your business, your goals, your pain points, and your industry.

5:41No fluff, no generic use cases, just real ideas that fit your business and the ranked by ROI potential. It takes about three minutes to run and it's like having your own personal AI strategist for free. If you want to try it for free, check out the link in the show notes or go to hatchworks.com backslash AI dash opportunity dash finder. So let's get started with the first one. I think that that point though, right there is, it's such a big thing because this is one of those transformations that you almost got to break the current line of thinking. It's like coming out of the matrix to a certain extent because it's so transformative in a way.

6:19Yeah, a hundred percent. it's it's not like anything else we've seen before like i'm old enough as you can tell those of you who are watching this with the lack of hair that i have and the gray hair that i still have is that i've i've seen the dot-com rise and collapse in like 99 and 2000 and i've seen the house you know market rise and collapse and and i've and now this and it's very very different and maybe we touch on that first on why I think it's so different and why I think people should think differently. And it's very different from two major aspects. Aspect number one is how broad is it, right?

7:02It really touches almost anything we do and definitely everything we do in a business that is not manufacturing anything, right? And even then in manufacturing, there's a lot of AI stuff on both the manufacturing itself and the design process and the product design process and predictive maintenance. There's a lot of AI stuff in production as well, but it really touches almost everything we do in business. So that's number one. And number two is speed. If you even think, and I love giving that example. Like I said, I've been through the dot-com thing when the internet showed up. And I remember the first time I connected to the internet because it was the biggest anticlimax of my life my roommate at the time we were 21 i'm guessing 20 20 and change and he comes one afternoon to our apartment he's like listen i bought us a modem and i go what the fuck is a modem it's like oh it's this thing it's going to connect us to the internet yeah like what's an internet it's like oh it's i don't exactly know but it's going to be awesome.

8:12We're like, okay. So we, we open the box and we unwrap it. And there's obviously you can't search on YouTube how to do it because there's no YouTube. We actually read the manual. We connect the wires and we connect it to the phone line and we connect to the thing and we install the software with the CD and we do everything as it says and he goes for a while and then there's a prompt like like uh those of you remember dos like a little triangle symbol thing to put in something and we didn't have a clue what to do then and that was the first time i connected to the internet and that was 94 yeah i wasn't quite in college but i had i remember getting chewed out by my parents because you couldn't be on the phone and the internet at the same time yeah yeah yeah he was i was gonna eat that stage yeah so that was 94 the first time i opened my first email address was in 99 yeah so five years five years has passed from the first time i connected to the internet to the first time i had an email address forget about all the stuff that we're doing today with e-commerce and watching satellites in real time and communication and video conference, like email, five years.

9:31So as fast and incredible as the internet change transformation happened, it happened really slow. It gave us a lot of time to adapt. This thing is as fast as an F-16, going back to my experience. It's changing on daily basis. There's new capabilities that did not exist before. And businesses cannot operate on a daily basis unless they adapt the way they're thinking. So I know this was a very long intro, but I think it explains why this one is so different. And just to stick on that point, I don't know your take here, but I've thought about this exact same scenario comparing it to other things like internet mobile.

10:13And it's like, oh my God, it's moving so much faster. But I wonder if it's actually moving so much faster or if the endpoint that we're going to get is just so much bigger that this truly is if you put it on a timeline it's still at the same spot but where we get it's just going to be so insane we can't even really comprehend it yet i think it's one of the two it's either way faster or in the the long-term timeline it's just going to blow everything away i think it's both a little bit of both i think it's birth listen i think the the whole idea behind you know agi super intelligence and and even before that because everybody okay you know the holy grail is agi or super intelligence and for those of you who are listening i'm not sure what that is agi is artificial general intelligence which is basically an ai agent that will be able to do everything a human does from a cognitive perspective at or above human level and super intelligence is do everything better than we can do on on multiple aspects.

11:14But I'm putting that aside for a second, whether that's going to happen in two years, three years, or 10 years. And that's kind of like the range that the experts are talking about. The specific tasks that we need in business, it already does better than we do. So I don't care when it will be able to do everything better than us. I care about, okay, can I have five of these doing five major things in my business way better than any employee for practically free, the answer is yes, today. So yeah, so this is how I look at these things. But do you want to dive in? Yeah, let's do it. Let's jump into it.

11:51Let's dive in. So the first law of changing the way you think about how to implement AI in your business is stop thinking efficiency and start thinking outcome. And I know it sounds weird, like, what do you mean? Like when we plan, we always plan, you know, with the end in mind, And we're trying to adapt to that and build steps. But the reality is, as business people, we are trained, and especially people who have been in managerial positions for a while, we're trained to think of the process. So I'm a very visual person. I literally think in flow charts. But, okay, the flow chart of the process and everything we do in business is a process.

12:35Whether we ever mapped it or not is a different thing. But it's a process. This person does this thing using that tool, then it goes to this person, they have to do this with his software, and then he goes to that person, and that's how business things happen, whether it's writing proposals, reviewing client status, checking out prospects, delivering software, whatever the case may be, there's all these steps in the process. And as managers, what we look for and look for our teams is to find small efficiencies in different steps of the process. So let's take customer service as an example. How does customer service work?

13:12Well, we get a customer service call, and it comes either in the form of an email or a form of a ticket or a form of a call or a chat, like whatever the input is. So that's step one. That initiates the process. Step two is we need to evaluate what that thing is and the severity of it and how important this client is to us. These are usually kind of like the vectors you're looking at. Is this extreme? Is this an important client? And what category does it fall into within the services or product that we provide? And then we need to assign it to somebody to resolve. And then there's an iteration with that person.

13:49They may need some additional information. And then eventually it gets resolved and we have hopefully a happier customer. But the goal is a resolution and a happy customer. But the way we treat it as business owners and leaders is to look for incremental improvement in each and every one of those steps. How do I add the customer service chat button in a more clear place on the website so more people can find us easier and chat with us? How do I improve the calls queue on the phone so I can take more calls each hour with the same amount of people that I have today? These are the things we're looking for because this is the only way we train to think.

14:34Now, it's awesome, right? It does help. Like if you get a 5 % incremental improvement in one of those steps, especially if that's your bottleneck. And again, that's the other thing. We're trained to think in bottlenecks. And we'll get to that in one of the future other four concepts. But if you solve the bottleneck, now you have a much higher throughput for everything else, right? So there's a reason why we think this way. But the reality is with AI today, in many cases, you can jump straight to the outcome or at least a few steps in the process, completely circumventing them. So instead of looking for an AI tool to get you a 10 % improvement on how to better distribute the customer service tickets, you can have an AI customer service machine that can take calls, that can prioritize, that can solve the problems, and that can communicate with the customer 24-7 in any language on any platform they want.

15:39whether it's voice or email or chat or all of the above. And over time, as it gets integrated to the systems that we have in our company, whether it's an ERP or a CRM or a email marketing automation, whatever field you're in, it will be able to actually solve the problem. And so you're going from a situation of, I'm looking for these small incremental fixes or steps to, I can have happy customers almost immediately. And if you think about, I love customer service examples because as a customer, especially of large corporations in the US, it's a catastrophe. Like if you're ever trying to get help from any large organization in the US, it's a complete nightmare.

16:30And the reality is in the very near future, and when I say very near the future, I don't mean tomorrow, but in the next two to three years, you'll be able to solve problems in the minute you communicate with the system, because that's the way it's going to work for probably 90 % of the problems. Yeah. And just to like pause there for the audience, this is huge right here. This is the whole idea of breaking out of the matrix. And you hear a lot of the times today with Gen AI, it is very much efficiency-based, we'll do more with less. But I I love your point you mentioned. It's like, you know, do we change the button here on the website?

17:06What if there is no website? What if that's not the modality you're even interacting in? It's like where it's reprogramming your brain in a sense with what do you want to achieve? And you've got to throw all the other stuff out the window. And I want to ask you this. I feel like this gets to the point where you compare big, large legacy enterprise with legacy process people technology versus new startup. you know, I mean, maybe it's an obvious answer, but who's poised to really take advantage of this new technology? It's probably the starting fresh in a sense. I think there's actually a slide that's going to touch on that.

17:44We'll get to that. So one of the four concepts is going to touch on somewhat of what you're saying. But in general, I think we're about to view the biggest valuation change in history of valuations because of what you said. And there are several reasons for that. One is what you said, right? So smaller startups can just adapt to these capabilities and technology much faster and continually adapt because like I said, this thing changes on a daily basis. There's new, really incredible capabilities that are coming out regularly. Large enterprises will never be able to adapt on that speed. Smaller companies might.

18:25And so if they figure out how to continuously evolve as this technology evolves, they can do, basically they can create significantly more value faster and faster when all the giant companies will not be able to catch up, which means they'll be able to provide similar or better services for a lot less because they have significantly less overhead. So I definitely see a huge shift moving away from large corporations to smaller companies in whatever niche components of what the big company provides. Yeah. I mean, we're potentially seeing whole changes in business models to an extent. SaaS, you know, could be a thing of the past, potentially.

19:06There may be a new, better way of doing it down the road. Yeah. Going back to that, by the way, connecting into this point and kind of like me speculating. So today we have an app store, right? And now we have a GPT store as well, but we also have these coder co-pilots, right? You can go in not knowing how to write code at all, like me, and create code, which I don't create anything sophisticated, but now I started dabbling with creating different automations that use code, with creating API connections and and schemas that use code with creating plugins and extensions to Google Sheets that use code.

19:48And I don't write the code. ChatGPT writes the code for me. And I test it. And if it doesn't work, I tell it what doesn't work and it fixes it for me. And I try again. So run this a few years forward, especially for smaller apps. Usually think about the bigger apps we use. Most of them do a million things, but we need two things for real. Like we pay for the rest of it, but we actually needed to do two specific things. I think the day in which we go into a quote unquote app store, or it will be an app creator. And I say, Hey, I have this use case and I need an app to solve it. And it will literally create the app for you on the fly.

20:27And now you have an app. Now you can decide to share that app with the world or not. It doesn't matter, but that app is going to solve your very specific niche problem with this API with these kinds of clients or that kind of scenario with these amount of users. And it will create it for you right there and then. And I think that day is not too far into the future going back to thinking of what the outcome that I need and changing our mindset from thinking, oh, so which software do I need? What kind of integrations I have to create? How many people in what positions do I need in order to create those integrations?

21:02No, here's the outcome created for me. Okay, it's ready. Let's start using it. Yeah, it reminds me a bit, and I promise we're going to get to the next one in just a minute, but so many good points around this. But at Hatchworks, we've defined our generative-driven development methodology. And if you remember, I'm sure you do, extreme programming, you had the concept of paired programming, right? You'd literally be two engineers sitting at a keyboard working together, and it was much more efficient in terms of what you were trying to do and less rework and all those kind of things. How we're thinking about it now is this AI agent, whether it's ChatGPT, a custom LLM, whatever it may be, that is your buddy, in a sense, working with you.

21:42and then you progress down the road. What if it's actual AI agents partnering with other AI agents and it just starts to get into this crazy network effect down the road? But that's how we're starting to think about it and apply it at Hatchworks in a sense. Fantastic. Yeah, I'm with you 100%. And I'm talking to, you know, some of my clients are software companies and I also have a software company myself as another business. And over there I have a software company. So using these co-pilots to develop snippets of code became standard for companies to figure it out. And it just saves so much time and so much less errors in those small snippets.

22:23But those small snippets would become bigger snippets. And these will become whole components that you'll be able to just let it develop. All right, let's hit the next one unless there's any other points. So the next one is called from profession to skills. And so what do I mean by that? And what I mean by that is if you go back to the 17th century, there was a profession called computer. So if people had business cards back then, which I'm not sure they did, but if people had business cards, some business cards would have computer on their business card. Now, nobody has a computer on their business card today.

22:59When I was a kid, our next door neighbor was a typist because she could type on a typing machine. Now, how many typists do you know today? Well, very few because we all need to know how to type. It's a skill. Everybody does it now, yeah. Now, everybody's a typist. And there's a lot of examples like that. And I think what, not I think, what AI is doing, it's turning a lot of professions into skills. Now, when I say that, people are like, no, no, no, no, no, no. You still cannot design like a graphic designer who has experience and took it in university. I'm like, not yet. i'm getting pretty freaking close yeah and just for the audience that can't see there's a mid journey i'm assuming this is some type of it's a ai generated image it is and it looks real it's it is insane our designers starting to play with this stuff and it's crazy what you can do in the tool but then if you connect it with photoshop like it's game over it's it's insane what you can do now so if we go back to what you just said graphic designers computer coders uh different kinds of administrators um paralegals etc etc there's so many things that used to be a profession you had to go to the university study for four years or six years go and work for a company get some scars on your hand to show that you know what you're doing.

24:35And now you can have that skill if you learn how to use these AI tools and get to extremely impressive outcome. And some people say, well, you're going back to your slide and I appreciate the fact you like it. It's one of my favorite slides ever that I've created. And I've created that image. And yes, it took me this particular image probably half an hour to create. but if I had to send this to a professional agency to create it would have taken a few weeks would have cost me a lot of money and would have spent a lot of time of going back and forth with different iterations of this so here the iteration took me two or three minutes each one on me journey until I got exactly the outcome that I wanted and the slide looks amazing I'm not saying this to pat myself on pat myself on the shoulder I'm saying that because the ability to create amazing graphics, great research, fantastic summaries, great data analysis.

25:33So data scientist kind of stuff is now at the fingertips of any person who's willing to invest not too much time in learning how to use AI tools. So stuff that used to be professions is very quickly turning into skills. You look at even prompt engineering, that's the latest profession now. That's going to That's like the typist, right? That'll just be standard thing. But I got to ask you this though, what happens in this new world where we're not tied to a profession? And if you're going to get into this, let me know. But you got me thinking now, I haven't actually thought about it in this way.

26:10What does that new world look like? And who actually gets ahead based on this paradigm shift in a sense? So I'm going to address it on two very different aspects. And again, I don't know. Yeah, this is all pontificating, right? Based on my own thoughts and a lot of stuff that I read and hear and follow. The first aspect is the professional side. What does that mean for businesses right now? Because your audience wants to know, okay, what do I do with this information? What you do with this information affects how you hire and affects how you train the people in your organization. You must, I don't care what your company does.

26:47you must have people who understand how this whole ai game is played how these tools work what they're capable of doing and how to implement them in a business framework so this is one and that means you need to hire consultants usually a step one so that's why i have a consultancy right because most businesses do not know how to do that that's right uh over time you will either train people internally or hire external people to hold that role. And then in a longer time, everybody will just know, just like everybody knows how to use Microsoft Office, right? It will be, yeah, okay. Of course we use AI because this is a part of everything we do on the day-to-day, but that's kind of like the process.

27:32So this is how you hire, who you hire, what skills they need to have, what experience you want them to have with AI tools and how how you train your existing staff on how these tools work to change, like you said, that mind shift of how you're doing things today versus how you want to do things next month, if you want to, is one aspect. But the bigger aspect, which is really troubling. And I don't have an answer for, I'm just a big believer in humanity and that we'll figure it out is beyond profession. It's purpose. Right. Like if AI can do all the stuff I need to do, and because it's stuff I need to do, I aspire to do it.

28:20People aspire to do things that they want to do that they know that are doable. I want to provide for my family. I want to be able to go hiking at least once a month. I want to take a trip to Paris. I want to learn how to play bass. It doesn't matter. You aspire to do something. but what if that aspiration is already it's already done like there's there's yeah like there's no point in doing it because it's already done so what what's what becomes our purpose in life and i don't have a good answer to that like i said we'll have to figure it out probably not in the next two years but our kids will definitely have to figure it out because all the things that we need to do today are going to be very, very different by the time they grow up and have to have a profession.

29:08Yeah, I could see it as the dystopian future. What's the movie, WALL-E, where the people are just mindlessly moving around? Or is it something to your point, do we get to things that are of true, deeper purpose that maybe we're not even, you kind of think of the Maslow hierarchy of needs. Maybe there's other stuff we can focus in on. That's that's really you got me thinking now yeah it's like i said i don't have an answer there's probably smarter people than me that don't have an answer uh i think time will tell but we're definitely we'll see humans evolving because everything we know as the day-to-day is going to change okay let's touch on the next topic and we touched a little bit or around it so far and this is there's two ways to win in the ai era one and this is those of you who can see the graphics it's a kind of like a machine boxer on the right side that has a lot of data in his brain and that's proprietary data so one way one way to win with ai is proprietary data companies who have a lot of proprietary data can train models on that data and nobody else can because they're the only ones who have that data.