The Exchanges

Q Maybe talk about what's different about defensibility for even the, the bigger players today in the AI era than it was in, let's say, the web two era. Are the companies today more defensible, less defensible, or how should we think about sort of the strength?

A I don't know. I, I think the, the less defensible part, I mean, this is, this is why a lot of enterprise software has gotten beaten up in the public markets. It's kind of two reasons. Number one is that if you're doing per seat pricing, like, how do you come up with a pricing model that people feel is fair? And a lot of it is just psychology, and for whatever reason, for the last 20 years, it's like per seat per month, with like, uh, you know, you've, you've heard my joke, the, the tall grande venti model of, like, software, uh, charging. It's like somehow that felt fair. And whether that is fair or not, like, I don't know, but like people are like, oh yeah, it's like 85 dollars a seat, you know, per month. Yeah, ok, that sounds reasonable. Whereas if you, if you propose that pricing 40 years ago, you would have been laughed out of town. So this just became the norm. Um, and the reason why, as I was saying, public software companies have been beaten up a little bit is like, uh oh, maybe you won't sell as many seats. Like, is Adobe gonna sell as many seats if now you don't have to hire as many graphics designers? Or is Zendesk going to sell as many seats if the, Software just answers all the queries. Like, the answer is no. It doesn't mean that the companies are toast. They might actually quintuple their revenue because now they charge per outcomes as opposed to charging proceed…

AI assessment note: “I think the, the less defensible part, I mean, this is, this is why”

Q like Uber and Airbnb, et cetera, that, uh, you know, the incumbents, you know, some of them became trillion dollar companies, you know, I've got to buy mobile. When we look at the, you know, business impact of, of the AI era, um, what's your mental model for thinking about sort of the incumbent or startup or kind of net new company in terms of value, you know, value capture?

A I, I think a lot of it is the same, like, unless you really screw up the, the pricing model, or like, you know, you're all per seat pricing, it's very, very hard to just get the market to adopt something that is just violently different, and you're operating in the public eye, and your technology team is bad, there, there are a lot of ands that need to happen. I have a hard time believing that incumbents will really suffer. Um, I mean, there probably are some things, like, you know, take, like, one example of, and this kind of goes back to distribution versus technology, Like, all of these business process outsourcing companies, these BPOs, they're the largest employers on the planet. So, like, Tata, Wipro, Infosys. So, if I'm JP Morgan, and I say, I need a call center, and this call center needs to have access to, like, customer records, and it needs to be safe, and everybody needs to be trained, like, and I need to have, like, a 100,000 people that can answer the phone, you know who can do that for you? Infosys, right? Or Tata. Um, Tata has already done the integration with JP Morgan in this case. They might just add AI, and now they don't need a 100,000 people, and they maintain that JP Morgan contract, and they operate in the area of the Goldilocks zone, where it's like, they're gonna make, like, a hundred times more money. That, that's one case. That's the bull case for Ta…

AI assessment note: “I have a hard time believing that incumbents will really suffer.”

Q will, you know, your companies will, you know, there'll be a vibe-coded version of it, but we've seen none of that so, so far. Is your mental model is, we'll, we'll see it to the, in examples where the, the cost is significantly high, or in which there's sort of Greenfield, you know, opportunities, or what is sort of your mental model for the types of software that we'll replace?

A Yeah, I mean, I think the Greenfield one is always true, but when you look at Greenfield opportunities, you need two things to be true. You need the entrepreneur to be very, very patient and say, I'm not going to try to sell to everybody who's, if I'm, if I'm starting a net new payroll company, I'm not going to try to sell to GE because I recognize that they are, they are hostages to ADP and that's never going to change. So one is that patience of entrepreneur, and the other one is you just need a high enough rate of new company creation To really make it work, which is why, um, like to pick on one space of electronic health records or electronic medical records, how many new hospital systems are created every day? I mean, it rounds to zero. So if I'm trying to go build a new EHR system to go compete with Epic or Cerner, I can do that. Um, there are a lot of edge cases there, but it's like, and I might have patience as an entrepreneur, but wait a minute, like, I need to sell five million dollar deals to big hospital systems. Every single hospital on earth is currently using an EHR system. Going to be really, really hard to make that work. So I think, I think both of those need to be true. Like the right type of entrepreneur who's willing to be patient because it's, it's often a very lonely game of it's like, I built this great product. Wait a minute. I don't have any customers …

AI assessment note: “I think the Greenfield one is always true, but when you look at Greenfield opportunities”

Q Let me just pause on that for a minute. Why is that dangerous?

A I'll give you an example. There's a company called Yodaly. It's been around for about 20 years. It's a, it's a key part of the ecosystem for every fintech company that goes and gets data from banks. So if you ever go to E-Trade and it says, hey, log into your whatever Bank of America account to transfer funds, that's going through Yodely. If you ever signed up for Mint, uh, when Mint came out, that was going through Yodely. Now it turns out they, they get all of that information in aggregate, and they have a different business model, which is they sell anonymized aggregated information that they're collecting from everybody that is all of the businesses that are working with Yodely If they do that too aggressively, it puts them at odds with their main core business, if that makes sense. So you have to be careful when we looked at this as trial pay. The first time that we tried this, we're like, I know we're going to email a million people that went through trial pay yesterday and say, here's another product that you might be interested in, but that other product might've been at odds with WinZip. So we didn't have free reign over those consumers without being not parasitic because we wanted to be a symbiote with our, our middle B. And you can go from being a symbiote to a, to a parasite or even a, an antagonist. If you start doing things that are competitive with what they're d…

AI assessment note: “You can go from being a symbiote to a, to a parasite or even a, an antagonist.”

Q So is the ideal opportunity then for a startup to be sort of at that center of all these different players, like play a broker like role or to try to create something in its own vertical? I mean, like where did the opportunities lie here for startups in both of your spaces and beyond?

A I think it really, I mean, I hate to say it depends, but it really depends because I mean, in some cases you're creating something new and you're not really, I mean, like in the fraud case, it's not like you're extracting Like very, very confidential, confidential information and sanitizing it. Or there, there's a company called Yodaly, which is very, very interesting. They are like every fintech company pretty much on earth right now is in some way, shape, or form using Yodaly to aggregate information across all of these different, uh, financial services companies. Like, so you have an E-Trade account, you have your IRA with, you know, Fidelity, and you've got your bank account with Bank of America, and you want to put them in a Mint-like interface, whether on mobile or on the desktop, Yodaly is typically the player behind the scenes that's aggregating all of that, but then Yodaly actually retains all of that information as well, and they can use it for, on an anonymized basis, their own purposes. That didn't exist before. So people are doing all sorts of cool things on that data as well to figure out, you know, what's happening in the world. So it really depends on whether or not you're, like, there's the, I have to build a cooperative, and there are only 10 companies that have this data, and I'm going to be the UN between them. Sure, that's very, very valuable, but it's very…

AI assessment note: “it really depends... there's the, I have to build a cooperative”

Q So where did the tangible goods part come in?

A Um, so the idea was, wouldn't it be great if I could let you pay for something tangible And by doing so, I get paid from the tangible goods company, and then I'm able to give you my product for free. So I started doing this, um, kind of in the early 2000, which was, this was the, the harbinger of, of, of trial pay, which is, okay, you don't want to pay for my product. I'll give it to you for free if you go shop at gap.com. It turns out gap is a 50% gross margin or more. You go spend 200 bucks at gap, that's a hundred dollars of gross margin that they have to play with. They Almost every major retailer has something called an affiliate program, where they will pay for the referred traffic, so that's what I started doing, and that seemed like a major problem as well, because I wasn't the only one out there. Little Shareware Alex wasn't the only one that had a problem of most people not paying me. Every major software developer, every major kind of intangible goods maker had this exact same problem, where a hundred percent of their revenue comes from one percent of their users. If you can get one percent of the other 99% to do something, Um, whether switching to Geica, which I try to do, but it turns out you can't incent people to switch their insurance, um, or shopping at Gap or signing up for Netflix. So this actually worked really well and started branching out beyond that.

AI assessment note: “I'll give it to you for free if you go shop at gap.com.”

Q But don't the incumbents have a structural advantage here?

A The structural advantage that Chase has is that they have lots and lots of depositors. They have a very well-known brand. They have all these different systems in place for managing risk. Um, the structural disadvantages that they, and also the other structural advantages, they can borrow from the Fed for zero percent, which is kind of nice right now. Um, the structural disadvantage is they have 250,000 people. They have thousands of branches. These are all things that were super relevant 25 years ago. That's how you grew as a bank. But if you were going to develop a bank from scratch today, chances are very, very high, you wouldn't say, my first order of business is to go sign 9000 leases at different, ah, commercial banking centers across the country. You'd say, I'm gonna have a mobile app, and that will do it for me.

AI assessment note: “The structural advantage that Chase has is that they have lots and lots of depositors.”

Q Valley startups that have, you know, toothbrush tests, but don't have a money printing machine attached to it. You know, uh, rocket has been able to acquire a sort of demand machine, you know, in, in, in Redfin and others. Why is it so hard in real estate if you own sort of the place where people are searching every day to build the money printing machine next to it?

A Well, there's so much latency. I mean, like I think of Zillow is a good example of this, like Zillow, a lot of people use Zillow. Um, it actually doesn't make that much money because it's like, it's a lead generation machine for agents. That's how they make money. Uh, the vast majority of their revenue comes from like, you do a search. Why are you doing a search? You're not even doing a search with purchase intent. Like Google makes a lot. We've talked about Google a lot in many podcasts, right? Like, so Google makes lots of money and it's a freemium model where it's like, 99% of the time you're searching for like, how do I kill this annoying fly that keeps like buzzing around our, our pot? Like, and then One percent of the time it's like, I want to go buy a flyswatter.

AI assessment note: “You're not even doing a search with purchase intent.”

Q So where did the tangible goods part come in?

A Um, so the idea was, wouldn't it be great if I could let you pay for something tangible And by doing so, I get paid from the tangible goods company, and then I'm able to give you my product for free. So I started doing this, um, kind of in the early 2000, which was, this was the, the harbinger of, of, of trial pay, which is, okay, you don't want to pay for my product. I'll give it to you for free if you go shop at gap.com. It turns out gap is a 50% gross margin or more. You go spend 200 bucks at gap, that's a hundred dollars of gross margin that they have to play with. They Almost every major retailer has something called an affiliate program, where they will pay for the referred traffic, so that's what I started doing, and that seemed like a major problem as well, because I wasn't the only one out there. Little Shareware Alex wasn't the only one that had a problem of most people not paying me. Every major software developer, every major kind of intangible goods maker had this exact same problem, where a hundred percent of their revenue comes from one percent of their users. If you can get one percent of the other 99% to do something, Um, whether switching to Geica, which I try to do, but it turns out you can't incent people to switch their insurance, um, or shopping at Gap or signing up for Netflix. So this actually worked really well and started branching out beyond that.

AI assessment note: “I'll give it to you for free if you go shop at gap.com”

Q Does behavior need to change, and is that what we're kind of fighting against, why things don't happen as quickly?

A So inertia is an incredibly powerful thing, especially for banking. So why don't people change their bank accounts to earn more money? So all you have to do is go to bankrate.com or any of these other kind of savings account, like how much do I earn on my money that I have in my bank account? And you'll see like, I mean, probably 99.999% of people do not have the highest yielding bank account because it's probably the bank of internet or some like crazy name that's listed on bankrate.com. But think about what goes on with your banking relationship. You have your salary direct deposited into there. So I want to change my bank, and that means I have to go to my, my employer, fill out all these forms, bring a voided check. I don't even have, like, what is a check? I've never seen one before. Where do I get one? I never asked for one. Can my ATM card work? No, that won't. Uh, then you have, maybe you have a mortgage from your bank, and they'll give you a 25 basis point reduction on your overall rate, assuming that you have a direct deposit. Salary integration with them.

AI assessment note: “inertia is an incredibly powerful thing, especially for banking.”

Q like Uber and Airbnb, et cetera, that, uh, you know, the incumbents, you know, some of them became trillion dollar companies, you know, I've got to buy mobile. When we look at the, you know, business impact of, of the AI era, um, what's your mental model for thinking about sort of the incumbent or startup or kind of net new company in terms of value, you know, value capture?

A I, I think a lot of it is the same, like, unless you really screw up the, the pricing model, or like, you know, you're all per seat pricing, it's very, very hard to just get the market to adopt something that is just violently different, and you're operating in the public eye, and your technology team is bad, there, there are a lot of ands that need to happen. I have a hard time believing that incumbents will really suffer. Um, I mean, there probably are some things, like, you know, take, like, one example of, and this kind of goes back to distribution versus technology, Like, all of these business process outsourcing companies, these BPOs, they're the largest employers on the planet. So, like, Tata, Wipro, Infosys. So, if I'm JP Morgan, and I say, I need a call center, and this call center needs to have access to, like, customer records, and it needs to be safe, and everybody needs to be trained, like, and I need to have, like, a 100,000 people that can answer the phone, you know who can do that for you? Infosys, right? Or Tata. Um, Tata has already done the integration with JP Morgan in this case. They might just add AI, and now they don't need a 100,000 people, and they maintain that JP Morgan contract, and they operate in the area of the Goldilocks zone, where it's like, they're gonna make, like, a hundred times more money. That, that's one case. That's the bull case for Ta…

AI assessment note: “I have a hard time believing that incumbents will really suffer.”

Q Valley startups that have, you know, toothbrush tests, but don't have a money printing machine attached to it. You know, uh, rocket has been able to acquire a sort of demand machine, you know, in, in, in Redfin and others. Why is it so hard in real estate if you own sort of the place where people are searching every day to build the money printing machine next to it?

A Well, there's so much latency. I mean, like I think of Zillow is a good example of this, like Zillow, a lot of people use Zillow. Um, it actually doesn't make that much money because it's like, it's a lead generation machine for agents. That's how they make money. Uh, the vast majority of their revenue comes from like, you do a search. Why are you doing a search? You're not even doing a search with purchase intent. Like Google makes a lot. We've talked about Google a lot in many podcasts, right? Like, so Google makes lots of money and it's a freemium model where it's like, 99% of the time you're searching for like, how do I kill this annoying fly that keeps like buzzing around our, our pot? Like, and then One percent of the time it's like, I want to go buy a flyswatter.

AI assessment note: “Well, there's so much latency. I mean, like I think of Zillow”

Q Let me just pause on that for a minute. Why is that dangerous?

A I'll give you an example. There's a company called Yodaly. It's been around for about 20 years. It's a, it's a key part of the ecosystem for every fintech company that goes and gets data from banks. So if you ever go to E-Trade and it says, hey, log into your whatever Bank of America account to transfer funds, that's going through Yodely. If you ever signed up for Mint, uh, when Mint came out, that was going through Yodely. Now it turns out they, they get all of that information in aggregate, and they have a different business model, which is they sell anonymized aggregated information that they're collecting from everybody that is all of the businesses that are working with Yodely If they do that too aggressively, it puts them at odds with their main core business, if that makes sense. So you have to be careful when we looked at this as trial pay. The first time that we tried this, we're like, I know we're going to email a million people that went through trial pay yesterday and say, here's another product that you might be interested in, but that other product might've been at odds with WinZip. So we didn't have free reign over those consumers without being not parasitic because we wanted to be a symbiote with our, our middle B. And you can go from being a symbiote to a, to a parasite or even a, an antagonist. If you start doing things that are competitive with what they're d…

AI assessment note: “it puts them at odds with their main core business”

Q And how do you make it more deterministic versus, like, this random thing?

A Well, I mean, that's, that's where, kind of, economics comes in. So, like, imagine that you're at the stage where you actually are charging for your product. A good sign is that, assuming that you kind of started off in the low monetary value area, and now you're charging for reads in the high monetary value area, if you are charging more Then the incumbents. I mean, normally you say, oh, if I can like charge one-tenth as much, then it's going to be very disruptive and I'm shrinking the market, but you actually have the opportunity to charge a lot more, um, value-based pricing. So if you can really show that you're charging 20, 30, 40% more than the competition, that's a, and they're actually willing to pay for it, and they're switching from a lower priced product, either they're totally irrational, they say, hey, I want to lose more money this year and increase my cost, which by the way, almost never happens, or You've actually demonstrated in the eyes of many, many customers that they are willing to pay more because your data is better, and they're contributing back to this collective as well, which almost de facto means that you do have a data network effect, and it's not about prognosticating. It's like, it's actually real.

AI assessment note: “which almost de facto means that you do have a data network effect”

Q Right. Or what if you pay your bill in cash all the time because you're just not in credit?

A I remember, I, I could not get a credit card in college, and the reason why I kept getting rejected is because I had never had a credit card before, and this is the definition of a catch-twenty-two. If you look at most people between 20 and 30 years old, They have a debit card, not a credit card, but the point there is that they, they are known as thin file customers. They're not bad credit. The term in the industry is thin file. And how do you underwrite credit for somebody that has no file or a thin file? And the answer is you can't using kind of traditional FICO scores. Right. The other thing is that you have this whole category of people that went through some kind of hardship in the past. So, 2008, 2009 might seem like a distant memory, but it's not for your credit report. So, You might have been doing everything right, and you had this double whammy of you lose your job, and, uh, your house is foreclosed, and it doesn't mean that you were being reckless with your spending. You actually, you are predisposed to always paying your bills on time. You're a very honest, ethical person, and now you have this, this black spot on your credit rating, um, or your credit score. You actually might have a lot of cash now. Maybe you won the lottery, um, and all these good things happen to you.

AI assessment note: “they are known as thin file customers. They're not bad credit.”

Q So how did you go from these kinds of products to payments?

A I was running my business off of AOL because in the, the early mid nineties, AOL was kind of the de facto internet for most people that didn't have, you know, weren't at a university campus and didn't have access to like a T one line or something. In the, I think it was the winter of 1996, AOL used to charge three bucks an hour. They used to charge six dollars an hour when I started using it. They cut it to three, then they went to 20 dollars a month flat rate, and understanding the laws of economics, if you lower the price of something, typically the quantity demanded goes up. If you lower the price of something to zero, the quantity demanded goes up a lot, but they kept the number of modems the same. Consequently, it became impossible to connect to AOL, and AOL would dial each number one time and then give up. So I wrote this program for me that was called Always Online. It would dial each number a thousand times in a row, so it would guarantee that you connected, and then once you connected, it would keep you online forever by emulating modem activity and dismissing these dialogue boxes that AOL would pop up to kick you offline. Always Online sold tens of thousands of copies, which was kind of crazy. I was 15 years old, and I might get, like, a 1010 dollar checks in the mail in a day.

AI assessment note: “I might get, like, a 1010 dollar checks in the mail in a day.”

Q In, in, Web two, there was a lot of winner take most. Um, you were talking about one of the benefits in AI is that there's multiple winners. To what extent is, is consolidation inevitable? Or how do you think sort of this, this plays out?

A Well, I think if you have 20 companies that are all doing the same thing, um, what has historically happened is that it's a bad market if there are 20 companies doing it, but then, I don't know, the bottom 15 just go bankrupt, um, and then maybe there's some consolidation where number one buys number two, number two buys number three, and assuming that we have a functional FTC and whatnot, it's like all of this is approved because it's not like you're taking, this is like, Orthodontic clinic answering software or something. Um, so, and then what was a bad market becomes a good market. Um, and this kind of goes back to like why momentum is important, because if you have 20 companies that are all at the exact same scale, um, then it's actually great for the customer, which is like the, the prices go to zero, um, or they converge on the price of electricity, whereas if you, this is not saying you want to go build a monopoly in orthodontic answering software or something, But rather, you can charge more if you get to a certain scale, because whatever the, the quality of the product that you're delivering at the end of the day is just higher. Um, and you have to get to the critical scale to get there, and sometimes you just need these markets to, to work themselves out. I mean, like, when I was running my company, TrialPay, we had, I don't know, 20 competitors, and it was tough, bec…

AI assessment note: “then maybe there's some consolidation where number one buys number two”

Q will, you know, your companies will, you know, there'll be a vibe-coded version of it, but we've seen none of that so, so far. Is your mental model is, we'll, we'll see it to the, in examples where the, the cost is significantly high, or in which there's sort of Greenfield, you know, opportunities, or what is sort of your mental model for the types of software that we'll replace?

A Yeah, I mean, I think the Greenfield one is always true, but when you look at Greenfield opportunities, you need two things to be true. You need the entrepreneur to be very, very patient and say, I'm not going to try to sell to everybody who's, if I'm, if I'm starting a net new payroll company, I'm not going to try to sell to GE because I recognize that they are, they are hostages to ADP and that's never going to change. So one is that patience of entrepreneur, and the other one is you just need a high enough rate of new company creation To really make it work, which is why, um, like to pick on one space of electronic health records or electronic medical records, how many new hospital systems are created every day? I mean, it rounds to zero. So if I'm trying to go build a new EHR system to go compete with Epic or Cerner, I can do that. Um, there are a lot of edge cases there, but it's like, and I might have patience as an entrepreneur, but wait a minute, like, I need to sell five million dollar deals to big hospital systems. Every single hospital on earth is currently using an EHR system. Going to be really, really hard to make that work. So I think, I think both of those need to be true. Like the right type of entrepreneur who's willing to be patient because it's, it's often a very lonely game of it's like, I built this great product. Wait a minute. I don't have any customers …

AI assessment note: “when you look at Greenfield opportunities, you need two things to be true.”

Q So how did you go from these kinds of products to payments?

A I was running my business off of AOL because in the, the early mid nineties, AOL was kind of the de facto internet for most people that didn't have, you know, weren't at a university campus and didn't have access to like a T one line or something. In the, I think it was the winter of 1996, AOL used to charge three bucks an hour. They used to charge six dollars an hour when I started using it. They cut it to three, then they went to 20 dollars a month flat rate, and understanding the laws of economics, if you lower the price of something, typically the quantity demanded goes up. If you lower the price of something to zero, the quantity demanded goes up a lot, but they kept the number of modems the same. Consequently, it became impossible to connect to AOL, and AOL would dial each number one time and then give up. So I wrote this program for me that was called Always Online. It would dial each number a thousand times in a row, so it would guarantee that you connected, and then once you connected, it would keep you online forever by emulating modem activity and dismissing these dialogue boxes that AOL would pop up to kick you offline. Always Online sold tens of thousands of copies, which was kind of crazy. I was 15 years old, and I might get, like, a 1010 dollar checks in the mail in a day.

AI assessment note: “I might get, like, a 1010 dollar checks in the mail in a day.”

Q Maybe talk about what's different about defensibility for even the, the bigger players today in the AI era than it was in, let's say, the web two era. Are the companies today more defensible, less defensible, or how should we think about sort of the strength?

A I don't know. I, I think the, the less defensible part, I mean, this is, this is why a lot of enterprise software has gotten beaten up in the public markets. It's kind of two reasons. Number one is that if you're doing per seat pricing, like, how do you come up with a pricing model that people feel is fair? And a lot of it is just psychology, and for whatever reason, for the last 20 years, it's like per seat per month, with like, uh, you know, you've, you've heard my joke, the, the tall grande venti model of, like, software, uh, charging. It's like somehow that felt fair. And whether that is fair or not, like, I don't know, but like people are like, oh yeah, it's like 85 dollars a seat, you know, per month. Yeah, ok, that sounds reasonable. Whereas if you, if you propose that pricing 40 years ago, you would have been laughed out of town. So this just became the norm. Um, and the reason why, as I was saying, public software companies have been beaten up a little bit is like, uh oh, maybe you won't sell as many seats. Like, is Adobe gonna sell as many seats if now you don't have to hire as many graphics designers? Or is Zendesk going to sell as many seats if the, Software just answers all the queries. Like, the answer is no. It doesn't mean that the companies are toast. They might actually quintuple their revenue because now they charge per outcomes as opposed to charging proceed…

AI assessment note: “now everybody can vibe code up a Zendesk competitor.”

Q And how do you make it more deterministic versus, like, this random thing?

A Well, I mean, that's, that's where, kind of, economics comes in. So, like, imagine that you're at the stage where you actually are charging for your product. A good sign is that, assuming that you kind of started off in the low monetary value area, and now you're charging for reads in the high monetary value area, if you are charging more Then the incumbents. I mean, normally you say, oh, if I can like charge one-tenth as much, then it's going to be very disruptive and I'm shrinking the market, but you actually have the opportunity to charge a lot more, um, value-based pricing. So if you can really show that you're charging 20, 30, 40% more than the competition, that's a, and they're actually willing to pay for it, and they're switching from a lower priced product, either they're totally irrational, they say, hey, I want to lose more money this year and increase my cost, which by the way, almost never happens, or You've actually demonstrated in the eyes of many, many customers that they are willing to pay more because your data is better, and they're contributing back to this collective as well, which almost de facto means that you do have a data network effect, and it's not about prognosticating. It's like, it's actually real.

AI assessment note: “if you can really show that you're charging 20, 30, 40% more than the competition”

Q Their margins are just different, right? Um, So how do you reinvent the banking industry, and how do you reinvent the business?

A So at the end of the day, um, you don't need to reinvent it. Um, if I'm a bank, and I can line up, if, if I can source loans in a meaningful way, I can control my risk in a meaningful way, and I don't have all these, what I would call structural disadvantages, like thousands of leases, hundreds of thousands of tellers, and You know, no, no disrespect to the profession of the bank teller, but it's probably not one that's going to be around in 50 years, much less 15. If I don't have to pay all these people, and I can lower that spread, Lending Club is kind of a bank. It's not, it's not a bank for a variety of reasons, and they can't call themselves a bank.

AI assessment note: “you don't need to reinvent it.”

Q Why are they incented to even do that for you if you're so captive as a customer?

A It's actually, it's twofold. One is to keep your banking relationship, but actually more importantly, it's to watch your cashflow. So they know what kind of risk you are. They know if you've lost your job because you no longer have deposits coming in from your employer. So they're able to watch them in real time. I mean, it turns out that, uh, with companies like Yodaly and Intuit, um, anybody can do this now. Uh, you don't have to own the banking relationship. If you want to see what people are doing with their own personal funds, like non-cash, but like actual, like in a bank account, You can watch that through one of these third parties. So my main thing is that it's just inertia is very, very, it's very powerful. And, uh, Chase has trillions of dollars of deposits, and they offer the lowest rates, which seems like that doesn't make any sense in any other industry. Like, if there are, like, two gas stations, one's over here, one's across the street, and one of them offers gas for three times as much, you'd say, well, geez, like, it's a little bit of a pain to take a U-turn. Right. But I'm going to take a U-turn, because I'm going to save 50 bucks on my gas, and all gas is gas, and it made out of the same chemical compound, so it doesn't really matter. Banking is just, you have to get people to care, which is a big problem. Uh, there are all of these kind of interconnected re…

AI assessment note: “One is to keep your banking relationship, but actually more importantly, it's to watch your cashflow.”

Q Yeah. A lot of HR people come off very like, okay, and here's the paperwork and you're done and you gotta sign it. And there's like legal reasons for that. So what's the right balance here? And, and I mean, I know there's no right answer, but what's the best practice?

A Shannon can probably answer the, the HR aspects of that very, very well. I mean, for me, it was more of How do we still communicate? I mean, to, to your point, like people are showing up to work for this mission, for the founders, for everything else that they really signed up for. How do we show that there's still a plan to win? Because if you just kind of say like, Hey, we had to do this because we have to cut costs and yep, that's what we got to do. Sorry. Time to go back to work. Like you're not going to have a very motivated workforce at that point in time. And I'd say that in most cases, people understood, I mean, even the people being let go, I remember the first time we did one of these, I mean, I literally didn't sleep the night before, and because there were some people, like, there, there was somebody who had worked for me for a very, very long time, who was terrific, but she didn't really have that much to do anymore, just given what, what the company was going through, and that was a really, really tough one, but she was, she just said, you know, I, I totally understand. I mean, like, I, I know where things are, and like, you've been great to me, and you know, thank you.

AI assessment note: “How do we still communicate? ... How do we show that there's still a plan to win?”

Q Alex, how about you? How do you react to what's been happening or how do you make sense of what's going on?

A Uh, well, I hope, I hope I'm right in the long run, which is all this stuff is crazy. Um, I think I, I, I tweeted about this a few weeks ago where my, my kind of cursory glance is that there are three different types of SaaS companies and the public markets couldn't tell the difference between the three. And one is where seats are tied to outcomes. So seats, seats are being used by people who use kind of going back to the filing cabinet metaphor, right? Like if I'm Zendesk, I'm using Zendesk and, and, you know, they came up with a very clever pricing model. Um, which, by the way, like, maybe I can take a step back before I even answer your question, which is, there's this great book by Dan Ariely called Predictably Irrational. And I used to give it to all my product managers at my company. It's like, study this to figure out how we charge people for stuff. Um, because it turns out, like, people, like, and the example that he gives is, like, imagine you're locked out of your, your apartment, it's midnight, you hire a locksmith, comes one minute later, lets you in in 30 seconds, says it's 500 bucks. You're like, 500 bucks? What the F? Like, you just did, like, 90 seconds of work. You leave them a one-star Yelp review, you know, no tip, you know, protest the charge in your credit card. Now imagine Parallel Universe. Light, you know, Locksmith comes, um, spends nine hours trying to…

AI assessment note: “there are three different types of SaaS companies and the public markets couldn't tell the difference”

Q And you, you said a company that could do that will be one of the biggest in the world. Has a company like Amazon or, or other big companies tried to do something like this, or is it just so far field that they wouldn't, would never?

A Well, the other thing that's, I think, very unique about this industry is it's so fundamentally local. So if you say, I want to beat the MLS, there is no MLS Inc. It's not like, Ooh, I'm gonna go beat those guys. And the commander's intent of the general is like, take that hill. You it's every market is different. And that's the thing. It's like, just because like you could dominate Charlotte and that does not make a single dent at all in Hawaii. Um, and actually the, the one case where I used a real estate agent to buy my house was in Hawaii. I have a house in Hawaii and They don't use the MLS there. It's just like this captive system where it's just like they make sure that you go through and like those agents do so well because like it just shows the value of a marketplace. But you could have a company that decides I'm going to go run the table in X, Y, Z place, and it doesn't show up in a different geography. So what, what you do see going back to these kind of pockets of esoteric, you know, products, either financial or real estate, um, executive moving. This is actually like a big thing. So imagine that you're hired as, actually I have a friend who was hired as the CMO at Home Depot, and she and her husband lived in New York, and guess what? Home Depot is not in New York. They're in Atlanta. They're like, okay, we will buy your old house from you, um, and we'll pay like t…

AI assessment note: “very unique about this industry is it's so fundamentally local”

Q Yeah. A lot of HR people come off very like, okay, and here's the paperwork and you're done and you gotta sign it. And there's like legal reasons for that. So what's the right balance here? And, and I mean, I know there's no right answer, but what's the best practice?

A Shannon can probably answer the, the HR aspects of that very, very well. I mean, for me, it was more of How do we still communicate? I mean, to, to your point, like people are showing up to work for this mission, for the founders, for everything else that they really signed up for. How do we show that there's still a plan to win? Because if you just kind of say like, Hey, we had to do this because we have to cut costs and yep, that's what we got to do. Sorry. Time to go back to work. Like you're not going to have a very motivated workforce at that point in time. And I'd say that in most cases, people understood, I mean, even the people being let go, I remember the first time we did one of these, I mean, I literally didn't sleep the night before, and because there were some people, like, there, there was somebody who had worked for me for a very, very long time, who was terrific, but she didn't really have that much to do anymore, just given what, what the company was going through, and that was a really, really tough one, but she was, she just said, you know, I, I totally understand. I mean, like, I, I know where things are, and like, you've been great to me, and you know, thank you.

AI assessment note: “Shannon can probably answer the, the HR aspects of that very, very well.”

Q uncovering the ones that actually work, and then finding the The right amount to charge for a week, um, where you can make money and they still will be a customer. But how does technology enable all this and how is it starting to change things? Because I hear you describe the sort of landscape. How do we then come in with new ideas that help change what you described?

A So I think software is a huge part of it, because this is exactly, like, the reason why you charge very high interest rates is you just, it, it is this regression to the mean of, or not even regression to the mean, it's like, I don't know, so I feel like I'm protected with a margin of error if I just charge you a lot. Part of this is a regression to, or just going back in a time machine to an earlier place, so I find this very fascinating. Like, a hundred years ago, you go to the general store, And you left your wallet with your gold ingots and your silver back in your home, and you say, hey, general store owner Joe, you know me, I'm Alex. Uh, I don't have the money right now, but I live, like, right near the saloon. Like, I'll go pay you back next week.

AI assessment note: “So I think software is a huge part of it”

Q Alex, how about you? How do you react to what's been happening or how do you make sense of what's going on?

A Uh, well, I hope, I hope I'm right in the long run, which is all this stuff is crazy. Um, I think I, I, I tweeted about this a few weeks ago where my, my kind of cursory glance is that there are three different types of SaaS companies and the public markets couldn't tell the difference between the three. And one is where seats are tied to outcomes. So seats, seats are being used by people who use kind of going back to the filing cabinet metaphor, right? Like if I'm Zendesk, I'm using Zendesk and, and, you know, they came up with a very clever pricing model. Um, which, by the way, like, maybe I can take a step back before I even answer your question, which is, there's this great book by Dan Ariely called Predictably Irrational. And I used to give it to all my product managers at my company. It's like, study this to figure out how we charge people for stuff. Um, because it turns out, like, people, like, and the example that he gives is, like, imagine you're locked out of your, your apartment, it's midnight, you hire a locksmith, comes one minute later, lets you in in 30 seconds, says it's 500 bucks. You're like, 500 bucks? What the F? Like, you just did, like, 90 seconds of work. You leave them a one-star Yelp review, you know, no tip, you know, protest the charge in your credit card. Now imagine Parallel Universe. Light, you know, Locksmith comes, um, spends nine hours trying to…

AI assessment note: “maybe I can take a step back before I even answer your question”

Q a second. So Alex, you, you make the investment and you've got this vision for the company, uh, and the opportunity. What have we learned about the feasibility of the opportunity based on the company performance? It's another way of asking, like for people who haven't been following the company trajectory, you know, how have things gone? What have we learned? What are the ups and downs been, et cetera?

A Well, so, uh, there was a point in time where open door was such a good idea. Um, you know, there, there's a saying that we use a lot of venture capital. It's like, you know, you want to invest in a bad idea, something that looks like a bad idea, that's actually a good idea, because if it looks like a good idea, then it becomes a bad idea. Um, and Opendoor was somewhere in between the two of these, because Zillow was like, oh my God, like, you know, Rich Barton comes back to Zillow, Spencer leaves, and it's like, I have to go do what Opendoor does. Um, everybody was getting into iBuy and Offerpad, you know, popped up, but like Zillow was the big one, and, um. They couldn't do it. Uh, well, so, but, but here's why they couldn't do it. It's an interesting story, and, like, the other part of the story is, like, Ben Thompson wrote a post that almost, like, kind of summarizes in a more eloquent form, like what I was talking about with, like, you know, if you get all the, if you get all the supply or just a small sliver of proprietary supply, you get all the demand, and once you have all the demand, then you can have your own, then supply just comes to you, and that's how you finally build a marketplace, and I think rumor has it that Rich Barton reads Ben Thompson, uh, as, as everybody should, because Ben Thompson is very, very smart, like, holy shit, we have to do this.

AI assessment note: “It's an interesting story, and, like, the other part of the story is”