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- [00:00]
A
I'm very excited to share that we have Eric Jackson in the house today. He goes through his next hundred bagger stock picks, the software stocks that he is actively shorting right now, what he's finding with his new AI research system, how he discovered who Satoshi might actually be compared to the New York Times, and much more. We went over everything. There is a ton of alpha in this conversation. I think you're going to love it. Eric, it's great to see you. I want to get right into Open Door. You got in at 73 cents. The stock went all the way up to 10 bucks, and now I think it's around four or five dollars. How are you thinking about the company now?
- [00:38]
B
I love Opendoor as much today at 4 something as I did at almost 11 something and a heck of a lot more than I loved it at 73 cents. It's been wild for me to kind of get some of the pushback online, especially from the retail community who say, you need to tweet more about Opendoor. How come we don't hear about you tweeting about Open or help us? And I presume, like, a lot of these people got into Opendoor at higher prices, right? And basically Opendoor sort of peaked a couple of weeks after Kaz was hired as the new CEO. And that's when the stock shot up to almost 11 bucks. And now, you know, it's down more than 50% since then. And that's real pain. And I don't, you know, it hurts me, but I know anybody who got in at 10 or, you know, close to 11, you know, must really hate that. So I don't. I don't excuse that, but I, you know, you have to take a step back and you have to, like when I was tweeting up morning, noon and night about Open Door, I mean, that's when they were run by this woman, Carrie Wheeler, who was CAS predecessor as the CEO, who's doing a terrible job, by all accounts, left the company with, like, a financial stranglehold in terms of, like, a really toxic convertible note. And. And so. And it didn't seem like the board was paying that close attention. Now we've got this guy Kaz, who, in my estimation is, you know, as good, if not better than any other CEO in tech. I had been wanting, like, Travis from Uber to come in and kind of take this company, but the more I've gotten to see Kaz up close and see him operate, I think he's just as good, if not better. And you've Got the new board with Keith Raboy as chair of this company and everybody else that Kaz is assembled around him. It's a dream team in my opinion. And so why do I have to, from the cheap seats, be tweeting about Opendoor? It doesn't mean I like it any less, doesn't mean I like it when the stock goes down. But they are doing all the things that they need to do for the long term to turn this business around now. It doesn't help that mortgage rates are like 6, whatever 0.3%, you know, right now. That sucks. It's, you know, going to hurt open door. It's going to hurt all, you know, housing related stocks. Doesn't help that there's a war going on. Doesn't help that, you know, the housing market is basically frozen, you know, and you know, even the administration, you know, sees that and is trying to take steps to unfreeze it. So, so, but they are, this is not just like a quick flip kind of play. They are making the Carvana turnaround in real time. They have the dream team in place. They are taking the right steps. One of the things that people don't talk about is that since the time Kaz has been there, the cohorts that he's responsible for in terms of the number of houses that they buy and then sell, you know, it's, it's, you know, his October was his like first month on the job. It was like the most profitable October for Opendoor ever. And it's, it takes about six months for a home that Opendoor buys to turn around and flip it or sell it. Right. So we really aren't going to see, you know, the true measure of the new teams of the Opendoor 2.0 team success until like we come up to that six months and we're just a, just about there. So anyway, I love the company. I think they're doing the right things. It doesn't hurt help in the short term. But here's the other thing to remember. All of us retail shareholders, we're all screaming and bellyaching and complaining that oh what is no companies IPO early enough that we can't get access to them. OpenAI is going to stay private until they're basically a trillion dollar company. And so you, you can't be crying about that and then complaining when you get a chance to own an open door that is public that could have gone private. Kaz actually wanted to take the company private in February of 2025 when it was like a buck 30 per share. He could have been doing all of this cleanup work behind the curtain in private without any people complaining or tweeting at him, telling him he's not moving fast enough or whatever. But no, he decided to do it in public, and he's giving all of us the chance to own it. When you own it, you get the daily mark to market, right? And sometimes it doesn't always go up. It's only a loss if you sell it. And so I don't plan on selling the Open Door that I have. I'm sticking with it. I believe in it. I believe in the team.
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A
I had a gut feeling you were still bullish on Open Door. All right, I want to move on to Better Home and financing. I know there's another stock you were early on. It's down about 12% in the last week.
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B
Week.
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A
How are you feeling about this company?
- [05:26]
B
Well, you know, there's a cliche about AI these days that AI is never going to be dumber than it is today. And that's true. And so now when I look back on my picks from after Opendoor, I had two big ones after Opendoor. One was better. There was another one called Nextdoor Better I picked in September. Nextdoor was in December. And when I look back on those picks now, I still believe in both those companies. I still believe in Better. I believe in the CEO of Vishal. I believe, like my. I read back my thesis that I tweeted out in September. It's still the same thesis. I still believe in it. But I was too early. I was too dumb. My thought process needed some help from AI in terms of timing, kind of the bottom. I mean, that's always the trick. Are you getting. If you liked Carvana in June 20, it was a $20 stock. And now you look like a hero because it's like, you know, it's over 300 bucks. It got it to 487 last year, but in November, December of 2022, it got down to a low of $3.50. That that's like a 70 plus percent drawdown from June of that year. So timing is obviously everything. Better was too early. They have made a bunch of, like, positive moves recently. I think they're really a stealth, underappreciated company. They have integrated fully within OpenAI so that if you're in a chat now, if you're like a regular consumer in ChatGPT and you say, hey, can I get a mortgage quote for, you know, because I want to sell my house, Better has done the Work to actually integrate at the API level, to actually provide the information to ChatGPT to, to surface it to you right away. So you could actually within that chat be referred out to a better mortgage, which the main banks and the traditional mortgage lenders, they haven't even thought about doing that yet. So they have other key partnerships. Basically, they've built an AI kind of mortgage solution in a box that they can take out to sell to other people. I think they will show promise over time, but they've done a couple of equity dilutions recently, including last week, which is why the stock is down, which I, to be honest, totally didn't understand. But I still believe in the company long term.
- [07:49]
A
Okay. Yeah. It's interesting that pretty much every time you mention a new stock, there's this thing that happens on X and then it's reflected in equity markets. Stock goes up, whatever you tweet about a new company and another one I know you like Cipher Digital. I believe they started as a bitcoin miner and now they're getting into data centers. Is that right?
- [08:12]
B
Yeah, they're. I mean, they used to be called Cipher Mining because they were a bitcoin miner. Just on the last earnings call, they announced they were changing to Cipher Digital because of this shift. And they're not the only ones. Obviously there's a lot out there. Nebius has gotten a lot of attention.
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A
Hut 8 did the same thing.
- [08:28]
B
Hut 8, Iron has been a big one. So I'm in three of these names. Iron, Hut 8 and Cypher. I think Cypher probably if you, you know, I think it has the highest percentage upside because it's, you know, it's one of the small, smallest, so 100 bagger. So yeah, I mean, when I got into it in the threes, so it's, it's been volatile. But as of today, I don't know, it's 15, 16 bucks. It's sort of back to. It got as high as, I think it was like over 20 at one point, like last fall. But then all the miners have been drilled and like pulled back like significantly since November. So it's volatile. These stocks are volatile because when the economy gets hit, they kind of revert back to being tied to the price of bitcoin. And bitcoin, Obviously, with a 50% drawdown since October has taken all those guys down too. But well run, there's not enough compute in the world. None of us is going to stop using ChatGPT less in the next few months. I think it's just going to Continue to escalate up. And there have to be data centers built out by these guys, including Cypher to provide that compute.
- [09:40]
A
Some of you may not have heard this, but our partners at Public just launched something called generated assets. It brings AI into investing in a way I've honestly not seen before. Here's how it works. You type in an idea like AI powered supply chain companies with positive free cash flow or something like defense tech companies growing revenue over 25% year over year. Publix AI then dispatches a swarm of agents to that can scan every single stock, evaluate them and instantly build a custom index around your thesis. What really stands out is how clearly it explains why each stock is included. And before you invest, you can even backtest your idea against the S&P 500. So you're making decisions with real context and not just guessing. Beyond generated assets, Public lets you invest in stocks, bonds, options, crypto, all in one place. They'll even give you an uncapped 1% match when you transfer your investments over from another platform. If you want to build a portfolio that actually reflects your thesis, visit public.com openingbell that's public.com openingbell now let's get back to the conversation. Yeah, I think these are really interesting names and the energy story is gonna be the thing for years and years and years. So I know that you also have several names that you're actually on the short side of. And when you told me that, I was actually kind of surprised because this is a market that has destroyed short sellers for the last few years and it's been so robust and you know, there's been a lot of just strength in this market. To me it was, it's something that's hard to bet against. But I know you're short several software names and we've sort of seen this massive software sell off this year. Can you walk us through maybe why you're short these software names and some of these names that you're looking at?
- [11:30]
B
Sure. So I believe in the Jim Cramer line that there's always a bull market somewhere. And sort of the flip side of that is that there's always a bear market somewhere. And I think it's never a bad time to be long the names of the future and short the names of the past. But to be honest, I historically in my stock picking career have been a terrible short seller. I've been, I've been where I've been. Good is finding the Carvanas, finding these like hundred baggers, finding seeing the names that are going to play out maybe in three years and getting in them early, sometimes being too early, but I haven't been that good or you know, maybe as disciplined as you need to be as a short seller sometimes to stick with the trade. And that's on me. You know, we all have our strengths and weaknesses. Like the key thing is like knowing that. But I will say that, you know, with the explosion of AI since ChatGPT3 in November 2022, like it's, it's allowed me to become more conscious of my weaknesses and to do a better job, I think, in building models to find good shorts. And so I think the SaaS names are very interesting as sort of structural, secular shorts. And of course nobody believed that until just right off the bat in January, these names really took a hit and everybody started paying attention to the igv, which is the ETF that covers all the software names. And the thing just kept going down and down and down until about the second week of February. And then there was sort of a pause. And at that time everyone was saying, this is the saspocalypse. These names like, can't catch a bid. What's happening here? AI is going to destroy everything. Everything anthropic just puts out a blog post and all these names like tumble like 15% the next day. Oh my God, you know what's happening? And some people were saying, hey, this is too much. Oh, this is silly that these names are selling off too much. It's not deserved. They'll bounce back. This is like people getting kind of carried away on the short side or you know, just in the way people used to complain about Opendoor being, oh, these meme stocks. Oh, people are getting carried away. Retail being dumb again, you heard that kind of complaints about, you know, retail or Wall street in general shorting indiscriminately these SaaS names. But when I started to do the kind of deeper dive into a lot of these names and thinking like where, you know, I don't, I'm not. This isn't just a two week play here. This short position. I want to think about, like where are these names going to be in two years from now, three years from now? I'm not saying all software names are going to zero. Okay, first of all, I think there is like, there is some indiscriminate selling. I think like the cybersecurity stocks, for example, are, are undeservedly been sold off. I think they will bounce back. But I will say, Phil, there are a lot of names in this SaaS basket, where they are deterites, you know, like these guys are kind of, you know, heading lower and, and definitely will be lower than they are now in two years from now. And the reason why I say that is that I fundamentally believe AI is teaching all of us, the two of us in this room working on our little jobs, multiply that across thousands and thousands of companies and hundreds of thousand employees working within their companies, trying to understand how to be more efficient and what SAS did and why they got bid up and did so well over the last 15 years, is it simplified organizational workflows, whether it's payroll processes, hr, you know, sales, you know, sales automation and all this kind of stuff, you know, pushing people through the funnel, marketing, Adobe, you know, all these companies were built on simplifying a lot of these workflows. AI cuts through all of those to make them even more efficient. And so if you're selling software on a per seat basis, especially in an inefficient way, you're not going to survive. So you look at the stock chart of an SAP, for example, there wasn't even a bid for it in the second week of February. It's basically been straight down and people are saying, hey, this is a legacy player out there selling seats. AI is going to do this more efficiently. Anthropic is going to do this more efficiently. OpenAI is going to do this more efficiently. And so there are some names where I think they are in a structural pinch and the right play is not to just sort of say, hey, I want to jump back in for a 10 day trade, which is what sort of that IGV trade was in February. But to say, hey, this is going to play out over the next year or two, I want to be positioned for that. So I am short names like ASANA, Salesforce itself, DocuSign and the research that I did into these players suggests that these are kind of some of the most vulnerable now. It started to catch up at the end of last week. Citi came out with sort of like a bunch of across the board shorts for all sort of damning research for all of them, including DocuSign, saying these companies were in trouble if, if they're sort of like a one trick pony. And their solution was sort of organizing workflows that AI can organize kind of even better.
- [17:01]
A
It's so difficult to think about what these legacy players are going to do now that even in my own workflows I've been able to use Claude and Gemini for so many different things that I used to think you had to pay a lot of money to be able to do, but now it's so accessible and you know, frankly democratized. So just to repeat back to you a couple of these names that you told me you're Short on. Salesforce, Asana, 5 9, DocuSign@ Atlassian. Is that how you say it? Atlassian I'm not familiar with. Did you come into these positions before SaaS apocalypse or during or like what was the timing on this?
- [17:39]
B
Well, it was after the February kind of short term bottom and then when IGV sort of bounced from there and then, you know, it was sort of like when, when it bounced and then it started to roll over again. So we're talking like maybe three, four weeks ago. I mean I published a substack called Sasbak or no, no, it wasn't called sasbaklist but you know, basically kind of laying out the, hey, I'm short all these names. And it was sort of, you know, obviously before that that I put the positions on and I'm still, still nothing's changed in terms of those positions. But you know, one of the other things that was, that played into those structural short decisions that is interesting because I, I know we're going to talk later about, you know, Satoshi and the identity of Satoshi I've built, you know, within my Event Horizon IQ organization is like one of three companies I am involved with. But Event Horizon is sort of like a market sort of risk intelligence website that you, you know, there's a free version but you can sign up for, you know, more API access if you want it. And it's meant to be sort of a clearinghouse of, you know, what, what, what's the structural risk that's going on in the market in general, cross asset, you know, macro tech stocks, crypto. But it also gets into some specific names. And a long time ago, I'm an old guy, I'm in my 50s, but 25 years ago I did a PhD at Columbia up the street from here and I studied executive cognition, which sounds really boring, but basically was the kind of the. I studied with this amazing advisor who believed that what's in an executive's head, CEO, cfo, the management team, even the board of directors, like how they see the world, how they process the world that gets reflected in terms of how they structure their companies, how they build them, what they focus on in the companies, the strategies they choose and then obviously the performance. Right. So if you've got someone who is creative, like a Steve Jobs, but Also secretive. That's going to get reflected in the type of organization that Apple is. If you've got somebody who's like, you know, a risk taker, that's going to get reflected in the organization. But the thing was, Phil, is like back then, 25 years ago, there wasn't AI, like you had to do, you know, logistic regression, linear regression, you know, and kind of go, I'd have to send a Columbia college kid literally downtown to the World Trade center where the SEC library was to physically photocopy like SEC filings of like who's on the board and code, you know, like, where do they go to college, where they study and all this kind of stuff. Like it was just so impractical to try to put, you know, to really test those ideas. Now with AI in the last three years, you can do that. And so one of the things I've done is like build a linguistic deep kind of language model that understands people's words and what they're really saying, what are they saying behind the words? Because we can all be coached by PR people or comms people in terms of what to say. You know, they can write our prepared remarks if we're a CEO at a company for our earnings call. But when it's the Q and A session, that's when the real Phil has to step forward, right? And you sort of gonna hear the unvarnished truth of what you believe for good or for bad, right? About a tough question, do you use confident language? Do you use cautious language? Do you hedge? Are you full of yourself? Is there too much hubris? How do you process problems? How do you think about problems? You can measure all that. And so I built these models in the last couple of years to try to get at that and then obviously make some money from it with EMJ Capital, my hedge fund, and EMJ X, the digital asset treasury that I run. And to bring it back to SaaS. When I started to look at these SaaS companies, and especially the five that you mentioned, what you heard on the more recent earnings calls was an over exaggeration of how excited they were by the AI opportunity in front of them. And what that suggests to me is that there's like they're overcompensating for a known weakness that they have, right? And so they, they are trying to hype the market into getting the market and sell side analysts to believe AI is going to be the greatest thing since sliced bread for them in terms of revolutionizing their business and taking their seats up even more. And Being more successful. And a guy like Marc Benioff obviously is kind of like, he's been the, he gets excited many times. If you track all his calls across all his earnings in 25 years, he goes through these sort of peaks and valleys and he's, up until now he's been right about sort of like, you know, saying like, hey, this next trend, you know, is going to be even better for CRM and take us to the next level. But with AI right now, like, you're seeing too much overconfidence. That's, that's disguising weakness. And that language is a tell before the financial results appear. Like if, if, if you, it works in reverse. Like in Carvana's case, you could see clearly in 2022 when Carvana was going down to $3.50, the language of those executives of that team suggested they knew they were going to turn it around. They didn't have the financial numbers to prove it, but they, you could tell, you could read those words and now everybody ignored it, you know, until they saw the numbers. But the same thing happens in reverse. The language is a tell first. And right now for a lot of these SaaS names, the language is saying things are getting worse over the next six to 12 months.
- [23:16]
A
Real quick, we'll get right back to the interview. Just wanted to pop in and say if you like this content. I read a newsletter every single morning called Opening Bell Daily. I cover macro, the stock market, market, asset prices, why things are going up, why they're going down. And if you want to get that for free, you can sign up at the link in the description. Let's get back to the interview. How much of the language do you take into account now when you're building either your bull or your bear cases versus, let's say traditional metrics or fundamentals, like how are you weighing as far as when you're deciding to take a position, what the AI model is giving you on the language side versus traditional stuff?
- [23:56]
B
Well, I'll tell you something funny. Every company is different because every CEO is different. Sometimes you can have like a really kind of low energy CEO is always talks like this. He's, he doesn't give up much. And so if you're just sort of measuring him against him quarter after quarter, you're not going to see like highs and lows like you will with like a Mark Benioff, for example. So you have to control for that, right? You have to sort of normalize for a person's own style. But the other interesting thing I found is that this sort of like overconfidence that I'm talking about with the SaaS CEOs, there were hints of similar overconfidence, although it wasn't about AI, because this predated AI. If you go back and you read some of the Jeff Bezos earnings calls or listen to them from the time when he was the CEO of Amazon, and so there's like a euphoria, there's like a kind of a hype style that comes across. And so you would say, oh my gosh. Well, if you're Eric, you're saying like these SaaS CEOs are doomed because they're getting so hyped about AI. How can you say that when their style is so similar to what Bezos was, who was obviously like one of the greatest CEOs of our time? And the answer is like, yes, you do have to look at the financial performance. You do have to kind of understand like there was no risk that, you know, after Amazon grew to a certain, got to a certain escape velocity and they had, you know, billions of assets and distribution centers and cash flow that they were relying on. Like his a little euphoria was okay, was, you know, was tolerable for an Amazon. So when we get into maybe talking about some of the private credit names though, for example, you're going to see the reverse of that. There's a case where the language is a tell in private credit and the financial metrics are getting worse too. And so you do have to look at both in tandem.
- [25:57]
A
So let me ask you about that. The private credit signals you're seeing from the AI models that you're running, what are they saying that you're also seeing in the financials?
- [26:07]
B
Right. So right now in both EMJ Capital, which is my hedge fund as well as EMJ X which is my digital asset treasury, and we're in the process of doing a reverse merger with this NYSE listed company called SRX Healthcare. So their ticker is srx. So when it, when it finalizes, EMJ will be, you know, basically trading as a public company as a sort of like multi asset hedged digital asset Treasury. So you know, I am really excited about it because you know, it's, It's a Gen 2, I think, whereas a microstrategy or a bit mine inversion is gen one single asset kind of levered bet on kind of one digital asset. Whereas we're building something different. So but right now in both of those entities, MJX and MJ Capital, we are structurally Short, like a, like a bunch of these SaaS names and B, a bunch of private credit names. And so that's when I was saying before, you know, I always want to be kind of like investing in the future and shorting the names of the past. Private credit has a big comeuppance coming to it. And again, it's the same thing that we see in SaaS. You see a lot of justification if you turn on CNBC or whatever, Bloomberg or Fox Business right now when they're talking about private credit. People that have a stake in seeing private credit continue say it's overdone. People got carried away, like, oh, the pessimism about this is too much and they'll be just fine. There's just a couple of bad apples in terms of bad loans, but they brought in more money than went out the door last quarter. For example, I'm here to say I've done the work, I've done the analysis, I've gone through the SEC filings of all the big and small private credit publicly traded companies and there is a problem. And the problem hasn't kind of come come to a tip just yet, but it likely will at the end of this year. So we're still about six to nine months away from kind of the real, you know, bad stuff happening. Is it going to be like another GFC 2008 financial crisis, the big short kind of thing? I don't know is the honest answer right now. And I think anybody who says they do, there's just too many dominoes that still, you know, have to fall and, you know, too many, like, you know, is the government going to step in? Are they going to, you know, get involved and prevent something bigger, you know, something worse from happening? For example, like there's so many scenarios, but if you ask me today, I'd say there's a 25% probability that by the end of this year there is going to be a major financial calamity, a contagion type of an event where it's not just, you know, a couple of names in the private credit world that go under, but there's contagion where it's bleeding over and affecting some of the banks. It's not just a US problem, it's an international problem. Because these guys in private credit, they have been living high on the hog for over 10 years now. Money has been flowing in, a lot of it from outside the US A lot of it from sovereigns, you know, major pensions, you know, pensions in Canada, pensions in Europe, all over the world. You know, because the returns were, you know, too good to be true. And what happens when returns are too good to be true? Lending standards get lax and problems arise. And so the big warning sign right now in the world of private credit, it gets kind of arcane, just like it was like back in 2008. And we have to learn some new terms. The term that people need to learn now are pics. Payment in kinds. So if I'm a borrower from a big private equity shop, like an Apollo or an Aries or KKR or something like that, I go to them with my business. I'm a car wash company. I need some money to expand my business. Please lend me some money. Okay, here you go. Here's some money I got to pay you. Interest, cash interest every month or whatever the terms are. If I'm tight on one particular month, I might go to you and might say, hey, Phil, cut me some slack this month. Instead of me paying you the cash, let's just book it as a pick payment in kind. It's basically an iou. You add it to my total of what I owe. Right? Okay. And you book it like a payment to you. But cash doesn't happen. And I say to you, I'll make it up next month or the month after. Don't worry, I'll catch up. It's going through a tough time right now or something. Iran war just started or whatever it is affecting my car washing business. The problem is when you go through all these SEC filings and it's difficult to do, but AI does make it possible to do this. And you look at the loan level for all of these companies, you see two things. You've got about 20 to 25% of, of companies across the private credit sector that are in pick status. Okay. So they are, they are leaning on the IOUs right now. That's a problem. The other problem is that a lot of the same companies like Eric's car washing company from West Texas, you'll find them in multiple private credit shops. Like, like you lent it to me, plus Matt, you know, the producer kind of lent to me as well. Right. And so it's. So if I go under, it gets reflected in your book and it gets reflected in his book. But more importantly, if you decide to mark down the value of your investment in my car washing company next quarter and it comes up in your 10Q, he's got to pay attention to that. And because he's got an exposure to the same investment and you just took a public markdown of it he's got to reflect the same thing in terms of the value of his investment in my car washing business too. So it doesn't play out on a day to day basis. Remember I was making the point about being an investor in Opendoor and how hard that is for retail because every day you know the value of Opendoor, you might not agree with it, but every day the stock market's making a verdict and telling you what the price is. Doesn't happen in the world of private credit in terms of those loans and those. So that only gets updated once a quarter. It's going to be interesting when we come up to May, June and all these companies start to have to report and the details come out in terms of those filings. If you start to see some things being marked down, that's going to be a problem for the whole sector and prices are going to go lower. What's also interesting to think about is just that, you know, like everybody again to go to language, okay? And remember the overcompensation and the SaaS world. Same thing is happening right now in the private credit world. If you hear some of the Presidents and the CEOs of these companies talking on the earnings call, they talk about how one referred to the whole concern about private credit as Pebbles and he sort of chided one analyst as focusing on Pebbles. Whereas we, the, the management team at this company, I think it was Apollo, we're focused on boulders, you know, you're just focused on Pebbles. It's sort of trying to sweep everything under the rug. So again, I think it's, it's, it's a sign that they're overcompensating. They're trying to, you know, Blue Owl, which I'm short, you know, they, they sort of proudly announced in one of their recent letters to shareholders where they said like one of their tech tech funds got redemption requests for 43% of the assets. They gated it. They only gave back 5% which they have the right to do. That's fine. But 43% of people wanted their money out and couldn't get it. They were gated. But in this letter they were trying to say everything's fine. In fact, we had more inflows than outflows last quarter. And yet when you start to read the fine print and the footnotes in that letter, the only reason why they had more inflows than outflows is that they counted dividend reinvestments from, from existing capital in there, which a lot of people didn't even realize. They had a choice and they got gated. So part of the inflows that they counted towards and tried to show off as evidence that people still had confidence in them as a company were basically forced inflows. There's going to be more shoes to drop. I think there's still time for the government to step in and help the. The problem is treasury saved us during the great financial crisis because it was a bank problem. And treasury ultimately has responsibility for the banks and the Fed and the Fed and the Fed could do certain things like open the discount window to kind of keep the banks going. Nobody has that same authority over private credit. So it's more of like a cross regulatory body that is going to have to take control. And the risk is that, you know, government's not always the fastest moving and so they usually wait to see the crisis before responding to the crisis. And so that's what does worry me.
- [35:21]
A
This is extremely troubling to hear and it's funny because you said you were going with your AI systems all through the SEC filings. These are things that are essentially depicted in the Big Short as Michael Burry going through them by hand in some capacity. So it's amazing what type of research you can now do because of these systems. And I will say also when you turn on CNBC or even read the Journal, most of the comments about private credit the last six, eight weeks are shrugging it off as far as, hey, it won't be systemic, there's not too much to be concerned about. Just focus on earnings and the rest of the stock market and markets in general. So generally I think the sentiment is almost agnostic to what's going on in private credit. Unless you ask people that are really in the weeds and they might have a little more robust of an answer. But the bearishness I don't think has really been spoken about too much, which is why this is very troubling for me to hear the work you're doing. And yeah, it sounds worse than most people think if all this comes to
- [36:30]
B
fruition, but it's, it's not. I don't mean to paint it like this is the next big financial crisis. It's. At the end of the day it's only a 25% probability that I put on like something really bad happening. But, but that's a very high probability. Like, like most of the time we would only, you know, Nassim Talib, you know, like he made a whole life out of being like this black swan predictor. Right. And kind of Selling sort of insurance through his fund against that. And that was talking about like basically 1% probability events happening, like nuclear bombs dropping and all this kind of stuff. So 25% is too high. But you know, in that industry, private credit, there are, you know, good lenders and there are really bad lenders. And so it's not, I don't want to paint everybody with a broad brush, but there are problems. And the way that it happened, in the great financial crisis, there was this company down in Orange county called New Century Financial that was one of the first ones to go under, you know, with bad mortgages in. It was a sort of like spring 2007 now took another 18 months. You know, spring 2007 took another 18 months till like September, October 2008 for the real crisis to explode. But that first event, that first failure was kind of like the canary in the coal mine. And I feel like we, you know, we're kind of seeing the Blue Owls get a lot of attention. You know that, that's the name again. And again I'm short, so I'm talking my book here. But like, you know, if you do get a failure, there's just like all these unintended consequences. Like remember in the great financial crisis, like I don't know if it was Afternoon Financial or somebody else, but all of a sudden like a couple of weeks later you heard like, banks in Iceland were failing. Banks in Iceland were failing because they had taken on way too much risk in, in mortgage backed securities in the US So there's just all kinds, you know, it's opening a can of worms like when, when, when you start to have one domino fall. And so that's, and it takes that kind of crisis and seeing these events play in real life, I think for the media and investors to kind of really kind of focus, focus their minds on what the problem is until, until that happens, they can just slough it off totally.
- [38:39]
A
And you know, I've been speaking with investors. I have investors send me stock picks all the time, right? And they pitch me ideas for our best ideas club with opening bell and multiple investors in the last several months, maybe two months, have pitched KKR and Blackstone as two stock picks that they really liked. And you know, who knows, they're not my picks. We'll see how they perform. But you have a lot of advocates still for the private credit industry and financials more broadly. So this, even this conversation, it pushes back on a lot of that and a lot of the pockets of bullishness that I've been Seeing in my conversations. But Eric, before we run out of time here, I want to ask you about how your AI system matched up to the New York Times findings of Satoshi. Right. So the Times had this big report and they essentially did all this reporting research. They had their best people on it. They said, Adam Back is Satoshi. But you did a similar analysis with your systems and you came to a different conclusion. And I would love if you could share that.
- [39:47]
B
Sure. So remember, I built it for CEOs, right. For earnings calls, you know, based on my PhD research from a while ago. And so I hadn't really been thinking of using it for, you know, figuring out who Satoshi was. But obviously, you know, last week it was, you know, there were a couple of days anyway where it was all people could talk about was this John Carrie Roux, who famously kind of unveiled the problems at Theranos with Elizabeth Holmes. He was the one who was saying, I've got my man, it's Adam Back. And I didn't know much about it. I didn't know about all. There are about 12 names that are the most popular names of people who were around at the time of forming of Bitcoin in 2009 that typically get mentioned as possibly like the Satoshi. And it might not even be, remember one satoshi, maybe could be a combination too multiple people. But I listened to Cary Roos daily podcast last week as well, and a couple of things like, jumped out at me because he mentioned how he had heard an interview that Adam Back had given where somebody had confronted him, you know, with this idea that, hey, are you really, really Satoshi? And. And Cary said, I could see like his cheeks got flushed right away and his. His hands kind of shook. And that was a tell. And I remember it reminded me exactly. I could feel it in my bones. It reminded me exactly of Elizabeth Holmes and kind of some of the tip offs that I got from her that were, you know, I found later were evidence that she was lying. And so, you know, that made me curious and I really delved into it. And so, but he did. He took a very kind of, you know, reporter kind of. Personal kind of approach to solving this problem by doing things like counting the number of use of dashes or dots in Adam's writings versus Satoshi's. He noticed that Satoshi had a few British spellings and Adam was English. And so. And he sort of put together this kind of like grand conclusion that based on his analysis and he went and he found somebody who knew machine learning to kind of Back it up. He felt like this guy was the most likely guy. And so it struck me that that was. I respect him and obviously everything he did at Theranos, but it sounded like a very human oriented way of solving this problem. And when we. We live in this world where AI is available and, you know, more complicated models are available. And it made me curious whether the models that I developed to kind of detect these CEO speech patterns, whether it could, because it gets that sort of deeper kind of language patterns going on behind the surface that the CEO is not even aware that he or she is using. Maybe that could be a useful tool to kind of try to solve this question. So first thing I did was test it against Ted Kaczynski and the Unabomber because I wanted to see, like, okay, here's sort of like a test. If this deep language model can find a lot of similarities between these two, then that'll make me confident that we can throw it at the satoshi problem. And it did come back as like a perfect match, like Ted Kaczynski's writings sort of match the same tonality, the same kind of emphasis on similar patterns, similar language structures that the Unabomber. The Unabomber had in his writings. And so then I said, okay, well, let's throw this at the satoshi question. So I got the top 12 candidates that typically get kind of mentioned and pulled in collectively across those 12, 830,000 of their own words and compared it to satoshi's entire corpus of writings and basically said, you know, okay, among these 12, who are the most, who are the closest in sort of style, language, tonality to satoshi's own writings? Because I hypothesize that that person, you can always throw in a British spelling here or there, throw in a dash here or there to try to throw the scent off from you, but language patterns, you can't do that. And so surprisingly, and I put this out on a substack piece over the weekend, Adam back finished fourth out of 12. So he was kind of. He was 300 times less likely to be satoshi from his styles than the. There was a dead heat for first, actually. So for those two, they were only 7% each away in terms of being like a. A good match for satoshi. And so those two were Peter Todd, who was a developer at Bitcoin Core around the time Bitcoin was created, and Hal Finney, who a lot of people have believed he was satoshi. Unfortunately, that's a tragic story. Hal developed ALS in 2009. Eight months after the launch, the public launch of Bitcoin. So he still, or Satoshi still participated actively. But in 2010, Satoshi's writings decreased noticeably at the same period of time when Hal's health and motor functions were being diminished. And Satoshi gave his last public forum comment in December of 2010, and his last email to a couple of buddies in April of 2011. And a few months after that, Hal died of ALS. But interestingly, Hal and his wife Fran have always believed in cryogenics. And so hal was the 20th person at a clinic in Scottsdale, Arizona that had his body completely frozen at minus 196 degrees. And so if you say, who is Satoshi? Our models say it's one of those two people, but one is alive and is denied he's Satoshi, and one is cryogenically frozen right now. So if you ask me, Eric, who do I believe? I think the fact that these lost keys that Satoshi controlled are now worth $78 billion, that's a lot for any living person to kind of never touch. So my hunch would be it's Hal. Now, there's always a chance that it could be somebody outside of that top 12. In fact, when I published my substack piece, I had one of the smartest people I know in tech read it and email me right away and say, did you try this person or did you, you know, did you try that? He gave me like four other names. And I was, I was coming here today, Phil the CEO. So I haven't had the chance to do it. But, you know, I'm curious myself, and I'll go back and I'll, I'll do that comparison. But out of the top 12, I can, you know, I believe definitively that Adam Back is not the person. In fact, you know, the Satoshi is, is dominantly from the language style, American, you know, for sure, solidly in the majority American. There were some British isms, you know, in Satoshi's writings. Maybe that was the second person. Maybe it was somebody again trying to throw off the scent. But that's what, that's what, that's what I found.
- [47:49]
A
Wow. One of the New York Times is, I would say, big evidence pieces was that they thought he was British, which pointed them to Adam Back. So this system you built is actually pointing to the opposite evidence.
- [48:02]
B
And it's a danger of relying on human, you know, gut instincts because it was the reporter's belief that because he saw evidence of, you know, British spellings, that this person, you know, therefore Must be, you know, British. You know, it's more likely to be British than American. But it was the analysis with the AI of the underlying language patterns that said, hey, this person is way more American than they are British in terms of how they speak and so forth. And there were, there were other things as well, like Satoshi spoke with a lot of constraints and a lot of sort of hedging words and phrases which both Finney and Todd did as well. Adam back not so much. So anyway, it's fascinating and it's fascinating that it's something that I built it for CEOs and earnings calls and it goes sort of beyond that to the
- [48:53]
A
Unabomber and it's unprotectable. I mean, think that you can build essentially language analysis that can be used for detective work, but also stock picking and investment research and sell signals. It's really unbelievable. Eric, where can people find you online and follow your work?
- [49:14]
B
So I'm on xericjackson, the substack that I mentioned before, which has all the SaaS, apocalypse thesis, the private credit, Pebble's thesis, my long thesis as well. I've been using the AI to find some long ideas too. That is eventhorizoniq.substack.com and so the hedge fund is called EMJ Capital. The Gen 2 digital treasury is EMJ X. It's going to be part of SRXH very soon. My hope is. And then the third website you should check out is eventhorizoniq.com where it's sort of a clearinghouse for, you know, what's going on in the market, how much risk is out there, what should it be paying attention to?
- [49:58]
A
You are one of the busiest guys in finance, so I appreciate you taking the time. Eric, we'll have to do this again soon.