A (3:49)

You, you mentioned one of your rules, don't die in venture. Oftentimes it's only three to six months every decade where investors make the crazy returns. And there's really only two models there. One is you could pick those correctly, which is incredibly difficult, if not impossible. Two is you could be there for a Decade, that's the hard part. Being there for a decade, being there for 20 years and continually to be consistent so that you get that asymmetry in the market when things get better.

B (4:16)

Yeah, this business is not meant to be like smooth. Right. You're building up your deal flow, you're building up your backlog, your pipeline, your credibility, your friends, you know, your employee base. And then when, when the good things happen, the tidal wave of business, the tidal wave of profits comes. That's what we're seeing. That's what others I think are hopefully seeing. But, but that's kind of what it's been for us. I mean there's been, you know, sort of slower periods and busier periods, but you kind of been around long enough, you know, that the big, big wins are going to come. And so that's what's happening now. And, and I see that over the next year, I think our backlog as we publicize, it's at least 2, $3 billion of revenue of like signed clients that if they did their deal tomorrow be billions of dollars of revenue. So we've never had that in the history of the firm. So you know, it's, it's a, it's a good time to be infantech.

A (5:05)

How would you differentiate your talent strategy versus the Morgan Stanley's at Goldman Sachs?

B (5:09)

Our world is more the people that don't want to work at the big banks. Right. Sort of like how do you differentiate Sequoia employees from, you know, Goldman Sachs? If you are really good at what you do and you're the best, you want to go off and do it on a smaller platform and you know, prove to yourself, prove to the world that you can do things better than the big platform. So you know, how does a 200 person, 250 person firm beat Goldman Sachs? Morning. Steady JP Morgan. All the time. It's a teamwork in the elite team that we have and the results, it's all in a, results driven, you know, we're, we're very results driven place and you know, we kind of figured, you know, whatever the big banks are doing, we need to do something differently. Right. So that's the whole reason I left Goldman Sachs, you know, was I just didn't see the kind of work getting done that I would do for myself if I was a client. Right. So you know, we started doing things very differently from, from day one and we doubled down on that over the course of time and, and our team needs to kind of understand that a lot of times what we've hired People from big banks and occasions. Why are you guys doing 500 page decks or five 100 page decks for a company? And why are the models so deep and so detailed and so long dated? And why are you guys, you know, paying McKinsey a million dollars out of your own pocket? Why did you develop a data science team? Why do you have sort of a mini McKinsey inside the firm? Why, you know, why, why, why you doing all this extra stuff? All you have to do is throw, you know, a 40 page deck together and start working. And I'm like, that's just not the right way to do it, you know, so we're, we're, you know, we're throwing a lot of money at the team, a lot of money at innovating things in this space. So we've always been an innovator and the way we do these isn't public yet, although it might be about the time this podcast goes out. But we just invested $25 million in a company that's basically the leader in AI for financial services and investment banking. So company called Model ML. So we were the lead investor in a $75 million round that many of the Silicon Valley elite were trying to lead. So we broke in and took that lead role there. And so we're going to be AI, you know, all over the firm, whether that's looking for buyers, looking for investors, talking to investors, doing analytics, doing deeper data science work, using and applying AI to every single thing that we do as an investment bank and then giving that AI to our clients. So for example, right now it hasn't happened yet, but these AI tools can today and they will certainly tomorrow be ripping through thousands of documents and data rooms and financial spreadsheets and audits and historical legal documents and, and being able to basically tear all that down in a matter of minutes and create multi hundred page reports. So, you know, we're going to be arming our clients on the sell side with that kind of, you know, deal diligence and defensibility. So if someone's going to come and look at your data room, that 1500, you know, AI agents, you know, you better be prepared on your side to make sure you've done that work ahead of time. So, so yeah, $25 million back into the business, actually into Model ML for the support of our clients. And so, so we're just constantly adding many, many, many elements. Matter of fact, we just, we were in Vegas at Money20 20, had an amazing time there, and we decided to do our off site, you Know, a couple days before money 2020 and the theme was F1 racing. So it was kind of like, you know, we want to be like the fastest F1 team in the world. And it's not just the driver or the brand of the car, but it's all the people around the car, all the people around the brand, all the people around. If you're going to be better than everyone else in the world and getting better every single year, you need that elite team and you got to glorify and thank and love every single person on that team at F1. Yeah, sure, Max Verstappen's a guy in the car and he's great, but without the car, without the brand, without the team, he's sitting in a go kart, you know, on a little track somewhere. So I feel like we've got, you know, a great team, a great, you know, amount of innovation and everyone works together. Kind of like a proverbial F1 team. And, and we look, when you're in a big firm, you know, it just doesn't work that way. You don't have all those tools. If Goldman Sachs, if someone at Goldman Sachs said, or Morgan Stanley, JP Morgan, Bammel, whatever, said, hey, you know, FT's got that great data science team and they're like taking all the data cubes and running, you know, two days worth of analysis overnight to run their models and to prove out their, their clients data. You know, we should do that across all of our groups. They'd have to add a billion dollars of cost, you know, or something like that to get all these people on board. But then it's not going to do that. You know, someone said let's go hire a mini, let's go build a mini consulting group for every single niche within Goldman Sachs to provide that extra layer of service that would, they would never do that. Right. I remember when I was at Goldman Sachs, I even pitched my boss Peter Krause that we should go buy McKinsey. That didn't go over too well, but, but it would have been a great idea to some extent. So you know, that's always been in my mindset even from a young age to provide the best of the best service.

A (9:47)

And I guess there, there's two ways to look at traditional bulge bracket banks. One is that all the people are short term focused, focused on the deal over promising under delivering. But then there's also a second aspect of that which is the firms have no loyalty either. They'll pay you based on, not on future performance, not on Past performance but future performance, all these things that large banks have. Large banks are then incentivized quarter to quarter versus in the long term. So I'm still trying to wrap my hands around about how you created a different system because these are the default operating principles in banking. Why is FD partners different? What upstream decision did you make to make a difference?

B (10:25)

There's a few things I talk about which you have to new employees and their new team members and I think about every day. It's like we, we chose to be in a highly, in a high growth sector with companies that are largely not public, right. I mean there's a number of public companies obviously, but most of the market cap is in the private world. And these companies are generally high, growing. They're usually not at their full EBITDA margins. They're usually losing money or breaking even. They're, you know, changing their, their business, changing the business models every couple years. They're, you know, altering the landscape of financial services and they're hard to value. So what I figured out was that the skill set of being able to value properly and actually attain proper value for highly opaque assets is the, you know, best job in all of investment banking. Right? If you're at Goldman Sachs and I say Goldman Sachs Lexus because I work there and I vow respect for Goldman Sachs. But at the end of the day, if you're one of these big banks, you know, and you're working on, let's say an IPO, first of all, you're one of five or six or seven or eight firms working on the IPO. And second of all, you're one of maybe 50 people on the meat grinding process on the IPO just at one firm, right? You got the bankers ECM, you've got, you know, equity sales, equity research, you got back office, you've got, you know, stabilization people. And it's this whole entire process and it's very hard as an individual banker, as anyone on the team or even any one of the banks to sort of claim credit for. Oh, I was the one or our team was the one that added all the value, you know, to this, to this particular deal. As a matter of fact, you take a debt deal, it's like, is it really adding that much value to wire someone out $500 million, do a bunch of credit work and hope to get it back? Sure, that's value add. But it's like you're, you're giving someone $500 million and charging library, it's commoditized, it's somewhat commoditized, right? And then if you're working on very large, you know, M and A, it's generally seen as these companies typically trade it, you know, 25, 30% premium to market. That's the average over many, many, many deals. So you go in there, there's already 10, 20 owls covering the stock. So there's no mystery there. They've been public for how many years, how many quarters. Everyone knows that market premium is 25 or 35%. So if you get 25 or 35%, you're, you're basically doing an average shot, right? There's no, there's no glory in it. You add that much value, you got to be administering and processing the deal. If on the buy side, you know, you're not really creating a lot of value, you may be trying to compress value and maybe getting a deal of the hump, you know, but most of the time, you know, bankers are paid very little for the buy side because they're not really doing a lot of work. They don't really get in the weeds and understand the fundamentals of the company and decide is this going to be worth buying or not. They're doing more or less back of the envelope work to figure out whether the company might be worth X or Y and the increase might be worth A or B and, and might be, or B and so but it turns out all those things are like administrative roles, right? And, and you deserve to be paid administrative fees for administrative roles and like, like there's nothing wrong with that. Goldman Sachs, amazing place. They, they had a huge market share and same with Morgan Stanley. Mary. Nothing, nothing wrong with their model for the kind of deals that they do. But if you're a smaller elite firm and you can pick one or two things on earth to do, those will be capital raising and sell side M and A. In the private markets where valuations are highly opaque, the clients don't really know the buyers that well. They don't know the investors that well. And we can kind of be a network between the buyers, the investors and the companies and help get things done at in, in a high class way. Like I said before, another other even maybe your podcast like it's always about maximizing the value. It's finding the right fit. None of my clients wants to maximize, maximize value. They'd rather find a good partner and a quick deal that made sense for all sides. So that's actually even harder to do. It's actually fairly easy if you want to just maximize value. This one Function maximize value. You don't care who the buyer is. You don't care what the timing is. You don't care about anything. But when you're trying to think about, you know, speed and certainty and quality partner and what's the employees and you know, you want, you want the buyer to be happy with the transaction as well. So, you know, there's, or the investor for that matter. So it's, that matchmaking game is you can add an enormous amount of value in that equation and you know, you can get paid for that. Right? You know, we have a deal right now. We have a lot of our deals that are, you know, we get, you know, X percent up to say 500 million and Y percent above that and Z percent above that. And you know, we just got a, this is not public. I'll make it public here for you. But we just got $167 million fee on one transaction, which is the largest fee in the entire year. There's been two articles in the Wall Street Journal that Goldman Sachs got $110 million fee on this deal, the largest deal in the firm's history. And Merrill's got $137 million deal. And those were on like four, 40, $50 billion deals. Right. You know, or even bigger, quite frankly. I think the Bama was even a bigger fee on a big, small fee that was on a much, much larger deal. But we came in and we actually added billions of dollars of value to, you know, to a company. And, and so, you know, we got paid a, you know, a good fee for that. So, you know, we kind of figured out how to turn, you know, basically, you know, get paid on a value added model as opposed to administrative model. And that's really what we do. So it's a, it's a, you know, how do you get paid for adding value versus being an administrator of a transaction? And it's very similar to, you know, if you're, you know, managing Treasuries, you're not going to make as much money as Sequoia makes adding value to its portfolio companies. And it's, it's investors, LPs money. They're making 35% of everything over X par. Right? Because they're adding value to that X. Right? They're quadrupling that X. They should get 30, 35% of it. And I always say, why don't bankers get 10, 20, 30% of everything they get? They help achieve over a certain benchmark. And the reason is that bankers don't have any track record of doing so. In pebc, there's a perfect track record of who added value and who didn't. Right. You know exactly what your money mind returns. You know exactly your ROI is, you know exactly what your IRR is, I should say. And, and, and everyone knows it. It's completely 100% provable. There's not a banker on the planet that has anything like a track record of adding actual economic value. And we do. Right. Because that's the only thing that we're known for outside of fintech and selling companies is that everyone sort of says, you guys have really served your clients well and your loyalty serves the clients and you've actually gotten them great outcomes over the course of time. And it's been really consistent over 20 something years. Right. It's not just, oh, there was this one deal that was a high valuation that, you know, maybe you got lucky on that deal.

A (16:56)

Tell me about the best practices when, when it comes to structuring these kind of deals. What are some things to do, what are some things to avoid?

B (17:02)

The thing about the business is we are very flexible in terms of what the client wants. So we're happy and interested in working on really early stage companies and we're really excited about working on much larger companies too. So we have clients that are $500 billion in market value, half a trillion, and we have clients that have no revenue. Right. So we'll be advising, for example, you know, model ML, which is in the, you know, sort of lower end of the revenue spectrum and one of the, you know, probably, hopefully fastest growing, you know, AI companies out there. But, you know, that's a client of ours and we've got clients that are, you know, 40 billion, 50 billion, et cetera, many hundreds of billions as well. So, so we're really able to be very wide on that spectrum. So, and a lot of times if the company's super early, we're sort of well known for sometimes going in and saying, look, you know, if you want us to be your banker between now and when you ultimately exit, we can do that. Right. If you want to do buy the drink and it's $6 million capital raise, that's just not something we can do bandwidth wise. Right. So we have to work on fairly high ROI things, but the ROI can be stretched out over 15 years or it could be, you know, 15 weeks. You know, we're very flexible, so a lot of times we'll let the client sort of set the terms. So we've had clients where, you know, for example, amazing story Right. We, we got hired in 2009 by a great little company at the time called Avid Exchange. It was worth $20 million, give their metrics away. But they were raising money for 20 million and they wanted us to come in and help them raise, say 6 or 7 million dollars because they were buying a company for 3 million. Sort of famously said, mike, he's just too small. We can't really do it. And after many, many, many conversations, we agreed that we would basically be their banker for the long term and they could fire us wherever they want, but they'd have to pay us for 49 years post firing, which basically means that you're not going to fire us. So we now worked with them from 2009 to 2025. So we just sold them this year for $2.3 billion to TPG and Corpay. So it was a private equity institution teamed up by the company for a hundred x what it was when we found them. And of course along the way we raised a billion dollars for them. We helped them do eight acquisitions, never charged them for any acquisitions, helped them go public and helped them on the sale. And I believe he would have worked with them even if we didn't have the long term engagement letter. But, you know, that certainly helped. And you know, we're like, yeah, best friends this day, Mike.

A (19:29)

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B (20:53)

Was at my wedding and this and that. So we've got many, many, many of these case studies where we worked with people that were, you know, really early stage entrepreneurs and help them build, you know, many, many multibillion dollar, you know, kind of outcomes. So, and then you know, we'll work on stuff like raised a billion dollars for Revolut and they base, you know, X percent and it's a one time deal and you know we don't have a lifetime deal on that one. So, so, but a lot of things we'll let the client set the terms. So you know, it's, it's a daily thing for me to say the clients, you know, we love big incentives but you know, you tell us how you like to incentivize this. You, you probably know your fair market value, you know that X is the single, then there's the double, triple the home run, grand slam, bottom of the ninth, lights out, grand slam. Whatever, you know, and whatever you feel comfortable with, you know, paying us, you know, we'll, we'll consider that and we may want to tweak it or sometimes they set it, you know, in a way that doesn't make sense and we'll have to change it. But, but in general we're trying to let clients pick the fees and so that way they, they, they're just going to be happy with them.

A (21:50)

I have to say I've, I was a little skeptical of this model and then invited me to breakfast in Miami and we were sitting down and you started talking to me about what structure you should put on your own home with the agent.

B (22:00)

That's right.

A (22:01)

And right there I knew you were truly right.

B (22:03)

I mean it's, it's, you know, I believe in it and, and the clients believe in it too. The clients that have paid us the most money and we have multiple multi hundred million dollar fees. I must have gotten four referrals in the last two weeks from one of our clients who paid us a multi hundred million dollar fee. And you know, for, and, and, and the guys that just paid us a multi million fee like they're our best clients. Right? They're the ones that, that, so it's always the clients that are a little thrifty, that are, that are kind of missing the goal and saying I'm self fulfilling. Yeah, I mean, yes and no. I mean, yeah, hopefully not, but, but you know, if someone says show me incentive, I'll show you the activity. Right. So, or something like that. So I Think, you know, would you, would you pay a private equity manager? You know, one and, and four. Right. I give you 1%, you know, to just manage my money and then I'll give you 4% of everything over a dollar. You would never hire that person because like they must not be qualified, they must not have confidence themselves. They must not have the motivation. So I think that, you know, actually giving investment bankers similar types of upside as other financial professionals and other industries like private equity, venture capital, et cetera, you know, makes a lot of sense. Does it have to be to entwine now? Let's, doesn't have to be that at all. It can be, could give you more, give you less, whatever. So, but I just think that that's something that will change over the course of time. And a lot of bankers are trying to emulate what we're doing. But the truth is you need to build a track record first. So if you're working on a, a big buy side on Monday, a merger of two companies at no premium on a Tuesday, a big bankruptcy recovery for FTX on a Wednesday, you have a debt deal on a Thursday, IPO on a Friday, a secondary next week, and then, and then, oh, you just got out and to sell a private company, but that's like one of 15 things that you do. You're not going to really build a track record, right? It's like, so, you know, you really got to do the same thing in the same space with the same people for a long, long, long period of time in order to have the credibility, you know, to, or the audacity, you know, to charge, you know, greater than average rates for your service. Unless you're proven value add kind of a firm or person or team, it's very hard to do. We've seen a lot of people try to replicate our fee models and they don't get it. And pretty much every single time we get hired, people say, well, hey, we want to, you know, give you guys a really great incentive. And it's going to be way harder than your competitors because you're the guys we think that could actually hit it right or that would understand how to, how to, how to make that happen again. You know, there's a lot of great banks, a lot of great bankers, and we respect pretty much everybody out there. It's just, there's just different models, different structure, different folks and we're passionate about the way we do things and it's been recognized around the world.

A (24:44)

You've been labeled. If you Google you, it says world's richest banker. Is that a double edged sword or what? What is it?

B (24:51)

I mean I'm not counting, you know. You know and I, I don't really care about money honestly. You wouldn't, you wouldn't think that for what I said, right? But you know, we're trying to raise a family. We got three kids. Yeah, we are, you know, trying to raise them, you know, like we got raised. It's, it's hard, you know, cause we've done okay. But, but you know it's like the money part is keeping score and all that kind of stuff. But at the end of the day all the money's going to go to charity someday. So it's, it's just trying to, trying to do good by the world at some point in time. You know, when, when you have the time to go do that kind of charitable work. I'd say that people are, people are shocked when I get on the phone, right? And they're on like a hundred million dollar like what are you doing here? You've done so many deals and this, that I'm like this is what I do. I represent companies like you guys. Every day I'm just grinding and having a fun time and it would be able to scale the company. I'm such, we've got great cfo, hr, legal clients, you know, all that stuff. So I don't really have to do any of that kind of stuff. I could just really be client service guy and work with the teams and so. But yeah, I don't, I don't think about the money, you know, on a personal level. I think about building a great franchise, building a great place for the teams that we have here, the people that we have, the families that we have at the firm to, to prosper long term. And it's more worried about them than, than me and, and I, I worry about the clients more than me. The incentives sometimes are like the clients are the ones that win way more than us. You know, we, we, we get a little win here and there and the fees. But you say what's good for the goose is good for the gander. So it's like. But yeah, I don't sure Jamie Dimon's doing okay. And we'll see.

A (26:22)

Let's talk about Fintech today. What's the most underrated trend in the market today and where are you most bullish if you had to pick one, one spot?

B (26:30)

I don't know if it's fully underrated, but I think, I think the, the world of real world assets is something that really gets me excited and the tokenization, I should say, thereof. So you know, companies like Digital Asset Holdings, Tether, you know, taking a digital dollar, taking a digital mortgage or a digital stock or what have you. And to me that's really the future of financial services. And I don't think the traditional way is going away anytime soon. It's more of a percentage game. I think for a long time a percentage of the market is going to be done just the way it's done today on nasdaq, on nyse, you know, and you can trade through Robinhood or whatever but like slowly but surely some portion of that market is going to go tokenized, right? And so you can be trading on the blockchain, settling instantaneously with anyone in the world. And that's happening with stocks today. That's happening with at pretty much every asset class around the world. Starting the dollars with people like Circle and Tether. You know, Tether's now half a trillion dollar company. I think that that world is just going to go very big. You know, I think in the old days of, you know, 20 something years ago when you would electronify a sector, you'd be electronifying a, a piece of the sector in a small, you know, single geography. Now all this stuff is much, much, much more global. So it's kind of a trend that's affecting all fintech. But the companies are starting off being very, very big over the course of time. So that's, that's for better, for worse, that's, that's, that's where we see things going. So yeah, digitization of real world assets.

A (28:04)

Is, you go to sleep tonight, you wake up in a decade and you look at the fintech market, what does it look like in a post AI Fintech?

B (28:11)

A lot of the companies that are, that we think of as fintech today are going to be legacy, right? And there's going to be a whole new breed of companies. So you know, it's funny, you look at like the Pfizers and the, you know, first Datas and all these kind of guys and you know, they're growing single digit percentages. If I serve Stock was down 40, 50% the other day, you know, because they're getting eaten alive by lots and lots of smaller players. They got too big. FOUNDERS LAUGH the future, I think you're going to have some trillion dollar companies. You know, we've been on the record saying long before anyone, most people heard of or knew much about Revolut, that that was going to be a multi trillion dollar company. So I think you're going to see lots and lots of trillion dollar companies in 10 years. And you know, who's that going to be? But you know, nobody knows. But I would put revolut Cloudwalk, Digital asset Holdings, you know, and you know, anyone that's, that's doing things that are fully global, fully disrupting the old world, you know, that's, that's where we're putting our time. And again, you don't have to be a multi trillion dollar company to get our attention at all or potential to have that. But I think, I think the, you know, AI will just be commonplace at that time. It won't be disrupting anything. I think that all the disruption will have already happened and, and then there'll be, there'll be another wave of disruption. That's the thing I think about fintech and financial services is it's never going to be fully old school. It's always going to be probably 50, you know, 50, 60, 70% old and 25% new. And the new choose the old and the new becomes the old and it just kind of keeps happening. So you know, when you have a product like financial services, like I said, this is fully digital. I mean other than credit cards and ATM machines, which are all both going away by the way, or cash itself, you know, the whole space is going to be fully digital. There's not many other spaces that are like that. Healthcare, there's hospitals, there's medicine, there's drugs, there's gurneys. I mean that stuff's not going away. Right? But in financial services, everything being digital, you know, you can't really imagine a world where it's perfect. And so until things are perfect, there's gonna be a lot of innovation. Right? With 30 years of FinTech development, I, I find very few things in, in my life or anyone's life I know, or from underbanked up to, you know, Warren Buffett, where like the financial aspect of their life is just smooth and perfect and frictionless and all decisions are made in a highly alpha way. I mean that's where we're like 2% of the way there, right? I think with AI it's going to get a lot closer, but it's going to take a long time. So. But yeah, long live FinTech.

A (30:30)

And you referenced it. Disruption, the opposite of disruption is defensibility. What are fintech companies doing to become defensible and is that even possible in an AI world?

B (30:41)

The best ones are arming themselves with as much AI as humanly possible. I mean it costs a lot of money to do that. But I think what we're seeing is people hold the line on expenses and just push everything into AI, right? Every single function of a company has got to be completely embracing AI And I think if you're out there and you're not absolutely using AI in every single function of your company, you're going to be extinct or, or on the way to it pretty quickly over the this because the space is going to get highly efficient with a lot of new players and a lot of the old players, you know, changing their model. So it's going to be, you know, I would not want to be long a lot of traditional financial service companies over the next 10 years I'd be pushing my money into fintech and, and you know, blockchain and AI driven, you know, financial services companies. So there's going to be a lot of change coming.

A (31:30)

Do you think AI is fully priced into the fintech market or do you think it's mispriced?

B (31:35)

I think I, and still trying to figure it out. There's not that many sort of really great scaled, you know, AI first fintech companies, right? You know, you've got a couple here and there like model ML, you know, but they're not scaled, right? They're, they're, it's a great company but it's early stage and it's, it's got a scale and there's a bunch of platforms like that. You know, there's some that are doing call center stuff. It's pretty exciting. But there's, what's more exciting is companies like Revolut, Cloudwalk and others using AI first in their, in their current businesses, right? Using AI for advertising, for fraud detection, for customer service, for onboarding, for offboarding, et cetera. So I think those companies are the ones that are gonna, I think that are, that they, they were, they were already highly innovative and they immediately caught on to the AI, you know, wave, right? We've single handedly gotten certain clients to just completely abandon the old ways of doing things and just push them and say, look, here's examples of six year competitors that are doing X, Y and Z. So they literally just within a month changed their whole philosophy and you know, went full blown. You know, AI, you know, you don't get there in a month, but you change your mindset in a month, right? There's been CEOs of companies, you know, that have, you know, were like writing off blockchain or writing off AI is anything that was going to really Change their business and they're all going full, full crypto, full stable coins, full AI. So, you know, I think, yeah, people are getting religion.

A (32:57)

I look at AI as a dragon and the only safe place is on the back of the dragon. Although once in a while the dragon could look around and burn you. But it's still the safest place versus being anywhere in the village.

B (33:09)

A hundred percent. That's a good one. I'll use that one next time I try to convince a client to do AI. But no, it's a, it's ignorance.

A (33:17)

Ignorance is a strategy. Said another way, not using AI itself is a strategy. You could pretend it's not a strategy and you could pretend it's not a decision, but it's a, it's a decision to not make a decision.

B (33:27)

It's not a buzzword, right? It's, it's real. You know, you've really got to lean into these things and boy, would it be exciting to be a 25 year old kid, you know, building the next gen companies using AI. You know, one of the tricky things about AI is, is like, can everyone just build the same company? Right? You were telling me about someone else on one of your podcasts saying OpenAI is going to be dead because anyone could build a big, large language model and, or whatever his rationale was. But you know, can anyone build any of these businesses? Right? You know, and because AI can do all the building, AI could copy your business model. So what's really going to be the competitive differentiation in the future? And that's the part that's probably got me scratched in my head to some extent, you know, is, is how, you know, how that's all going to come out. Are you going to wind up having like 50 competitors doing the same thing? And therefore pricing is going to go to the point where no one can make any money and no one could differentiate company A from company B. And the minute company B comes up with a good idea, company A copies it. So it's, it's going to be, I think it's ultimately going to be very good for consumers, that the products are going to be very good, the prices are going to be very low. You, there's all this question about will there be enough jobs for everybody? Robots start, you know, taking over and you know, it's funny, we're doing a lot of studying about robots these days and one of our clients is investing in robotics companies and becoming the payment rails for these robots and things like that. So there's just some wild stuff going on out there with AI and robots are coming, so only a matter of time. And using fintech, what's a big thing.

A (34:49)

That you've changed your mind on in the past six months?

B (34:51)

Oh, six months, wow. It's a short period of time.

A (34:54)

Usually I say a year, but with AI you have to, you have to break it down to six months.

B (34:58)

I don't know, I mean, maybe it's just leaning heavy into it in my own business. Right. I think again, not to keep harping on this investment in Model ML, thinking through, you know, can you really revolutionize what we do? It's a high end craft business. At the end of the day, Apprentice, you're cranking spreadsheets, you're writing memos, you're reading data rooms. And you would think that I don't want a machine doing this stuff, but it turns out a lot of that work can be done a lot quicker, a lot more streamlined. And even if you're doing a lot of it manually, it can be checked by these agents. Right. You know, a lot of the back office stuff that we do that was kind of exciting. But then I started realizing that this could really benefit the execution of transactions. There's one thing in investment bank to save money on, you know, cheaper cost of building spreadsheets or you know, building decks and things like that. That's not something that gets me that excited. It's nice. But to me what gets me more excited is getting to market faster for the client, so getting to market in more thorough way. You know, a lot of times these, these clients that we're selling, they might only be worth a hundred, two hundred million dollars, right? Or three hundred million, whatever the number is. Well, it turns out that now the world is so global, the buyer could come from literally any continent. Right. And, and you're talking about only writing a $300 million check. As a buyer, the number of buyers that could buy any given company is probably like a thousand, right? And no banker can know a thousand companies. No banker can contact a thousand companies. No banker can analyze a thousand companies. But with AI, you can, right? You can sort of look at the whole entire world and look at the whole entire very, very detailed product description of what Company X client does and what even small divisions of large companies or private companies that have never, you've never heard of that, you don't speak the language and you couldn't even read their website, you know, could be buyers for, for certain companies in the US or Australia. So you can now sort of use today, you know, AI and not just ChatGPT. ChatGPT is going to be good for a lot of things. But I do believe that the hyper verticalization of a space is going to be very important when we are starting to train our own models on our own ecosystem and all the deals and all the buyers and all the buyer type of criteria that we think, you know. So I think it's the human side of what we do mixed in with the AI side is going to make, I think, a big difference in locating and finding buyers. One of the things that we do as a firm is we publish a lot of reports and we get a lot of imbalance from companies all around the world that we've never heard of that want to buy companies that are in the reports. Right. And so again, like even as good as we are, there's companies all around the world that no banker knows because they're not big enough to know they're on the radar, you know. And so we know that just even in the regular world without AI, we go out inbounds with people that we don't know looking at buy companies that we're affiliated with. With AI, we should be able to like significantly increase to it to a asymptotic level of perfection, like the buyer research outreach, you know, kind of process. Same thing with investors. Right. I just think that, that leaning into AI, leaning into automation, leading into this kind of stuff, it's very expensive, you know, but there's no bank in the world on a, that on a pound for pound basis is putting more money towards the client service that we are. And every single client I talked to is like, this is differentiated. Like what you guys already doing is like 10x differentiated, but this is, this takes it to 11, right? Or whatever. So it's, yeah, try to be on the leading edge. So I think that's something that's got me super passionate and then that's got me passionate about investing in AI as well and investing in fintech. So we're doing a lot of investing in companies on the side. It's just a fun game to be in.

A (38:26)

Right now the prevailing paradigm, at least among generalists, is that AI is about cost cutting, but it actually has this revenue expansion that's, that's highly undervalued. Well, Steve, 23 years in, a lot more interesting things to come for FT partners. Thanks for jumping on the podcast again and looking forward to continuing this conversation soon.

B (38:44)

David. Thank you, buddy.

A (38:46)

Thank you, Steve. That's it for today's episode of How I Invest. If this conversation gave you new insights or ideas. Do me a quick favor. Share with one person in your network who'd find it valuable, or leave a short review wherever you listen. This helps more investors discover the show and keeps us bringing you these conversations week after week. Thank you for your continued support.