The Meaning of Money

Chapter Eight

The Amplifier

Rudi Adigbli on why neither capital nor technology can supply what it magnifies

Featuring

Rudi Adigbli

Founder, ReeWire Ventures; Host, The ReeThink Podcast

reewire.vc

August 4, 2026Episode 08 · 30 Min

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Welcome back everybody to The Meaning of Money podcast. We've got a really great guest joining us today, Rudy from Rethink podcast. I'm going to introduce him in a second, but first just a quick reminder that The Meaning of Money is a live show for founders, investors, and families who have already made money and are now focused on what wealth should make possible. We like to explore what comes after financial success, things like freedom, family, purpose, investing, and of course, legacy. And I'm really excited here today, in the tradition of bringing together people from around the world. Today, Rudy joins us from Switzerland. Rudy is the founder of Rewire Ventures and the host of Rethink podcast. Rewire Ventures operates an integrated ecosystem that is designed to generate insight, build trust, and de-risk investment in the convergence that we're seeing between technology and neuroscience. So I'm looking forward to, no pun intended, picking your brain. Welcome, Rudy. Thank you, Stefan, so much for this opportunity and for having me. Great introduction. In particular, I was thinking about the theme of your podcast, and I was thinking that Switzerland is quite a fitting country for that, because we find a lot of people and families, in particular, after they made their money and their wealth, that came to Switzerland and enjoyed a good life. So I've got a question for you on that, and this is one of the fun things about the show, I've been able to bring people together from around the world, and not surprisingly, there are different points of view in terms of how to think about money and how people invest that money. I was speaking to one person, actually also a venture capitalist in Europe, a different part of Europe, not in Switzerland, the other day. And he mentioned that one of the things he finds interesting is that in the US, when there are big exits, you tend to see a lot of people reinvesting back into new ventures, starting their second or third or fourth business. He said in his country, and I think he was referencing Italy in particular, a lot of people, when they've built extraordinary wealth, tend to just hold on to it and put it in things like real estate and very conservative assets. Which on the one hand is good; on the other hand, he worries that there's an underinvestment going on in terms of the new generation, new technologies, new ways of doing things that is needed to help all economies continue to evolve and stay vibrant. Where does Switzerland fall in that mix?

Switzerland's missing capital layer

Oh my God, I love this question in particular, because I think this is one of the things where I believe Switzerland has to view the US from a different light. Maybe to unpack this, because it's a quite difficult answer with different layers. In particular, I can tell you the Swiss mentality is very similar to the one from Italy. What you see, it's improving, but what you see often is that people tend to build companies which sustain or create their wealth, and they have this company over the next maybe 50 or 200 years. So you have a lot of families that come from generational wealth. And then you have the new money, the classical entrepreneurial stories with an exit. And funny enough, you also see, in particular if it is a really big exit, that they either join a multifamily office or they build their own family office, also depending on the exit amount, of course. What you see in particular, referencing the established families, is that their investment appetite is very much de-risking. In that sense, you don't see exactly what you mentioned, a lot of reinvestment happening after a big exit. And this is very interesting, because we have a couple of different things going on which are not particularly aligned. So for instance, Switzerland tends to be very, very innovative. We are the country of the hidden leaders; we have a lot of companies that are not that famous, but they are leading in certain aspects of the industry, and we have a lot of patents and all these different things. And for such a small country, we have a lot of Fortune 500 companies that stem from Switzerland. But nevertheless, what we have in particular is this missing capital layer for startups and these more risk-driven ventures that we are still missing. The good thing is, people are realizing that, and there are efforts to alleviate that. One effort, for instance, and that's fairly new, is that pension funds have the possibility to access venture capital as an asset class. And this is something that, like in the US, is coming. Is that new in Switzerland? It's very new. And you have to imagine the implementation of that, because I was in contact with one of these consortiums that try to enable that. It's almost like it's the wrong people doing this, because you have to imagine, they're saying all the right things, they made the right analysis, they understand the mechanism, but when it comes to application, these are not the people that understand that when you do an investment in startups, these are inherently risky things. That's why you have risk-adjusted returns eventually. But it seems they don't understand it. It is almost like a cultural thing, in particular in Switzerland, to always play safe.

Bottom-up energy versus the old dogs

So a question for you. You mentioned there are some things that are slowly beginning to change, an awareness that this needs to happen. Is that being driven from the bottom up, from the younger generation? Or are you seeing an awakening in the old dogs, and these guys starting to realize it's important and driving it? Yeah, I think it's both. The innovation is still there, the hunger is still there, or is rising, and you see more startups. Venture capital as an asset class is on the rise. And also, from the institutional side, things are moving, but not as fast as the US. For instance, they have this vision for 2030 of Switzerland, that they want to be a unicorn factory. And one of these particular measures is to pour more money into early-stage investment. Because with late-stage investment, you don't have a big problem finding money in Switzerland, but it's early-stage investment. So, as I said, the old dogs see it as well, but the movement and the implementation is poor. On the other hand, what you still see, that is very preferred, is things like the classical private-equity cases, where you have a cash-flow business that will be bought and then later eventually sold. So they tend to avoid the riskier ones. But I don't understand it, because there's so much wealth here. I think we could just own specific industries if we wanted to, because the money is there.

AI and the two-person company

So what about AI in that context? One of the arguments that I heard made the other day was that money used to be a barrier to creating new companies. I was interviewing another venture capitalist, and he shared that they've got a portfolio company where, it's not indicative of his whole portfolio, it's kind of a standout example, but there are two guys that built a business that are generating tens of millions of dollars a year, and they have no employees. And in that context, the startup capital that's needed is human capital at the founder level, figuring out what business you need to start, who you want to target, how you add value for them. And with the benefit of agentic capabilities today, it unlocks paths that were not possible two years ago. Where does that fit into the picture here? Is Switzerland embracing agentic innovation at light speed, or what is it like on the ground there? Yeah, I think there are different pockets. Of course, everybody is embracing their version of AI. Although I believe, when we look at the corporate side of things, I don't think they really can implement it in a way that truly, let's say, tenfolds their productivity. However, exactly what you mentioned, what we are going to see more and more is that we have maybe two guys, one guy, building a company that usually needed maybe 200 employees. They do it with two and they generate the same kind of revenue. And also other things, like prototyping, all these different things that we're currently seeing, I think there is a huge step forward. And I also believe the algorithmic side, and the insights we can create, all these things are tenfolding, and we see that. However, there's also, for me at least, I can see the other side, that we are in a way in a bubble. Because on the one hand you have this tremendous productivity gain, but on the other hand there is also an index for automation and all these different things; AI is not perfect. And you have this super reality of AI, what it could be, and everybody is on the hype train of that, and then we have the actual reality, which is also amazing, but it comes with the caveat. And I think what we see is, yeah, maybe we can build things that used to need capital of, let's say, two million, and now it's 200K, but we had this always. We had it with software, we had it with everything else. I mean, if you use your iPhone and just have a look at the software suite, 20 years ago this would be maybe one million in just the software suite, and now it's your iPhone and you bought it for 1,000 Swiss francs, or in US dollars. So you see this transition happen either way, and we see that as well. So I see a lot of innovation come through, enabled by AI. And I think we have to look really from a grounded perspective of productivity gains; there will be breakthroughs all the time, but it's not as fancy and shiny as it sounds. Although the progression is rapid.

It all depends on the operator

Yeah, you mentioned that it's not perfect, and I smiled, because at the end of the day it's still human-run, and human operator error is a guarantee. Absolutely. And it's very much dependent on the operator, in my opinion. An F-16 in the hands of somebody that's an inexperienced pilot is going to be a very different plane being flown than in the hands of one of the most experienced pilots in the Air Force. Same tool, same environment, but very different outcomes. That's such a great example. I can give you even another example. And I think that's why I love the quote of Warren Buffett's business partner, I just lost the name for a minute, Charlie Munger. Charlie Munger says, show me the incentive, I'll show you an outcome. And with AI we have these two different realities. On the one hand, we have something like Copilot in the Microsoft Office Suite. And to be honest, if you think about the fact that they have a share in OpenAI, I think this version of AI is rather, from my perspective, and this is a hypothesis that I have, it doesn't mean it needs to be real, it's like you have something that is implemented to generate more generation of tokens, so they make money on the back end, right? And not that it's actually changing the world. And that's why I said, for instance, if a corporate is implementing AI, I believe most of the time it will not work. Because if something is not in the base layer and in the identity of a company, and you build the whole process and everything based on a new capability, it's always a layer on top, an afterthought. And if you have these huge corporations, you have all the people that have different agendas, they are not so aligned, and that's why I believe AI in corporates most of the time will not lead to the promises of an outcome that we are looking for. But for OpenAI, it's great. I'm glad you mentioned that, Rudy, because you did mention earlier that large corporates were not implementing it very much, and I was curious why not, and where the sticking points were. So your explanation right now makes a ton of sense. You've got to have a deeper mission that you're driving for, like what powers your efforts, in which case AI can become an amplifier. If you're just slapping it on as another tool without figuring out how to embrace it far deeper, in the spirit of what your mission is, then you're not going to achieve anywhere near its impact.

Client-driven versus self-serving: banks and Apple

Exactly. And I can give you an extreme visual example. Let's say Salesforce. Of course, on the product level, they have their AI layer, and it might have a good use case, I don't doubt that. However, now imagine we, you and me, Stefan, we say, okay, we can build something better as a competitor to Salesforce. I don't know the exact number of employees of Salesforce; it's probably 100K or whatever. And now we can build eventually the same as Salesforce, but from the ground up, with AI first in mind. And we probably build that software with maybe 10 people. And I think that's the difference. And that's why I believe in the corporate layer AI will not be successful, because there are so many different agendas and incentives working against achieving what AI potentially can achieve. But when you build something from the ground up. Well, from my perspective, Rudy, it's not necessarily ground up, but in my opinion it's about, is it client-driven or not? Because if you're building something that is designed to radically add value and make something so much more powerful for your user, with your user in mind at every single step of the way, you'll crush it. On the other hand, if, to your point, you're looking at this as a tool for you to do better for you, well, you know what, somebody may come along and invent a better mousetrap for the client, and then you're out of business. So for example, banks in the US are inherently antagonistic to their clients. The question they ask is, what is the lowest rate of interest I give Rudy while Rudy keeps his money at the bank with us? Or what is the highest rate of interest, the most money I could take from him on a loan and have him still do the loan with us? Which is inherently antagonistic. Whereas if you compare that to Apple, whom you were talking about a second ago, Apple's not the cheapest phone out there, but they focus day and night on, how do I add more value, how do I be useful, so that you'll buy it even if it's more expensive? And at some point they do that, and then you decide to upgrade. They're constantly going, how do we make it better for the client? And that is one reason why I think they've been very successful. And why banks today are still terribly, horribly slow and not innovative. When's the last time the banking sector has really come out with an extremely innovative product, or an innovative way to add value for clients? You ask somebody, they don't know. And so, to your point about large corporations and the Salesforces of the world, what I find is that everybody's feeling compelled today to come out with their own AI app. But from a customer standpoint, it's very rare that that app is truly designed to be transformational for you and to bring transformational benefits. It's just falling into the category of, we felt we had to do it, or make things a little bit better, but it's not transformational. And then it's rolled out to be, like, this transformational thing, and it's not. And that kills authenticity with the users. I remember there's an app that we use for a very specific purpose, and I was in the middle of a billing negotiation with them, because they were trying to jack up rates for the next year. And I was like, whoa, whoa, whoa, why? And they're like, well, we came out with two amazing AI-driven apps that are just incredible. And I'm like, well, I don't know anything about them, I don't use them, haven't used them once, they don't add any value to me. And so you're using that to try to raise fees on me? That's a hollow argument. But in their minds, they're like, oh wow, we're doing something so cool, we're doing AI. It's like they had forgotten how we use their product, how they really add value, and they haven't done anything to change that. And that's where I think big companies are going to get in big trouble. Because a lot of companies are coming along with leaner versions of something similar that might be a lot less money, might actually solve a problem in a better way for them. And I think incumbents need to watch out. It's not so much about AI, AI might be a catalyst out there, but everybody in business has got to be worrying about, how do we add more value for clients? Because that changes and evolves every year. And to your point, it's not a new, what was it, Schumpeter, that said creative destruction? It's not a new concept, even if AI is the tool of the moment. So it's an interesting debate. And I say debate because I think a lot of big companies are debating internally, what the heck do we do with this? The funny thing is, everybody rolled it out, right? And then suddenly their token usage cost went crazy, and now they're like, well, maybe we shouldn't give it to clients. And it's almost like they did it without any thought to ROI. Exactly. And I don't mean just financial ROI, but return on investment to the client that has to learn something new, that has to make an adjustment because you're changing how you do things. And I just think a lot of big companies forget to do that, because there's so much money coming in right now that they must be right.

Where the hype really comes from

And I feel like you're touching on something very profound. I feel like a lot of people are struggling with this. There are fundamentals that are not changing. Because when you make a model of the world, you always have to consider what are the constants and what are the things that are evolving or changing, and what are the variables. And I think one of the things, that's why these hypes get created, and I have an idea where the hypes come from. The hypes come from the AI companies, because from their perspective, whenever they can sell you something and you use the token, they're making money, right? So they have this position of inflating their value in that sense. And of course, in order to create all these mechanisms and institutes and everything, you have to create a compelling narrative. And to a certain extent, we are always in one narrative, right? But then we have humans, we are a constant. We are very predictable in our behaviors. And that's the reason why, when a new technology emerges, of course the vision of it and the potential are clearly there, but the way it transpires is totally different from what we anticipate. Not because the vision is not fulfilled, it's because of what you mentioned before. The downside of having so much productivity means that I can do more nonsense as well. It's not that you can create all of a sudden more useful things; you can create nonsense as well. And you know who doesn't care whether you create nonsense or a super app? Of course, the companies that create the infrastructure for the AI companies, and the AI companies themselves. So coming back to the fundamental question, which is what you mentioned: what is it we are trying to build? Is this adding value, and how can we leverage this technology to add value, and add value for ourselves too? I think this is always the end result of everything, and this is the thing that will change eventually. Of course, technology is the amplifier, it's the tool. But it feels like it's the opposite way around. It's almost like, oh, we have this new technology, so now everything is going to be solved. It's always backwards thinking. But of course, as a narrative, it's easier to sell something that magically solves all problems, right?

The line versus the circle

Yeah. So, really interesting. Another reason I think big companies ought to be scared, that we haven't talked about at all, is engineering loops. In my opinion, what Claude and ChatGPT, where they're really excelling more than anybody even begins to appreciate, is what they're learning. Think about everything they are learning. Every time, they are being paid to learn. Absolutely. And they are learning so much about you and me and everybody that uses those tools. And what ought to scare the big companies that are not using it in a smart way, the 100,000-person companies, is that if you look at their business model and the way that they're planning, AI does not involve radically accelerated loop engineering to make sure that you're learning what is adding value for your clients, how your clients are using it, what they want, what they don't like. If you don't have that built in, your rate of evolution is going to be so slow compared to the rest of the new competitors and the infrastructure companies. That's what ought to scare people. And we're not hearing enough people explicitly focus on loops. They're more focused on the line, the linear measurement of efficiency and things like that, rather than, they're interested in the line, not the circle. Yeah. And I think that if your business model is based on a line and you don't have a fierce circle component to your business, you're in trouble.

What humans still do better than AI

Let me switch gears here a second. Last question on AI that I want to ask you before I ask you some more wealth-related questions. AI, done right, can do a huge number of things as well, often better than people can, especially if you compare what it can do today to, say, 20 years ago. It's just insane what it can do today, if done right. But you would probably agree with me: there are some things that people can still do better, or should do, not a computer. What are those? Oh, 100%. At the end of the day, and I always take the example of Bloom's taxonomy, the highest level of intelligence is to create something original. Of course, you can argue that agentic and generative AI can do that; I don't fully buy into that narrative. I think where AI is still amazingly great is having a lot of data and analyzing it and telling me what patterns are there. But when we move forward to ingenuity, and thinking about how to solve things creatively, we use AI as a tool that enables us and helps us; it's almost like you have the chance of a higher level of thinking. For instance, when you have 100 employees, you tend to focus more on the bigger questions, and your thinking is more high-level than in the details, right? And I think with AI it's very similar. For instance, I use AI, and you mentioned loops, I use it to help me learn better by engaging myself. Because I know that, and this is something inherently human, we are really good, or we are addicted, when we have direct feedback and we cannot anticipate what reward we get. This is something that makes it addictive, and that's why social media is ramping. But you can use the same mechanism, for instance, in my case I use it for summarizing the books I have read. It's more engaging if I just ride with my AI. So, hey, look, this is the book I have read, use the table of contents and match it with the live content you find on YouTube, in order to have a summary of the content; and I make a summary of what I have learned and match it, and tell me whenever there's a gap, challenge me on that, so I can improve my learning. And these are the things, you see, I am the one creating these scenarios. I want to get you back on path here, Rudy, because while I want to explore how you use it, I want to know at a very high level: what are the things today that people can do, and do better than AI? Human beings, what is still human, what do we still do better? You argue maybe creativity, the new is not being born. What else? Where else are we still better? Engaging with other humans, 100%. Engaging with other humans. And there's also something, maybe this goes more into esoteric thinking, but I think intuition is a big factor. When you look at the biggest scientists, the biggest thinkers in the world, they always led with intuition, and that brought them to things we are still using today. So I still think that's something that is unmatched. I love that. So intuition, creativity, and connection with other human beings. Yes.

What wealth can and can't solve

Love that. So, one last question here. You live in a country that's full of wealth. Tell me, where do you see wealth most effective at solving problems and fulfilling the promise of money being great for what money is? And where have you seen examples of human problems that money doesn't solve? That's a really good question. I think for me, what wealth does is it enables two things: time and leverage. And time is ultimately the most important resource we have. And leverage is the rate of how fast you can implement things and the resources you can accumulate. I think money helped with that. However, and maybe that's the other thing, money is a function of something that you receive by being resourceful. And that's why you see people with a lot of money, maybe they have inherited it, that it doesn't lead ultimately to success. You cannot use money to solve the problem of generating money, in a way. And the other thing where I think it's not directly helpful, although it might have an impact, is whenever it's your health. Of course, you can get the best treatment, but when you have something so severe that your body has stopped working, then no amount of money will solve that problem. So that's why I believe we should see wealth as also something that is beyond money. Health, you're saying. Yes. Yeah, that's a good point. From a different perspective, I would say that true wealth is lived at the intersection of health, wealth, and purpose. And to your point, if you have a lot of money but your health is terrible, you're not going to enjoy it as much. So that's an interesting thing to understand, because a lot of people, when they're in the pursuit of money, are so focused on that goal, okay, boom, I get an exit, now I have it, but then two decades of ignoring your health, and then you realize, wow, you have all the money, but you can't really enjoy it to the level that maybe you would have liked to, because you're dealing with all kinds of deeper health issues. I would even add something, and that's qualia. Because what I have seen now, at this level where I am, I have a lot of super successful friends, like really successful, money-wise. But one thing that I started to see more and more, and it touches on what you mentioned before, is the quality of the experience. And this is something that is really, this is not solved by money, it's not solved by success. This is something I would attribute to your consciousness: that you enjoy this experience. I know so many people, super successful, and you think they are enjoying life, but they are not. And the funny thing is, that's something that can be cultivated by everybody. And that's something I don't think any amount of money can fix. Because when you have everything and you are miserable because you don't have the biggest jet, then it's something fundamentally in your consciousness that is not working. And I still think that I would pity you, because from my imagination, from my consciousness, my box of thinking and my way of relating, how narrow would your field of reference be that something like that would bother you? Yeah, and it could be about anything, right? But it's just internal anxiety. There's a lot of internal anxiety that people of all wealth levels today still carry. And I think that's important for people to invest their time and energy into, because there's no investment in the world that'll make your anxiety go away. Even if you have perfect health and a lot of money, if you don't have clarity as to who you are, why you're here, what you're meant to be doing, how you're contributing, there's going to be a hole in your psyche, and a hole can't be filled with stuff. It can only be filled internally, through spirit. And the solutions and the exercises and the work to be done inside, you can't buy a few extra tokens and skip the work. That's the heavy lifting that we human beings still have to do. So, Rudy, it is so good to connect with you. I didn't get to tap into one-tenth, or even one-hundredth, of some of the other things that we've talked about offline, tapping into your study of the human mind and neurology, and I look forward to staying in touch and exploring those subjects in the years ahead. Thank you for making time today. It's been really great. Thanks for having me. I had so much fun talking to you. And as you mentioned, we had our conversation before and I enjoyed that as well. So it's always a pleasure talking to you, Stefan. Thank you so much, Rudy. You're welcome.

Transcript edited for readability from the video. Machine-transcribed; may contain minor errors.

Key Takeaways

A written companion to the episode, written for those who prefer to read.

Switzerland is where the world's money goes to rest. Rudi Adigbli says so himself, and with affection: a great many people and families, once they have made their fortunes, head for Switzerland and enjoy the good life. It is a country organized around the preservation of what has already been won. Which makes it an unusually clean laboratory for the question this book keeps circling. Once wealth arrives, what does it actually do? Adigbli, who spends his working life at the intersection of neuroscience and technology, has an answer that is more unsettling than it first sounds. Money does not create outcomes. It multiplies them. And a multiplier cannot supply the thing it multiplies.

Adigbli is the founder of ReeWire Ventures and the host of the ReeThink Podcast. ReeWire operates an integrated ecosystem designed to generate insight, build trust, and de-risk investment in the convergence between technology and neuroscience. He joined Stefan Whitwell from Switzerland, and the conversation that followed ranged from Swiss capital formation to artificial intelligence to the interior condition of very successful people who are not, in fact, enjoying their lives. It sounds like three subjects. It is one.

The country of hidden leaders

Whitwell opened with an observation he had collected from another investor in Europe. In the United States, a big exit tends to recycle. Founders take the money and start a second business, then a third, then a fourth. Elsewhere, and Italy was the example given, extraordinary wealth tends to settle: into real estate, into conservative assets, into the safety of preservation. Good for the family, perhaps. Worrying for the economy, which needs someone to fund the next generation of technologies and ideas. Where, Whitwell wanted to know, does Switzerland sit in that mix?

Squarely with Italy, Adigbli said, though the picture has layers. Swiss wealth divides roughly into two kinds. There are the generational families whose companies have sustained them for fifty or two hundred years. And there is new money, the classic entrepreneurial story with an exit at the end, after which the founder typically joins a multifamily office or builds one of their own, depending on the size of the outcome. Among the established families in particular, the investment appetite runs almost entirely toward de-risking. The American reflex to redeploy into something new is largely absent.

What makes this strange is that Switzerland is anything but stagnant. Adigbli calls it the country of hidden leaders: a small nation carrying an outsized number of patents, an unusual concentration of Fortune 500 companies, and a long roster of firms that almost nobody has heard of and that quietly lead their corner of an industry. The innovation is real. The hunger, he says, is still there, and rising. What is missing is a capital layer. Late-stage money is not hard to find in Switzerland. Early-stage money, the capital that carries genuine risk, remains scarce.

Efforts are underway. Pension funds have recently been permitted to treat venture capital as an asset class, part of a stated ambition to turn the country into a unicorn factory. Adigbli has been in contact with one of the consortiums working on implementation, and his assessment is blunt in a way that is worth sitting with. They say all the right things. They have done the right analysis. They understand the mechanism. But when it comes to application, these are not people who understand that an investment in startups is inherently risky, which is precisely why the returns are risk-adjusted in the first place. The vision is correct and the execution is poor, because the instinct underneath it, in his words, is a cultural one: always play it safe. The capital is there. The permission has been granted. What has not changed is the disposition of the people holding it.

This is the pattern in miniature, and it will repeat.

A layer on top

The conversation moved to artificial intelligence, and Adigbli made the same argument in a different key. Everyone is embracing their version of AI. Very few corporates, in his view, will get anything like the promised return from it. His explanation borrows from Charlie Munger, whom he cites with obvious pleasure: show me the incentive, and I will show you the outcome.

Consider who benefits from the current enthusiasm. The companies selling inference earn revenue every time a token is generated, which means their incentive is volume, not transformation. Now consider the buyer. If a capability is not in the base layer, in the identity of a company, and the entire process and structure were built without it, then the capability arrives as a layer on top, an afterthought. Add to that a large organization full of competing agendas and imperfectly aligned interests, and the outcome is close to predetermined. The tool is genuinely powerful. The organization is not shaped to receive it.

He offers a thought experiment. Salesforce has an AI layer in its product, and it may well have good use cases. But imagine building a competitor from the ground up with AI assumed from the first line of code. That team might be ten people. The incumbent has something on the order of a hundred thousand. The asymmetry is not about talent. It is about what sits in the foundation versus what got bolted to the roof.

The line and the circle

Whitwell pushed the frame somewhere more useful. The distinction that matters, he suggested, is not ground-up versus incumbent. It is client-driven versus self-driven. Build something designed to add radical value for the person using it, with that person in mind at every step, and you will win. Build a tool that mainly serves you, and someone will eventually arrive with a better answer for your customer, and you will be out of business.

His illustration was banking. The questions a bank asks are structurally antagonistic to the client: what is the lowest rate of interest I can pay and still keep the deposit, what is the highest rate I can charge and still write the loan. Set that beside Apple, which is not the cheapest phone on the market and never has been, and which spends its days asking how to make the product more valuable and more useful so that a customer will choose it anyway. Whitwell's challenge lands: when was the last time the banking sector produced something genuinely innovative for its clients? Most people cannot name one.

The same hollowness now shows up everywhere. Whitwell described a vendor mid-negotiation attempting to justify a price increase by pointing to two remarkable new AI applications. He had never used them. They added nothing to his experience of the product. The company had built something impressive to itself and forgotten how its customers actually derived value. That gap, announced as transformation and experienced as noise, is what kills authenticity with users.

Then Whitwell named the thing that should frighten large incumbents most, and it is not the technology itself. It is the loop. The frontier model companies are being paid to learn, continuously, about how people work and what they need. A business whose implementation of AI does not include radically accelerated learning loops, mechanisms that reveal what is adding value for clients, how they are using it, what they want and what they do not, will simply evolve too slowly to matter. Most executives, he observed, are focused on the line: linear measures of efficiency. They are interested in the line, not the circle. Adigbli finished the thought. If your business model is a line and there is no fierce circular component to it, you are in trouble.

Constants and variables

Underneath all of this sits a discipline Adigbli returns to repeatedly, and it is the intellectual core of the conversation. When you build a model of the world, you must be rigorous about which things are constant and which are variables. Most people get this backwards, which is exactly how hypes are manufactured.

Technology is the variable. Human beings are the constant. We are, he notes, remarkably predictable in our behavior. So when a new technology emerges, the vision and the potential are usually real, and the way it actually transpires is almost always different from what anyone anticipated. Not because the vision failed, but because human incentives were in the room the whole time.

He is careful not to be a skeptic about the technology. He believes the productivity gains are real, that the algorithmic analysis and insight generation are genuinely tenfold, that prototyping and a hundred other things have moved forward dramatically. What he resists is the collapse of the gap between what the technology could be and what it currently is. And he names the cost of abundance with unusual clarity: more capacity to produce does not mean more capacity to produce things worth producing. The same leverage that lets one person build something remarkable lets another generate noise at scale. The infrastructure providers are indifferent to which one you choose.

He also punctures the novelty. Yes, something that once required two million in capital might now require two hundred thousand. But that has always been true. It was true of software. Look at the suite of applications on a phone and price what that would have cost twenty years ago. The direction of travel is old news. Only the slope has changed.

Whitwell offered the image that stuck. Artificial intelligence remains human-run, and operator error is a guarantee. An F-16 in the hands of an inexperienced pilot is a fundamentally different aircraft than the same jet flown by one of the most experienced pilots in the air force. Same tool. Same sky. Entirely different outcome.

What is still ours

If the machine is an amplifier, what does it amplify, and what can it never originate? Whitwell pressed the question hard, and twice, because it is the one that matters.

Adigbli reached for Bloom's taxonomy. At the top of it sits the creation of something original. He concedes the argument that generative systems can do this, and he does not buy it. Where the technology is extraordinary is in holding enormous quantities of data and telling you what patterns live inside it. Where it thins out is ingenuity, the creative resolution of a problem nobody has framed yet.

Pressed for what else remains distinctly human, he named two more. Engagement with other human beings, without hesitation. And then, with a caveat that it edges toward the esoteric, intuition. When you look at the biggest scientists and the biggest thinkers in history, he said, they always led with intuition, and it carried them to things we are still using today. He considers that unmatched.

Creativity, intuition, and connection. Three capacities that no amount of leverage will manufacture for a person who has not cultivated them.

Time and leverage

Which brings the conversation to money, and to Whitwell's central question: where is wealth most effective at solving human problems, and where does it simply fail?

Adigbli's answer to the first half is precise. Wealth enables two things: time and leverage. Time is ultimately the most important resource anyone has. Leverage is the rate at which you can implement things and accumulate the resources to do so. Money helps enormously with both.

But he immediately reframes what money is, and the reframe is the sentence to underline. Money, he says, is a function of something you receive by being resourceful. It is downstream. It is evidence of a capacity, not the capacity itself. Which is why inherited money so often fails to produce anything, and why you cannot use money to solve the problem of generating money. The resourcefulness came first. The capital is its residue.

The quality of the experience

Then he named the two places money cannot reach.

The first is health. You can buy the best treatment available, and when the body has genuinely stopped working, no amount of money will solve that problem. Whitwell agreed and extended it into the philosophy that runs through this entire book: true wealth is lived at the intersection of health, financial wealth, and purpose. Two decades of ignoring the first while pursuing the second produces a person who has the exit and cannot enjoy it.

The second is harder to see, and Adigbli raised it himself. At his current altitude he knows a great many people who are extraordinarily successful in financial terms. What he has begun to notice is the quality of their experience. He knows many people, he said, whom you would assume are enjoying life, and they are not. Money did not solve it. Success did not solve it. He locates the problem in consciousness, in the cultivated capacity to actually inhabit an experience, and he points out the thing that ought to be liberating about it: that capacity is available to everyone, at any level of wealth. When someone who has everything is made miserable by not having the biggest job, the trouble is not in the portfolio. It is in the narrowness of the frame of reference.

Whitwell brought it home. The anxiety is not a function of the balance sheet, and people at every wealth level carry it. There is no investment in the world that makes anxiety go away. Perfect health and substantial money still leave a person hollow if they lack clarity about who they are, why they are here, and how they are contributing. That hole cannot be filled with things. The work is interior, and there is no way to buy a few extra tokens and skip it.

The heavy lifting

The through-line of the conversation is a single structural insight applied three times. Swiss capital did not become adventurous when the rules permitted it, because the disposition underneath had not changed. Corporate AI does not transform companies whose foundations were laid without it, because a tool bolted on top amplifies the organization that already exists. And wealth does not produce a good life, because it multiplies the life a person is already living.

In each case the amplifier is real and powerful, and in each case it delivers exactly what was fed into it. This is why the questions that matter are the ones that come before the leverage arrives. What are you actually trying to build? Whom is it for? Are you learning in circles or measuring in lines? Have you cultivated the capacity to enjoy the thing you are working so hard to obtain?

Adigbli's answer to what money made possible is disarmingly simple, and it stops short of promising anything else: time, and leverage. What a person does with those, and whether they are able to experience any of it, is the heavy lifting that human beings still have to do themselves.