Exploring AI's Impact On Entrepreneurship And Innovation, with Lior Weinstein
Serial entrepreneur Lior Weinstein returns to the show. Teaming up with Dan and Steve, he shares his systematic approach for tackling business challenges and leveraging AI alongside human capabilities. Three entrepreneurs operating at the top of their game promise valuable takeaways to transform pains into new revenue streams and fuel your success.
Show Notes:
Every company has a history and constraints they bring along.
Good marketing requires empathy.
Too many entrepreneurs overthink, overengineer, and overbuild.
Though it may seem counterintuitive, it’s better to build the website before building a product.
When an amazing technology launches, people make predictions without appreciating or understanding the actual engineering problems that underpin the technology.
The rate at which the open source community is creating competitive products is incredible.
You’re only as smart as the quality of your questions.
Search engines are becoming answer engines.
We're going to learn more and more about human intelligence by interacting with AI technology.
Resources:
Book: The 4 C’s Formula by Dan Sullivan
Article: The 4 Freedoms That Motivate Successful Entrepreneurs
Book: The Gap And The Gain by Dan Sullivan and Ben Hardy
Dan Sullivan: Hi, everybody. This is Dan Sullivan, and this is the Free Zone Frontier podcast. My co-host, Steve Krein, and a really great, great continuation of the wonderful discussion we had with Lior Weinstein, who is one amazing person. Well, the opening project we had yesterday, the opening thinking tool, was inspired by you, Lior, because I said, what's Lior's biggest problem? And I've been noodling this for a couple of years since we had sort of a first in-depth experience in a breakout group in one of the 10x Connection Calls. You identified that you're good at everything that you set your mind to. Your parents thought you were extraordinary and your teachers thought you were extraordinary. And I asked, you're good at everything, aren't you? And I said, you know, it's your biggest weakness. It's your biggest weakness that you're good at everything. Steve, we created a tool called Your Life as a Single Project. Okay? And what we did is we put together The 4 C's and the Four Freedoms in the matrix and you had to answer 16 questions. You're going to have to see it on the virtual.
Steve Krein: I saw the tool last week. I think you previewed it on the Connection Call.
Dan Sullivan: Agreed. Could have been. I didn't do it last week, but I did it on a Free Zone Connection Call. But anyway, the big thing is that I see a constant and a pattern in Lior's life. I personally see it. Okay. And the question is, could I get Lior to see it? The big thing is that you're almost pure capability. And I think a lot of it has to be how you grew up and where you grew up has a lot to do with it. Because Israel doesn't have a lot of margin for error as a country. And I think that the Israeli background is really, really important to who you are. And the reason is that because of the very constrained conditions and the edge-of-the-knife existence that is a normal course of events for Israel, you don't have a lot of time to just get real simple. You have to get real simple really, really fast. But it's the getting simple really, really fast and understanding what the simplest thing we can do in the biggest picture actually creates the accelerator. And that's who you are. That's the capability, that you can probably get simpler faster than anyone else and it's the combination of the elements that exist at the simplest state is what accelerates because it's freed up from all the constraints. The constraints of history. In other words, every company's got a history and they have constraints that you bring along and you immediately get rid of all the constraints of the past so that what's been created that's really valuable is now just free to expand.
Lior Weinstein: Yeah, I guess the biggest value in those conversation is I don't have the constraints that they have because nobody tells me about them.
Dan Sullivan: No, if you're an Israeli and they moved to the United States, you feel like a shark at a beach party.
Lior Weinstein: Right. That's why a lot of Israelis are very successful as entrepreneurs in the US.
Dan Sullivan: Oh, yeah.
Dan Sullivan: Yeah, because here it's easy here. It's like, oh, you just do things and there's enough market and people buy and people just pay you. Yeah.
Dan Sullivan: Yeah, and the United States is the only country in the history of the world that can afford to be lackadaisical.
Steve Krein: Lior, as you reflect back on our conversation over the past, I think, 45 minutes or so, what's your biggest takeaway, even from reflecting on some of the questions, but actually what Dan just described as an insight and a tool belt just for you?
Lior Weinstein: I have to say that last part is very profound to me because back to the tie-in that I'm very empathetic in general. I think that's what made me a good marketer. Like I was able to just appreciate people's problems and kind of feel where they are. And that's the same when I talk to another entrepreneur, like having the same mindset that he has or she has and understanding the 360 problems of entrepreneurship, not just this you know, funnel issue that you have, or maybe you're trying to build this device for half the money, right? I also understand that you also have employees and investors and market and all those kind of stressors. And the fact that I can connect with their vision very quickly, I can understand. That's probably one of the biggest feedback I get from them. I'm like, I feel like I just share with you and you get it, and my executives are still trying to get it. So I connect with their vision very quickly, but I share none of their constraints. They don't tell me about the problems. Or if they tell me about the problems, I ignore the problems. I'm like, okay, if that's the vision that goes to the past, what needs to be true for that vision to happen? And specifically the thing I'm trying to build is the system that makes the vision inevitable. And we spoke about that in Coach as well, where 10x is just an event. Right? It's not like there's something that creates the 10x. There's activities that create the 10x. And if those activities proceed after 10x, there's 15x and 20x and 30x and so on. And that's my mindset on all these problems. Once I understand your vision, I'm trying to think what's the system that creates this vision. And then it goes back to the mechanics of what are the constraints, what are the risks, and so on and so forth. That's for me, really just saying I can connect with the entrepreneurial vision very quickly. And because I don't have their constraints and I'm a systems thinker, then it's easy for me to create the system and then it's an engineering problem. Okay. So we know what we want. What do we have? What are the resources? What are the gaps? And then it's just, you know, do the work.
Dan Sullivan: Excellent. What have you learned, Steve?
Steve Krein: I think there's a profound difference in having the value of and benefit of a large company and the complexity that comes with that and having the freedom that you're describing of operating alone to pursue joint ventures that are multipliers. And I think AI is a big enabler here for this trend of individual entrepreneurs able to do a lot of great work alone through collaboration and teamwork without the complexity, especially when it's not their Unique Ability or they don't want to integrate that into their life, as you describe some of the things you're trying to balance. So I think you're taking a refreshing take on JVing entrepreneur to entrepreneur and perhaps being a new perspective that understands what they need or what they're going through. So like an entrepreneur partner, that's not truly partnering as a company long term, you know, and having the complexity of that, but having some of the benefits you described for them to take advantage of perhaps seeing things as though they might only see them if they were looking fresh at it like you are. So that was really insightful. I didn't realize you had that.
Lior Weinstein: I would say in the joint venture side, I partner with big existing companies, but the way we do it is we agree on current, and then we share upside. Not 50-50, obviously, if it's a big company that, you know, and we get you with a company that makes 250 million a year. I'm not going to get, you know, 10, 50% of a company that does that. But we can also isolate and articulate what is the new value we're creating. And I get to share in that value. And the nice thing is that the zero point in the zero to one model is just a lot of resources or existing business relationship or existing clients. It's not zero like I was used to in the start-up world where zero is zero. It's ether. You have to get the items, you know, make the tree, get the log, do the whole thing. Also persists in existing bigger companies.
Dan Sullivan: Yeah. Going back to the zero to one model, when I was reading Peter Thiel's book, it struck me that a big value for his is that one of the considerations of growth that it's invisible to everybody else. Because if you're invisible, you have no competition. Okay. So my sense is that you're a zero to one accelerator that since we're going from zero to one, we have a certain time frame before you become visible.
Lior Weinstein: Yeah.
Dan Sullivan: I mean, it's like a good tumor. And I think that your duration in that situation is what's the fastest we can get from zero to one. But if it keeps growing and you never get to one, I think that's your notion of a lifetime growth relationship.
Lior Weinstein: Yeah. And to me, probably the first thing that I always try to clarify is that what's the one point? So the goalpost doesn't just keep moving. And we can actually measure it and hit it. And that's where a lot of entrepreneurs are not in my fields, but they need those capabilities. They just overthink, they over-engineer, they over-think, they over-build. And because I can understand their side as well, I can make sure that when we build something, that's the effective piece. The efficient piece is fast. But the effective piece is, what is the one point? What's enough? In marketing, one of the better examples you learn about marketing earlier on when you're trying to do a new product is, I was mentoring entrepreneurs in Georgia. There's a big kind of entrepreneurship center in Atlanta. And I was kind of walking them through the product. Let's assume you build a product. Let's assume you build the app. What happens? And they're like, well, I need to tell people about it. What do you do? Like, well, I guess I need a web page. Or a website. I'm like, okay, do you need a website or a webpage? Like, well, I guess I need a webpage. I'm like, great. What are you going to do on a webpage? Well, I'm going to, you know, show some pictures, show some text and, you know, show the offer. I'm like, great. Let's start with that. Let's build that first, instead of building the entire product. Because if the end of the entire process you're saying is that, let's just start with that because that's going to take you two days. And with AI now, it's going to take you 30 minutes, if that, and you can send some traffic, send some people in and see if it works, and then you know what to build. Yeah.
Dan Sullivan: So Lior, I'm told that the world really changed on November 30th, 2022, when open AI released ChatGPT. Okay. Is that your sense?
Lior Weinstein: I think similar to COVID, that suddenly the world was forced into sets of technologies that have been around for a while with early adopters. That's the same with ChatGPT. Like it's thrusted the world into applications and utilities and just kind of basic intuition of what's possible with computer science that most people didn't have, but practitioners that were in the business certainly knew about. There's no doubt from a product perspective, not from a technology perspective, ChatGPT created this, which was launched on November 30th to the world, created awe and created new standards. Now that everybody's doing chatbots, as if like chat suddenly became the most valuable interface for whatever reason, it created new standards and new expectations. I think similar to every time an amazing technology launches, people also we have kind of the Star Trek mindset of immediately forwarding 300 years of capability, and like, oh, it's just around the corner. In six months, all of this is going to happen, or in two years, all this is going to happen. They don't have the appreciation of the actual engineering problems that exist in that world. One of the bigger unlocks that people in the business more appreciate than people out is the hardware. So the algorithms were there, right, since 2017, when the original paper, attention is all you need, was launched by the team at Google. But it really wasn't viable from a product perspective until NVIDIA figured out how to create the chip that made it. Like if you had gone to ChatGPT and you put in, you know, give me a hundred blog posts about the, you know, full marketing strategy for my company with, you know, variable topics, 2000 words each and TikTok scripts and whatnot, and you came back 24 hours later and everything was there, that would have been pretty impressive. But it's not nearly as impressive as real time, which is what this chip, what these hardware revolutions can do. And from that perspective, I think it opened imaginations, it opened receptivity. You know, when cloud storage, for example, launched, people were highly skeptical of it for years. You know, the Dropbox, the Box, generally put your data on the cloud. It's like, what? I'm going to, you know, security and hack or whatever it is. And now you wouldn't imagine not having cloud storage, right, for your corporate documents or personal documents or so on. And it's just ubiquitous, it's completely standard. And I think AI, well, ChatGPT with the advent of it in the market did the same in that category. Like now people are looking forward to it, they're excited by it, it's standard, it's expected. By the way, certainly in our circles, a lot of people talk about and use it, but it's still, you know, not even a common population in terms of usage, which just shows you the incredible upside that it still has. So I would agree with the statement, primarily because of the mindset shift that they have on these technologies.
Steve Krein: Yeah, it democratized, I think, access in a way that, although many people can poo-poo it as it's been around, and as you said, some of the things that it's doing people have been able to do and utilize for years. But the accessibility of it, even for kids who are in school and need a co-pilot to kind of brainstorm or work on things, I think the expectations of quickly seeing how you can use it on a daily basis to help you be more productive and more effective and get more done quicker clearly is something that occurred when ChatGPT became the interface that made it accessible but when you look back at like the netscape browser in the mid-nineties, you look at the iPhone in 2007, I think each of these interfaces might have democratized things like for the phones or for the internet that had been available prior, but these were watershed moments. So I do think when Apple kind of integrates in and some of these other companies reinvent the interface that we use with phones and AI, it'll be one of those moments again where it's just more seamlessly in the background, kind of like the internet is today or phones are today.
Dan Sullivan: The interesting thing is, my experience, the problem with the word democratize, it connotes a certain sense of equality, and my feeling is it's doing just the opposite. It's creating greater inequality in the world, and that the distribution of people who are opportunistic is completely unequal in the world. But what I think it's done is randomize the entire technology world, and it's that you can't predict who the new winner is. It's actually introduced a great deal of unpredictability. The big thing I've noticed with the except of, you know, the chip makers, I don't see any centralizing force in the technology world. In the year and a half, I'm not seeing the big players. I thought Google was actually caught with their pants down, and they've not responded in a way that indicates that they know how to go forward so far. Now, there may be a secret war room in Google where they are, but they're not exhibiting any corporate behavior that indicates that they're on their game with this one.
Lior Weinstein: I completely agree. I actually said, you know, I had a few friends and I do some due diligence for private equity companies and VC companies. And I generally advise against investing in these companies for a few reasons. One, I think the rate that the open source community is creating competitive products in the technology and in the industry is incredible. Incredible. I mean, now you have open source models that are better than the November 30th, you know, version of ChatGPT. And it took, you know, less than a year pretty much to get to those. So the exponential, you know, impact is across all industries, including the open source type. It's the first time, I think, in a few decades where larger businesses have more opportunity than start-ups. Because now, back to what we were talking about earlier, their ability to collapse decades into days and years into months with the MVP, with the minimal viable product, with quick product iteration and creation, they're not as fast as start-ups. But now they're fast enough, they can be fast enough, which earlier, you know, if a large company wanted to introduce a new product, it took them like three years, four years, the market had passed them, you know, by that point, plus it was, you know, big and chunky and messy. But now they can actually do it in months. But they have something that start-ups don't have, by definition, they have the business relationships, they have the data.
Dan Sullivan: Well, they have the teams too.
Lior Weinstein: Oh the teams. It's incredible to see. To be honest, if you're a start-up now building in a market where there's a large competitor that with the application of AI can just pummel you, I would stop. I just don't think you have a way to win. And that's one of the more fun aspects of some of the work I do right now, like go into big companies and say, hey, we can create a product incubator or product factory around this because you have the relationships, you have the data, you have the capabilities, but you don't have the process to actually fabricate it, you know, quickly in front of people.
Dan Sullivan: Yeah, I have a rule regarding technology. I always keep smart people between me and the technology. Okay, you're a smart person. So Steve was a smart person back, you know, when he first entered the Program. But the big thing is, I'm really interested in thinking. I mean, my whole passion in life is, how do you think about these things? You know, what's the mechanisms, your own thinking? And I didn't need a lot of experience, but I've really developed a very nice relationship with perplexity, because every time I do a search with perplexity, I say, what is my relationship with this intelligence? There is intelligence here. What is happening to my intelligence as a result of this intelligence, okay? And I've come up with, you're only as smart as the quality of your questions. That's the thing that I've got from here. If you ask a really intelligent question, you get a really intelligent answer and it will give you a stupid answer to a stupid question.
Lior Weinstein: By far the most important skill, you know, search engines, you know, introduced in the, like in this current form, mid-nineties, right. With AltaVista, Yahoo. And eventually Google got the leg up because of their algorithms, because of the way they were able to index a lot of information very quickly and find information that indexed very quickly. Search is like a chatbot, it's just an interface to do something, to access information on the internet. And the thing about what, A, I don't love calling it artificial intelligence. And in fact, before these were called low-stackage models, they were called large-number models. Because of the debate of the intelligent, like, you and I spoke about this, right? They cannot create net new knowledge with this set of technology. And then, as Sam Altman actually just said it a couple of weeks ago also, like, the big breakthrough is, can it do scientific breakthroughs, you know, by itself? That's going to be our signal, you know, that we have actual intelligence or general intelligence, something like that. But the same thing that search did and unleashed incredible value, measured in the many trillions of dollars, this set of technologies is doing the same pretty much for any human knowledge-based work. Like, what you're doing with Perplexity and what Google is trying to do but is not really doing a great job, is that search engines are just becoming answer engines. It's no longer about… the search, like it's no longer about showing you options, just giving you the answer. Google has actually done it in other categories over the years, right? So if you go to Google right now and you search for weather, you just see the weather. You don't go to weather.com. You just see the answer, right? But this is happening across everything, which is huge across any knowledge base. And it's not just questions, it's instructions. It's clarity of thought. In the context of search, it's questions, but in the context of AI tooling as general, it's just, can you articulate the impact? Can you articulate what you're trying to do? And then these tools can just be incredible shortcuts to make it real.
Dan Sullivan: Yeah, one of the sort of interfaces that I've created with Perplexity, I break it down into 10 things. I always use 10 things. And I'll say, in what way, for example, in the last 230 years, what are the 10 ways that the U.S. Constitution is exactly the same then as it is now? You know, 15 seconds, 20 seconds later, just like that. And that's real knowledge. That's real knowledge. You know, I'm, I was struck there. I said, you could study constitutional law for four years and you wouldn't get the clarity of how the thing has sustained itself over 230 years. Cause if it hasn't changed over 230 years, that means it's real.
Lior Weinstein: You know, it's a judgment call. I was just talking about this in a workshop a couple of weeks ago. Somebody was complaining about hallucination. I'm like, it's a funny concept for me that people complain about hallucination because 100% of the output is hallucination. It's not a search engine. This is not retrieving from an index. It creates the response. It's the human that makes the judgment that it's a hallucination. The human is saying this is false, or this is true, or this is useful, or this is not. It's not the thing.
Dan Sullivan: Yeah. Well, one of the reasons I use AI, but I don't talk artificial intelligence, because the definition in the dictionary of artificial, number one, is that it's man-made, and number two, it's phony. To think that this equals human intelligence is phony. These are two totally different thinking systems, you know? So my feeling is that we're going to learn more and more about what human intelligence is by interacting with this technology.
Lior Weinstein: I haven't thought about this. That's an interesting concept as a thinking system. It's really doing processing. That's just the thing that it's doing. Yeah.
Dan Sullivan: We don't do processing. Humans don't do processing.
Lior Weinstein: We're meaning makers. That's right. That's why I think it's an interesting concept. I haven't looked at it from that perspective.
Dan Sullivan: Okay, so now that it's available in a wider way, it's more accessible. How do you add this and integrate? I mean, you're probably already doing it, but the tools are more available now and there's more tools and the tools are getting better. How does this relate to the enterprise called Lior Weinstein? This dervish, this constant dervish in motion?
Lior Weinstein: Well, for me, first of all, as a curious junkie of newness, it's great because it's an endless stream of new things. I think as a contradiction to the blockchain world, where the blockchain projects also had this, you know, still have a lot of streams, a lot of projects, a lot of new concepts, but all of them are built on this thing that this will be big one day. Right? Like this project, this app, this system is going to be big one day. In 10 years, we're going to revolutionize that, whatever it is, whether these AI tools are effective now. Like you suddenly sign up to something and it works and it's your video. Summarize your meeting like immediately right now. So for me, there's the, the personal stuff I use, which are probably the 80, 20 that everybody does. The meeting summaries, the video summaries, helping you brainstorm. I love same thing. I love using these tools as a thinking buddy before a meeting, before a workshop, just kind of work with it. I use it a lot with my family. Actually, I gave a whole AI and family workshop a few months ago, where I gave examples of, you know, my grandfather was a great storyteller, and I am not, right? I don't have his skill set. I mean, he could make up the stories.
Steve Krein: But ChatGPT can make you sound as good as your grandfather.
Lior Weinstein: So what we do, and I've been doing this since ChatGPT came out, I actually shared it in the first Free Zone session in January after November 30th, in January 2023. And end of day, end of vacation, whatever it is, I have three kids, but like two boys that I read stories to, they're old enough. And I say, this is what happened today. This is my kid's name. And they like Power Rangers and Minecraft and put in a fart joke because they're boys and it's funny. And I specifically give instructions. I'm like, give me a 10 minute story, not a 45 minute story, right? Because if it were up to my kids, we would be there for like two hours. That's incredible utility. It goes back to the value unlocks in the real time element of this, like the fact that they can do it right now. So there's the professional side, the summaries, the writing, the thinking buddy, the personal side, planning, writing. and so on. For me, from a pure business perspective, my mindset is already in the context of, let's assume this is solvable. Now there's just more tools to solve things. Meaning it wasn't an enabler or unlocker for me in terms of solutioning, but it's introducing thousands of more ways in solving something. One of my probably favorite applications that I've had since before AI, but now these tools are better, is kind of these live recording. Like I use a tool, for example, called Rewind. I think it's AI. But there's a few of them, there's open source versions of them as well, which basically record your entire computer or phone, whatever you have installed on. So at any point in time, I can go back and say, oh, Dan says something, thinking system or just system, and I can put in system and it'll zoom into the date and the moment you said it, and I can play back like it's a Minority Report kind of thing. And having that as a second brain, not from a processing perspective, but from an access and reference is incredibly helpful. So I don't have the task of record keeping my life and every single moment, but I know it's there and accessible and I just need to remember the threads.
Dan Sullivan: Steve, I'm going to ask a question and I'm going to ask myself the same question regarding Lior. The big thing is, right off the bat, what are some possibilities for Lior to be useful to StartUp Health?
Steve Krein: You know, I was thinking about that early on in the episode. Lior was describing his partnership with entrepreneurs and why I asked the question, how do I know when I should be introducing or I want to be introducing Lior to someone or a situation where Lior could be instantly helpful? And the real answer is I'm not sure where the sweet spot is to partner him up with the individual companies. So I'd rather start with like an office hour where he gets introduced to the community so that we can get much more specific with the entrepreneurs and StartUp Health. And it sounded very situational the way you described it, Lior. Like, well, it depends what they need. And so you talked about marketing or tech or whatever it is, you know where to bucket you. I'm wondering the situation that lends itself for people to see right away how they can leverage you as an entrepreneur for hire, or an entrepreneur JV, or an entrepreneur partner, where oftentimes a consultant's not going to do the job, or the consultant's not going to fix the problem, but they know how to plug you in.
Dan Sullivan: I want to go a little bit more local, Steve, with that question. I'm not sure of 500 companies, but StartUp Health itself.
Steve Krein: Oh, that's a good question.
Lior Weinstein: That's a different question. I want to add something to your comment, which is fair. Now, the JV is my end goal, but it's not necessarily where I spend most of my time. The JV is an end of a funnel. And part of the reasons why I can be effective and stuff that I like to do, I like to do this more than Netflix, right, is in the creativity, in the problem solving, in the brainstorming. And usually in strategy elements, I love doing it and it's very helpful for other people. And in 99% of cases, they get all the strategy they need and I don't want to do any of the work because it doesn't translate into a JV model or they know how to do it. They just needed somebody from the side to tell them, hey, you know, look at this from this angle. Now you see it's clear. Okay, I can go. And those are usually great because people back to the earlier comment, they have their blinders on because they're focused entrepreneurs in their market and they have their baggage because they've been in the market for 20, 30 years. But if somebody can be there that can quickly catch up to where they are, but not have the blinders and have the owner mindset with all the challenges of being an entrepreneur. Being a part of that is helpful for me and helpful for them. Because now I get to learn more about a new market, a new technology, a new avenue. They get to get the outside perspective and the strategy. And we both win. That's 100% win. That's not a win for me. I can do that probably three out of four weeks in a month and one week due to JVF.
Dan Sullivan: And with mine, it's pretty straightforward. We're a content machine. Strategic Coach is a content machine. And that comes in new tools, six new tools every quarter, a new book every quarter. By the end of the year, we'll be getting five, six, seven, maybe 10 patents per quarter. I'm now producing new tools just to have patents. OK, I'm tempted to test them out. So the tool I created last week was your 10x Habit Builder. I just created that to support an existing patent because you have a three-month window. If you get a patent, you can support it with new patents. And those new patents take on patent status the moment they're approved. OK, so I see us within a reasonable amount of time having 500 patents, probably assessed value at $2.5 million each patent. And it's just taking what we already have and turning it into assets. The other thing is, I have a goal that the entire community, you know, and it was in the writings yesterday, Lior, you saw it, that by the time I'm 100, which is 20 years down the road, the entire value, IP value of the Strategic Coach Free Zone community, is $15 trillion or above, but we indicated in the exercise yesterday it might be a lot larger. And that's it. It's what we do right now and what the result is 20 years down the road. And that's it. And then how do we do that in a very, very effective way that preserves the culture?
Lior Weinstein: Yeah, I guess in those contexts, Steve, by the way, for you or for your group, if somebody's spending billions of dollars on technology, I can probably make them spend half and make it twice as fast across the board. I've yet to see a situation where that statement is not true. Obviously it can be, but most people just over-engineer, overthink. They don't have a good process to manage these things. And because of that, they trust the wrong people, not from a level and standpoint. It's just like they're not choosing the right thing for the job, right? Right person, right process. Easy. And I've done that many times. And those are usually easy avenues for me to come in and not just help and be effective, but then learn about the joint venture opportunity down the line. I'm a very relationship kind of guy. Some of the JVs I have, these are people I've helped for a decade straight. Not asking for a penny. And then suddenly we realize, oh, here's the combination lock. Here's what this unlocks and now let's do it. So I'm not trying to transact in that way. Like, oh, let's talk and see if there's a JV. That's not the mindset. I'm like, what's the problem we can solve? And then if there is a JV, then great. But if there isn't, maybe it's a free help, which is great. Maybe it's a paid help because, oh, you're spending 10 million, you would like to spend five, or you're spending 20 and I think you should spend three, because of not just making it cheaper, but just making different things, right? Like if I was the CTO of Coach, for example, it's called that, right? Because Coach has great marketing, great sales, and technology is not leveraged to the point that it could be. Like one of the conversations then Babs and I had, my last year, I told him the first quarter came in after ChatGPT came out, and I told Babs, you know, I really see a future where, like books, you now have audiobook rights and Kindle book rights and so on and so forth. You're going to have a chatbot, right, for the book. And I don't see a reason why any of Dan's quarterly books cannot have a chatbot with them, just like they have the audio pairs, the video, the PDFs and so on. And I actually was on a call with Dan and I showed him live. I'm like, hey, let's open, I think it was like Cloud or something. Let's open it up. Let's upload a PDF. Let's give it a prompt. and see how it is and it was pretty dang good as something that happened in a four-minute MVP, right? Did you say pretty dang good or pretty darn good?
Dan Sullivan: Pretty dang good.
Lior Weinstein: I like that. Dang good. The reason why I decided to do a fractional CTO accelerator and not another position is because CTO is one of these things that pretty much any company could have, but it doesn't make sense for most companies to afford that full time as a role. But having a strategic executives that know how to leverage technology to grow or to save money is a big deal. Big deal. There's a lot of opportunity there.
Dan Sullivan: Yeah. Yeah. The one thing that people don't understand is why we have so many staff. They said, you know, we could do what you do with half the staff. And I said, because one of our ten times is to increase the amount of personal connection that we have with our clients. So the big thing is that you have as many people front stage in your company as possible who are interacting on a continual basis with your customers. I made a statement, I think it was at dinner last night, some of us went over to the restaurant next to the workshop and I said, I don't think you can spend too much on value added. I just don't think you can spend too much on value added. And there was a recent conference where our team was, and they were charging large amounts of money for the conference, but they didn't feed the sponsors. And the sponsors were paying a lot to be there. We were paying a lot to be there, and they didn't feed the sponsors. Our clients were there, the clients were at the conference, and their takeaway from the entire conference is that they paid a lot for the conference, but they didn't feed the sponsors. That would never happen at Coach. That will not happen at CoachCon in Nashville. The sponsors get everything the paying clients get.
Lior Weinstein: In the Free Zone annual, we had an AI panel, right? And I spent about two minutes showing, hey, here are the tools that I'm using and it's cool and it's great. But then I spend my last five minutes talking about artificial intimacy. And I think that's the biggest risk and opportunity in AI. That's one of the first thing I think, Dan, you shared with the, the Four Seasons quote, with the systemize the predictable and humanize the exceptional. And a lot of people are using AI and removing humanity from their process. You know, it's the doorman's effect, right? You think, oh, there's a hotel with a doorman. Let's just replace it with a door sensor. It's going to open 24-7, 100% of the time, and we'll save all this money. And you forget, it's just called the doorman because he's at the door, but he's doing 50 other things that are not in the job description.
Dan Sullivan: Yeah, or it can be analyzed, actually. That's right.
Lior Weinstein: And I think one of the bigger challenges across the board, AI and artificial intimacy, companies using these tools, and we were just talking about that yesterday then, right? About humans are starting to get an intuition when something is AI generated or not. It's little things and most people can't articulate them, but they see that this is not actually what a human would say or talk or how a human would say or talk about it. And same thing for images. You see, oh, this is probably Midjourney. It's probably, you know, generated by AI as opposed to a photograph and so on. Now it'll get better, but still there's a difference between a hundred percent and 99.9. There's a real difference in the human ear and the human eyes are very sensitive to these things. And I think to your point, the wrong application of technology or like somebody coming in strategically to Coach and say, oh, let's do the same customer service, same account management with half the people. That's not even the right starting point. That's not even the problem to look at. First of all, we need to think about where the company wants to be in 10 years or five years. And do we have the system to do that?
Dan Sullivan: That's where we want the company to be always. Always and then expand.
Lior Weinstein: Yeah. And then do we have the system to do that? And then what is the thing that we should never AI? Never. And when I say never AI, I mean never have AI replaced. I think in all areas, it makes 100% sense for AI to augment. 100%. I mean, the more technology gets better to where we get this Iron Man capability of everything we look at, we can have some digital insight from the World Wide Web, is incredible, but that's still saying, you know, one of our core values is human connection with our entrepreneurs. So always have a human connection. Don't try to replace it with a chatbot, even if it's a great chatbot. Don't try to replace it with a chatbot. But when a person is on the other line talking to the entrepreneur, absolutely use AI tools to give them the quick snapshot of what's the latest news of the entrepreneur's company, right? Or a quick reference. Oh, you're speaking to him right now in live, real time. Remember three quarters ago, he also said this. You know, something to tee up for the human to be human. That makes perfect sense. But I think most of the mistake that people do on the mental models of AI right now is replacement. Replacing humans is incredibly difficult. It's like autonomous driving. The difference between L4 and L5 is decades in the ability to do that.
Dan Sullivan: Yeah, great pleasure, Lior.
Steve Krein: Yeah, really interesting. I'm looking forward to the cutting up of the episodes. I think this second half of AI conversation will be really interesting for people out there as well.
Dan Sullivan: Anyway, a real pleasure. What did you learn, Lior?
Lior Weinstein: I think by far the crystallization around connecting to the vision and not having the constraints. And that's why the simplification is just there, because I didn't learn the complex way. Like I said, I didn't learn how to do it slow or I didn't learn how to overcomplicate it. It was a really great insight for me.
Dan Sullivan: Yeah, I have a tool that I'm creating in, I think it was Motorola. I don't know who the originator was, Six Sigma. You know, I remember the early literature. I think it came out in the ‘70s of Six Sigma. The whole point of it was to increase defects in manufacturing. But the big thing I do, go big or go home. You know, there's always this phrase, these various sketch phrases, and you know, I'd be home really quick in that phrase. But the big thing I came up with, people say, well, this has got the possibility of a million customers. And I said, well, that's really good. A million customers would really be good. But does it even work for one person? So I spend a lot of time, does it even work for one person? And if it works for one person, then I know I have 50% of what's needed to know how it works for 10 people. And if I have 10 people, I know 50% of what it might take to do 100 people. And I just keep working in orders of magnitude. But when you get there, you only know 50% of what it takes to get to the next order of magnitude. And I think that'd be a neat tool for people, because a lot of people fall in love with big right off the bat, and then they're always in The Gap that they're not at big, where you might as well give yourself a lot of rewards along the way.
Steve Krein: Inspired by your flexibility as a individual doing really great teamwork with other people. I think it's, it's refreshing. I was surprised but pleasantly about how you've kind of thought about being a one man show with multiple opportunities to have multiplier opportunities with good teamwork. That's an interesting flexibility and agility you have. In this world today, it's possible. I think it would have been very difficult to do five or 10 years ago because you can leverage a lot of the key learnings and I think this AI discussion in the end was an important part of that.
Lior Weinstein: Wonderful. It's been a pleasure.
Steve Krein: Thank you for having me. Thanks for staying up. I know this is a long, long, long extended timeline for you given your travel, so appreciate it.
Lior Weinstein: My body is still 15 hours away from where it is right now. All right.
Steve Krein: Take care. Thanks, Lior.
Lior Weinstein: Thank you.
Dan Sullivan: Thanks, Lior.
Lior Weinstein: Thanks, Dan.