Full Transcript: Weekly Wrap — Four Guests on AI, Markets

Jim Paulsen, Brent Kochuba, Anthony Wong, and Tom Hancock on Markets, AI and Options Flows

Jack: Welcome to the Excess Returns Weekly Wrap. I’m Jack Forehand and back from his dark retreat. we’ve, we’ve got Matt Ziegler.

Matt: Back from How did go?

Matt: it was great. It was great. I was in the, I was in the middle of the desert. There was a pink moon. I dunno if you know about the pink moon, but we had a moon.

I don’t know. It took away some of the, the stars in the California desert, but at the same time, it was really cool to see a giant full moon rise over the desert landscape and, pink, because it’s like early spring and stuff is starting to blossom. That’s where the name comes from. I got to play Nick Drake’s Pink Moon.

And observe a pink moon drinking wine in the desert with my wife. Doesn’t get much better than that.

Jack: That sounds better. I thought, I thought we were talking about some sort of Aaron Rodgers type dark retreat, so, which would’ve been a whole different situation. Like it’s some sort of cave or something where you’re pondering the meaning of life or something like that.

Matt: The best, the best part was like, I didn’t have any instances of like, nothing. I had no scary desert experiences. ‘cause the weird thing, have you ever been to the desert before?

Jack: No.

Matt: So like you sit still and five minutes goes by and then the desert starts to be the desert again. Because like everything’s different in the desert.

It’s like being on a Martian planet, being out like in Joshua Tree. So a couple of times my, my wife had like ventured a little bit further into the park and off like the property where we were staying. It’s like, you know, you’re sitting on a rock. And five minutes goes by and you’re relaxed and it’s nice.

It was like 80 degrees with like a great breeze blowing on it on random occasions. So it was really nice to be outside still. But she, she’s like, well, this time I went outside and I saw a coyote, and this time I saw rattles stake. And I’m like, all I’m seeing are jack rabbits and like crows and like the occasional road runner from my little book perch next to the house.

But I’m making noise the whole time because yeah, I don’t know. I’m not, I’m not fighting nature. I’m not doing that.

Jack: Well, you had more excitement than I did, but, I guess we should get into the clips here. ‘cause we got a ton of them. We had some great guests this week. we had Jim Paulson, we had Brent Kochuba, we had, Anthony Wong from, who’s the manager of the T. Rowe Price Science and Technology Fund. We had Tom Hancock from GMO. So we’ve got, we got four different guests. We got tons of clips. So let’s get into it. And the, and the first one here is Jim Paulson. And I love, the thing I love about doing this We Monthly podcast with Jim is, Jim has truly unique data every single time.

Like all the charts you’re seeing on Twitter and stuff, nobody has the stuff Jim has. Here’s Jim talking about the Walmart indicator, which is, which is flashing something very interesting right now.

Jim: I published this several years ago, for the first time, and, it doesn’t go back super far, just for lack of good data though on it. But I, I kind of, the idea being I, this is true, i, I, you know, recessions when they come upon, sort of show up first in the lower income part of the distribution, now that part of the, that part of the income distribution is always less well off, if you will.

They’re always closer to recession than anybody else. And so naturally, if things start to get a little worse, they’re gonna feel that quicker than the rest of the economy. And I think, you know, how do you pick that up? Well, one good way, or one way of getting some indication of that is look at a ratio of, of a low, low income per, retailer to a high income retailer.

Sort of the differential of what’s going on in, . A retailer like Walmart that services mainly low to middle income consumers is not, that’s the only ones, but a, a lot of what they do compared to a retailer that serves mainly high-end retailers. And if that differential starts to change, then it is sort of an early peak that things are changing in the economy on the ground.

So what this chart shows is the ratio of Walmart stock, relative price of Walmart stock to the S&P Global Luxury Retailer Index. And. You could see when you look back historically, the, big surge there was back in the 2008 2009 crisis, the financial crisis. And Walmart’s, this relative ratio was an early indication of that coming.

and then it also was kind of an early indication that things were improving before they were really notably true. And actually, I think it might be the next chart if you lay it over like credit spreads, here. The red line here is indeed that same relative price of Walmart stock to the global luxury retailer.

But the blue line is, is basically, the credit spreads in the, in the US economy. and you can see they haven’t done well here of leap, but up until just this cycle, you can see that basically the, what Walmart’s relative price traced out was credit spreads to the United States. We did, it was an.

Early read on, on, in some sense, on credit stress in the economy on it, did a pretty good job of that. Now, that has not worked here in the last few years, which often happens with indicators. You, you find them, they start working really well and then they blow up as far as the being able to predict credit spreads.

And I think the last time I published this was before, right before this, this latest surge in Walmart stock or during it and, and not picking up credit spreads, haven’t responded at all. But, there’s still some other things that it does a pretty good job at. And maybe what’s happening today, if you look at the next chart, is it’s not suggesting so much that we’ve got a credit spread problem in this economy, public debt problem, if you will, a private sector debt problem, or overall.

But we may have a private credit problem, which we’ve kind of heard about a little bit. And here are the, the Walmart indicators inverted. It’s in the red. It’s just on inverted scale, so you can see it’s been heading straight south. It’s now about as bad as it was in the suggestion of the oh eight crisis.

But what I’ve laid on top of there is the Bank of America’s private credit proxy equity basket. And you can see when, private credit, when that equity back hit south, it suggests some stress in the private credit industry. And maybe that’s what Walmart’s picking up this time, is it’s not a, . A public credit problem, but a private credit problem that’s going on.

And if that’s the case, it’s a little discouraging here ‘cause it still says there could be more of that left in terms of private credit problems. But what I’m, what I probably published this for this last month was the next two charts. and the next chart lays the Walmart indicator, if you will. and I took this back to 1990.

It lays that Walmart relative price indicator, which is the red line on inverted scale. So when it’s going down, Walmart stock is outperforming, and I’ve laid that on top of annual real GDP growth in the blue line. And again, not a perfect indicator by any stretch of the imagination, but typically though, when the Walmart indicator goes south, real GDP at a minimum tends to slow its growth rate.

And we’ve got an indication right now of recession out of this Walmart indicator. I personally don’t think we’re gonna reach that, but I do think it’s another thing to put on the pile of, we probably got a slower economy coming and there’s pressure and this is the voice of the lower and middle income part of the economy that says it ain’t good.

Out here we got, we got, we got some issues. We’re feeling this a little bit. And you know, in the past when that has been spoken. It generally is caught up with real GDP.

Matt: Can I just say I was at a Walmart, like outside of Joshua Tree in California. That might be one of the sketchiest Walmarts I’ve ever been at out in my life.

And so to come back and start catching up on these episodes, and one of the first things I get to is Jim Paulson talking about the Walmart indicator and the lower leg of the K and why. That tells you a lot, Jim. I have seen. Exactly what you’re talking about in real life.

Jack: And it is so smart because if you think about it, like obviously the, the ratio of how Walmart is doing relative to luxury retailers tells you something.

Like it tells you something about what’s going on in the economy. And, and what’s interesting is in the past, and you can see in the chart that we, we put up, like in the past, this has been a sign of, of bad things. But Jim was talking about, and that’s the other thing that’s important, is like keeping in mind that these new, these indicators are all nuanced.

You know, Jim talked about the idea that in the past has been a bad sign, but in this case, like if you look at 2008 and say we’re at the same levels, well obviously. The debt situation, like the consumer debt situation in the economy is very, very different now. So it doesn’t mean we’re about to go into 2008, but it’s just interesting as, as a signal of, of what it’s telling you.

And, and as we went on the clip, we kinda looked at some other charts and said, you know, here’s some other things in their correlation to the Walmart indicator. And you’ve seen, like in, in the past when the Walmart indicator has flashed, some other bad things has happened in the economy. So that doesn’t mean it’s gonna happen now.

But it, it’s just an interesting indicator that’s completely different than what else you’re seeing out there.

Matt: I also think this was interesting, and this is a question for Jim for another time, is basically how that’s evolved over time. Because the other thing that’s a reality, especially like you go back to 2008, or if you were to look back before just the existence of Walmarts that are there in the world today, the existence of Amazon Prime that’s in the world today.

You have all these things that service different levels of the consumer and pull people into that mix. There’s a real evolution that goes on inside of this chart too, or inside of these images that I think is an interesting part of the story.

Jack: Yeah, in the future it probably won’t be the Walmart indicator, like when, when, you know, low end consumer starts doing something else, we’ll have some other indicator that’ll come up because who knows?

And we’re gonna get into the AI and these other clips and who, who knows what AI’s gonna mean. But, prob probably a bunch of different stuff, probably a

Matt: bunch, a little bit. take me to, to, Brent. Brent had this great clip, I think on oil and the vix.

Jack: Yeah. So, Brent, we just recorded this right before, you know, Brent, I, I sit down with Brent every month and we look at.

What’s going on in options flows behind them are behind the scenes in the market. So the idea of not what people are saying, but what they’re actually doing. Are they buying puts, are they buying calls? And what does that tell us about the market? And so I, I, you could watch the episode, it came out the day before this one, if you wanna see what his take on the current market is.

But I like to pull some evergreen clips from it. And one of the things I thought was interesting is this idea of oil in the vix. And so what happened is this crisis is being driven by oil. So that changes everything in terms of oil’s, correlations with other things. So here’s Brent and I talking about that idea.

Brent: So this is the oil vix correlation chart that really ended with, and this was true through the rest of April, the fact that oil hire meant VIX hire and vol hire. and so it was really, you know, such an interesting, position there. And also on this point, we were talking about this analogy of when March quarterly expiration rolled off, and then last April we had this giant market drop, right?

Remember the, the tariffs sort of like the, the, the. Tariff fears really kicked in 2025, and the market dropped so substantially, the analogy worked out perfectly. And, and, and Trump even, you know, caused oil to go to one 15 with some of the tweets and the escalation oil went up 15% in the equity market.

The next day was flat and it was like, holy cow, like this analogy was set up to work so well. And it was sort of like, you know, what the heck just happened? Like, market didn’t move. It was really pretty fascinating. And that goes back to the Taco idea where people just weren’t, weren’t buying it, I guess.

Jack: It’s interesting, we have gotten a little bit away from the idea of oil driving the bus. Like last time oil was driving everything, like the vixen oil we’re moving together, the market was down, oil was up. And I dunno if people are getting a little more comfortable with where the level of oil is, even though it’s still high or, but it is driving things less.

But obviously having said that, if we have some bad news and the oil spikes, you know, quickly, it’s gonna drive the bus again. Yeah. You know, and I had put in, in my conspiracy corner the 2008 crash where oil super spikes and then you have all these other cascading issues. Right. And so. being correct on the idea that realized vol starts to move was right to a point.

Brent: we were given these higher oil prices and the equity market just really didn’t, and, equity vol just didn’t really, move much. So looking forward here in, into where we are, this oil equity of all correlation seems to have, at least for the time being snapped. And so the red line is just the correlation between VIX and USO, which is, my proxy for oil.

Historically, these things really aren’t really, you know, related, right? It’s like on a normal day, I don’t care what oil is doing, and I’m not gonna use that for my VIX proxy. If there’s a credit market crash, oil’s probably not doing all that much. this is the latest last five data points here in, in black.

And, you know, a couple days ago we just had such a massive VIX in, in vault collapse. that’s what this day was. I believe this was the seventh and the into the eighth. So there is still somewhat of a relationship here, but that’s really cooled off now. and here is mid-March when we’re talking about the correlation, right between, this is the march OPEX effect basically, and this is oil in blue and the VIX is in candles.

And then what you see here now is after the alleged deal was announced, we had this big gap in oil, right? But equity vault just got, I think you call it shanked. and. Now you see there’s this big divergence there, right? Right between the two. And oil is holding up. And I think oil is smarter in this situation, in that the oil prices have a better beat on what the geopolitical situation is.

Jack: So I, I just think this is very cool, like this idea that whatever’s driving the crisis often when you have a crisis becomes correlated with the other major assets. so like oil is going up, it’s driving volatility. So the VIX is going up with oil stock market’s going down with oil. But if you look at a long-term correlation chart between oil and the vix, there’s nothing there whatsoever.

Like it’s irrelevant, but it’s just interesting when you get these crisis, what’s driving the crisis? You know, can be, can become correlated and, and all these things can change.

Matt: I had somebody tell me, this is like financial crisis era, and they were basically like. They talk about certainty and uncertainty, like they’re two different things.

What you really wanna look for is what people are certain that they’re uncertain about. And as I’m listening to you explain Brent’s clip, and I’m looking at Brent’s clip before I’m going, this is what this is. When people are certain that they’re uncertain about what oil means in the rest of the world, it’s gonna show up in the VIX and that correlation’s gonna happen.

But as that starts to wane, as we start to declare the war is over, whether or not that’s even true or whatever’s happening in this, in the political framing of this entire thing. Is that as that starts to wane, it’s gonna have to spread back out, and then we’re gonna see something new that’s gonna catch on with the VIX next because I, this is kind of what it is too, right?

Like,

Jack: or we might even see oil catch on with the VIX again, because as you know, the war’s over you were, you thankfully we’re away for all of this, but the war’s over, the war’s, not over the war’s over again, the war’s not over. We’re probably gonna be doing that about 250 times between, between now and when the war’s over.

And you’ll probably see like if, if one of these is a major escalation, you know, if like, if a plant in Saudi Arabia blows up or something, you’re obviously gonna see oil and the VIX get correlated again.

Matt: Yeah, so this idea that you have this certainty about the flavor of uncertainty that’s driving the spook, that’s when it gets concentrated in the vix.

When that mitigates, it comes back down and I guess it’s just high alert for consensus uncertainty again, for what pushes it back up, and then if it’s transitory or not, we, so let’s,

Jack: move on to Tony Wong and yeah, to Tony is, is really interesting. He, he’s the manager of, as I mentioned before, of the T. Rowe Price Science and Technology Fund, which is a $12 billion fund.

it’s a big fun, quite the

Matt: track record. I mean,

Jack: we, yeah, yeah. I’ve looked at this clients for

Matt: my entire career. This thing has

Jack: been, yeah. So it was really cool. We gotta talk to him like, but we were talking at the beginning about this idea of AI intelligence and the cost of intelligence dropping to zero.

So here’s Tony talking about that.

Tony: Yeah, so I think that’s, you know, like take a step back. Like what, what, what is this kind of breakthrough that we’re kind of seeing is that, you know, you have the ability to drop the cost of intelligence to pretty much zero, I think you think about it, right? Like cognition is becoming really plentiful.

I think that it brings up the average to be very high. And as a role, I think you take a look at like different parts of tech, right? Like software for example. If you think about it, software’s essentially, been designed for humans to use, right? Like driving in, clicking, typing in operating software.

And I think we’re gonna have a shift in terms of how we’re seeing like agents, you know, software be designed for agents. and I think that’s, that’s a pretty big unlock and. You think about like what companies and enterprises have been doing is that David, you know, spending on software and having, enabling humans to be more productive and that cognition is like you paying probably somebody to, you know, input data into a piece of software.

And that’s the cognition piece. But that was, that’s compressing to the soft, the token now. So, you know, I think that like now to get a similar. Intellectual combination. You pretty much ping Azure for a, for you know, Anthropic model or OpenAI model. And I think that’s gonna be probably what’s gonna happen.

And just like thinking about like, you know, your everyday life, how many times do you call a restaurant? They can’t pick up ‘cause they don’t have enough people. Right. So an agent now can, has been, you know, I’ve been calling restaurants and increasing, they have agents picking up the phone. So I think that’s an interesting, like just a small little.

Little sliver of what it could be, but I think I’m, I’m more optimistic that, you know, it unlocks the economic proximity of like labor, you know, plus, plus productivity equals to economic output. So we as a team do a lot of quantitative. Analysis, also sentiment analysis. We look at valuation, we look at technicals, we look at, fundamentals.

And so I think it’s a multifaceted approach, but I think there are signals, you know, like here, like in video trades at, you know, sub 20 times earnings, you know, for the growth. And then Micron’s trading out four or five times earnings. and you’re, you’re seeing like tremendous, demand and, and number revisions off.

And people aren’t really buying it because. Markets has never seen anything like it, you know, semi investors and market in general. When you’re seeing massive inflection, there’s usually like a, a lag between the numbers, believing it to some extent. And so here, I, I do think there’s a lot of skepticism.

Jack: Yeah. I think this is one of the most interesting things with AI is like intelligence has existed inside human beings. Now we’ve got this cost of intelligence coming to zero. As he talked about agents, AI in general, a as intelligence becomes something that other than human beings can do.

It’s just really interesting to me to think about like, how’s this playing out? As you probably saw when you watched the interview, like he’s very into agents. He thinks agents is the next phase, and agents is gonna be a huge, huge revolutionary.

Matt: What I, even though I don’t, don’t feel like don’t know this with con great confidence here, I feel like there’s parts of this I wanna like push back on it, but I think it’s the way he’s framing it, that I’m pushing back on it.

Because the takeaway, and correct me on, I haven’t listened closely to this entire interview yet. The relationship between like humans and the agents. Like the people doing some of the work, but then the agents that are helping, like at the margin or around all the corners and edges and cracks, it’s, it’s this interaction that he’s talking about that’s driving the productivity gains, right?

Jack: Yeah, I think so.

Matt: So this idea of like humans and agents being integrated and that’s where the productivity gains come from.

I could actually see this across lots of different industries. ‘cause I could see that in my life as an RIA doing like planning work. I could see this in our work doing like the podcasts. This army of agents that we have that help us with all these little aspects of productivity and we get the best things out of each other.

Jack: And the question becomes, I think the interrelation between humans and agents is gonna be the key thing is like, how far can the agents go in terms of what they can do? Where’s that line between like how much of the agents are gonna be able to do and how much the human’s gonna add value? And that’s gonna totally vary based on what the task is, what the job is, what the industry is.

But I think that’s the idea is like I think agents are probably going to do much more than you and I think they’re gonna do right now if we look forward like a decade or guess.

Matt: Completely agree. And I think it’s a matter of, to invoke the great Rory Sutherland is this is a way we are gonna raise the threshold of Crappiness.

It’s gonna be harder to have a crappy experience getting a reservation at a, you know, at a hotel or for your rental car or at a restaurant, or. With the appointment with your CPA to get your taxes done. It’s like all these things, those crappy experiences, we’re gonna raise that threshold and we’re probably gonna raise it higher than we’re, we’re imagining possible right now.

Which is not a bad thing.

Jack: Yeah. The other thing I liked here is this idea of, there’s a lag between an inflection and everyone believing it. And it made me think about, like, I was at this presentation last night where Robert Hagstrom and Michael Mauboussin and Chris Mayer, were all presenting, we’re we’re talking about compounders.

It was kind of the general topic. But the idea is like, that’s a, in some ways, the way compounders generate their returns is people underestimate the sustainability of how long like their moats can last. And I was thinking about the same thing here, like when we get this disruptive technology like ai, we’re all probably underestimating like this inflection, how big it is, how long, all that stuff, we’re probably all underestimating it.

And, and so I just think that’s interesting. Like people inside of it, like the, those guys with the compounders and him with AI probably see this. See the duration better than you and I see,

Matt: yeah, the, the compounding of progress. It’s one of those things and just like, just like all great growth investors know is the under reaction to good news.

So as that floor comes up, as those results snowball forward, that becomes harder and harder to unseat in system because what are you gonna go back to? You can’t just go back to the before times and extract the same economic premium you were able to extract in the before times.

Jack: So this next clip is from Tom Hancock from GMO and, they wrote a really good paper on AI and they’re, they’re high quality investors, so they wrote a paper on AI from the perspective of like a quality investor, which is sort of different from the perspective of a technology investor, which I thought was really cool.

But he, here’s him talking about this idea of cash and how ca important cash is in terms of ai.

Tom: That’s one of the things that led us to think about this layer approach is that I basically, from the top of the layer, a company gets revenues and then its investments or a CapEx or expenses are the revenue of the layer beneath it. So I’m an application. I get revenue from an end user. I pay a fee to.

Get my compute. and then the compute, has to invest in, you know, Microsoft, they has to invest in CapEx that will go when they have to pay. the LLM, they also have to invest. In either directly or through the LLM, like OpenAI is spending a lot of CapEx that’s going to Nvidia, so NVIDIA’s revenues are open, AI’s CapEx, and OpenAI has the CapEx to spend because they’re getting money from Microsoft and also from just.

‘cause they’re spending in advance of that revenue. They’re getting a lot of money from outside investors of course, but in equilibrium this is gonna be funded all flowing down from the applications, not from just external investors who are bootstrapping the system today. And then that NVIDIA’s spending money, it goes to TSMC, that goes to apply materials, et cetera, all the way down.

and I think that’s an important way to think about it because. For any company, however much they’re earning now, their revenues are only as durable as the spend from the person above them who is buying their products. And as you do get further down the layers, you do lose visibility in what’s going on above you.

So it’s a, it’s a harder way to manage a business. Perhaps sometimes. You touched on something that’s really unique here of this boom relative to, say the.com boom, which is this idea that a lot of this is being funded from cash. I mean, do you think that makes this inherently like more stable? because the big players are spending their own free cash flow, which is something like the.com.

Tom: That was much more, I think, driven by debt. Yeah. Yeah. And I, I think it absolutely does. Although to a limit, it doesn’t, insulate you from all the risks. But yeah, if you think of companies like Microsoft and Alphabet investing, they’re not gonna stop investing. ‘cause the Fed hikes interest rates by 50 basis points if that were to happen, right?

They’re playing a long game that’s based on the fundamentals and they’re not borrowing money to invest it. So there are a lot of kind of macro shocks, like they’re not gonna stop investing. At least immediately because the Strait of Hormuz is closed, for example. So that, that is, a real difference that you have long-term committed strategic investors.

a couple of caveats to that. What is, while those have, they’re very deep pockets, they’re not infinite pockets, and we’re seeing some of these companies get down to a point of sort of break even on cash flow. And so. The grade of growth that we’ve seen over the last few years, we are getting to the point where they will either have to take on debt or slow down their growth.

I think. Frankly, both are possibilities. there are also some other things to think about. I just mentioned the straight of four moves, like, and right now we’re getting outside capital. So Middle Eastern investors are, are a big, supporter of things like Stargate and OpenAI and stuff. So there, there’s still funding risk out there.

. I’m saying that just to sort of, I don’t know, modulate my answer, but to your basic question, yeah. I absolutely think it’s a lot of a safer, safer situation than the 99, 2000 tech bubble in some ways. You know, we talked about that as a bubble, of course, in hindsight, but we think about a lot of the business models that sort of were thought of then actually did succeed.

Ultimately, they just had a very long period in the wilderness first.

Jack: So, yeah, there’s a couple things here. One is the idea that, first of all, this, this is very different than the.com, in that the money that’s being spent, at least initially, is coming from companies that are generating a lot of cashflow and are spending that cashflow.

This is not a debt ridden thing, and that changes the nature of this whole thing in terms of the way you think it through.

Matt: Yeah. Pulling money off the balance sheet to fund the things you want to do. This is like a, a proper household example now, right? This is like, you didn’t put it on the credit card.

You didn’t cash out of the house with a refinance to go pay for the thing. You were like, no, no, I saved up the money. It’s in the bank account. We’re gonna go buy it. And in this case, it’s not just like. I dunno, putting a swimming pool in the back or something. It’s, it’s appropriately funding the right type of education for like the kids.

It’s that type of a, that type of an investment off of the balance sheet. And that is a market shift from a lot of, a lot of the cycles we’ve seen end really, really badly in the past.

Jack: Yeah, and the other idea was how the cash goes down the stack. And that, that was very interesting to me is like it starts and it’s not really, ideally when it’s working, it’ll be like the consumer pays cash, it’ll work down to the LLM and eventually it gets down to Nvidia.

Right now it’s not working that way ‘cause the consumer’s not paying nearly as much as everybody else is spending. But eventually it’ll work that way. But it, the idea that like. It gets a little more risky and variable as you get down. it’s, it’s sort of a different way than I had thought about it, but like at each step you have a little bit more risk and maybe like the NVIDIA’s at the bottom you get more variability because of that.

Matt: And is that where, like, is that where it matters that we have companies at the size that these companies are because they’re able to absorb that risk in a different way?

Jack: Yeah, I think so. I think that definitely, I mean, Nvidia obviously is very equipped to, to absorb risk at this point. you know, this is not like the debt ridden fiber builders of, you know, of the late nineties, like Nvidia can, if, if NVIDIA’s revenue goes down, NVIDIA’s not gonna be like in, in financial trouble here.

obviously the stock will go down, but they’re, they’re not gonna be in massive trouble. But it did, like you, you kind of think about NVIDIA’s like the most solid. Of all the companies that at least some people do, and, and I just thought about it. I thought about it a different way when I saw this, when I kind of thought about Nvidia is like at the bottom of a stack of cash that’s sort of flowing among multiple levels.

And like if those multiple levels break down, like it’s problematic for Nvidia.

Matt: Yeah. And without those being like leveraged, this is the key part here. It’s like stacking healthy balance sheets on healthy balance sheets. Yes, stuff can still go wrong. You can still have down quarters, you can still have down stocks, you can still have headaches.

But it doesn’t undermine, it doesn’t break us. It doesn’t blow the whole system up. It can still, right.

Jack: Having said that, the things are so strong right now. I mean, the money, the spend is so strong. Like there’s more demand than Nvidia can meet. Like this is not a near term risk to anybody. I don’t think what I’m talking about.just interesting to think of like as you get down the road here, where they sit relative to everyone else and this, this podcast is eye-opening from that perspective for me.

Matt: Really cool stuff. Take us to Paulson. You got another great Paulson clip here. Cudo,

Jack: yeah. Yeah. Again, unique charts from Jim, but this, this idea, what’s interesting is we’re seeing a lot of indicators right now that you typically would see at the beginning of a bull market.

And, you know, most people would not argue we’re at the beginning of a bull market right now. So I just thought that was interesting. So here’s Jim talking about that.

Jim: Yeah, I just think, I think the overall thing we’re dealing with today, you know, you think about our mindsets and whatnot, you know, we’ve got a, a pullback where we’ve had correction in some of our markets, like the small caps, the nasdaq, you know, full on 10% plus correction. We got not somewhat close in the SP, but, and whenever there’s a pullback, a period of time, and now we’re still in the situation where we’re unsure the catalyst for how long it will go on.

We get this feeling, well, you know. A bull market’s three and a half years. It’s gonna be four years by October. It’s getting a little long in the tooth, you know, is could this be it for a bear? And I think, not for a couple reasons, but one of ‘em is, I’m kind of amazed when we sit here three and a half years into this bull and the, the feeling by a lot of, a lot of people that, oh boy, you know, bear risk is pretty high.

You know, valuations are. Are very high earnings have been very good. They are they gonna, can they continue to do that? Those kind of things that really scare people. I’m seeing a lot of normal sort of indications that look more like the start of a new bull market than they do the start of a bear market.

And just to run through this quickly, you know, one of ‘em is just consumer confidence on Main Street. The dates here are listed on this consumer confidence Index going back to 1960 and. Where we are today, and the dates I also have listed there, one reason they’re in green is because they, most of those mark the beginning of a new bull market, most of ‘em Mark what You’d see confidence on Main Street like this when you’re pretty darn close to being done with a bear and you’re gonna start a bull.

We don’t typically have confidence at this low of a level, when we’ve been in a bull, bull market. But we, we do. And I, and. Confidence historically, if I go back to 1960 and I look at the impact statistically of what rises in confidence do for the S&P 500, the numbers are just outstanding. In other words, if you look at every month when confidence went up versus every month when confidence went down, how did the S&P do the, the difference in total return is something like almost 20% during annualized when months go up.

Versus something like 8% when months go down. And my point about that is we’ve suffered from the 8% when confidence goes down most time, if we get into a period where we could raise confidence for a period of time, that could be a powerful, positive force. Yeah. We, we’ve talked about in previous episode, it seems like low in increasing is actually a good place for confidence in terms of like a bull market.

Right? That’s a good point. It’s, it’s already, maybe you could argue it’s already past the low. Right. And, and, . It, it low and increasing with the potential to increase. And I think that’s where we’re at. so you could think about can earnings go up? You know, can multiples go up higher? Well, one thing that can go up is confidence.

And we’ve been playing, I would argue we’ve played this entire bull without any animal spirits. And maybe we could get some animal spirits playing before it’s over. And if we do, that’s, that’s a real positive bullies force.

Jack: Yeah, he had like, I think he had like eight or nine indicators in the podcast. So definitely, it’ll be in the links, in this episode.

So watch it. But the first one was this idea of confidence. and that’s something we’ve talked with Jim a lot about, and this idea that like low confidence is actually a bullish thing. And, and we sort of got into it in the podcast, like the idea of low and increasing confidence is an even more bullish thing.

So it, it is kind of counterintuitive, you know, you think like when everybody’s confident about everything, that’s not necessarily a great time for the stock market. And when there’s low confidence, that sometimes could be a good time for the stock market. As you saw on Jim’s chart,

Matt: I already said it once, I’m gonna say it again.

This is the great gift of good growth investing. It’s that under reaction to good news. So what, what’s interesting and granted, there’s a lot of assumptions in what the good news could be here that. I, and I’m sure a lot of people watching this don’t feel 1000% confident, let alone a hundred percent or even, you know, 70% confident in.

But that under reaction to those good news is like the bedrock for the proverbial wall of worry that we’re looking for stocks in the economy decline.

Jack: Yeah. And also obviously what’s going on politically plays into this, like people are less confident in a political environment. We’ve got a war right now.

All, all that plays into it. But it’s just interesting like that. That’s when, like to your point, expectations are always low. we’ve got all this crazy stuff going on. Expectations are low and you sometimes end up in a situation where the market actually does a little better than people think. So you and I are not gonna predict that right now.

But, nonetheless, it’s, it’s possible. So I always, like Jim always brings something unique to it and he always brings kind of a balanced take no matter what’s going on, which I think is good.

Matt: Boy do I love an upside surprise.

Jack: Exactly. Let, let’s, let’s head back now to, you and I talking about stuff we have no business talking about.

and move on to the JP Morgan collar. because, neither one of us has any idea about the JP Morgan collar, but I think it’s very interesting because it, it’s getting more and more pressed these days. It, it’s basically a huge JP Morgan fund that has to do a trade at the end of every quarter. And, and the idea is that, that the strike prices of that options trade, they do can be a magnet, they can pull in the market.

but it doesn’t always work that way. So here, here’s Brent and I talking about that.

Brent: The big thing was the JP Morgan collar trade. Everyone was talking about this thing the day we blew through it, but I don’t think a whole lot of people were talking about it. like we were at OPEX. in mid-March, we tagged that level perfectly. you know, if we go back to this chart, 6,500, you know, was the area roughly those puts.

So we go right through that strike and then we get a little bit of positive news and clearing of that strike. And there was just a massive dip rally, right? Right. At that, at that quarter end position. And so, you know, that was one thing I think that if you were aware of that position, weren’t there, like a lot of people that were kind of calling the JPMorgan thing into question this quarter, because I think there was a massive rally like on the last day of the quarter and it like moved it away from the magnet or something like that.

Jack: Didn’t, didn’t, I see like some controversy on Twitter around that. I, I, I think what it is, is that people assumed that we would pin straight to that strike and there was some positive news that day. And so what ended up happening is we, we really moved up and through that strike. We rallied from, you know, a percent below it and then just kind of finished higher.

Brent: And so what you, what you ended up having here, if you think about that position, is the market makers were short, the 64 75 puts, I believe was the strike. And so really anything above that made them money. Right. And, and I mean, their hedge generally, but just as a, as a function of that specific strike in that position, looking at just that options position.

That position expires worthless. Right? And so you also had the news, so you just get this kind of negative gamma rally. And I think a lot of people are saying, well, it doesn’t count because we didn’t pin that strike. But we’re pinning, we’re talking about pinning in the context of, you know, 2% equity moves with tweets going out left and right.

And so the fact that we sort of gasped back up and through that strike, it when we’re at 6,300, you know here, right? And you are positioning for the possibility of a huge move like that based on that position. You very easily could have made some money. And those options were very cheap to trade.

Right? I going into the end of the month, so I think some people kind of nitpick about, about it. And, and the point is clear. It’s like, well how do you express a rally back into that move? Like, would you bet on a $10 wide fly, right? Where the market closes $10 outside of that strike, you lose. That doesn’t make a whole lot of sense when volatility is just going bananas.

Right? So I think the, . I think you could tell people who lost money betting on how the market would react to that position is basically how it was like if you had calls or call spreads, you did great. If you bet on a pin at that strike, you probably lost. And, and then you said, you know, this is garbage and you throw your towel.

Jack: And I, I also think people have to realize, like everything in markets is probability. Like we, we talked, you know, we, you and I talked about options. We talked to technical analysts, you’ve got fundamental analysts, macro people like you can all have your views and put the view together, but if, if Trump tweets, you know, the war is over and we’ve developed super intelligence.

Like the market’s gonna go up a lot, like irrespective of what everyone else has analyzed. So like, all this stuff is looking at probabilities and, and looking at the range of things that can happen. It’s not necessarily like, nothing’s like this is the line in the sand and this has to happen no matter what.

Brent: Yeah. And on that point, if you were playing the JP Morgan dip and you just bought, let’s say futures, and the market rallied up a lot, you know, even if it went through that strike, you’re probably even happier that it went through that strike. Right. And so you’re not gonna complain on Twitter. If you, you know, put, put on a, a trade that bet that we’re gonna pin there and you lost, then you’re, you’re gonna be mad.

Right? So the expression of the trade is also another important thing. And, and you know, we don’t talk about that necessarily here, but on the point of probability, the way that you trade also changes the probabilities and, and payout structures. And so, you know, that’s another, I think, interesting part of the equation.

But, you know, did, did the JP Morgan position take part or lead to the rally? I think so. We talked a lot about the fact that was a level to watch going days into that, it did rally through, it did rally through that strike a hundred percent. So, you know, had we not gotten a good tweet and we were at 6,300 on that day, or, or decent market move.

That strike may not have come into play. Right. And we would’ve possibly closed below it. So we needed some positive news to get the momentum going up. But then once you got that momentum, you have your target, right? Your target is sitting there a percent above. And so I think that’s kind of the, the critical thing here.

Jack: So I, I thought this was a bigger point in terms of indicators and how you use things. You know, we just had recent, recently had Katie Stockton on as well, and we were talking about the Death cross, and you know, indicators like that.

And the thing is, nothing gives you a hundred percent confidence in anything in the market. That’s just the way it is. Like everybody who’s good at anything, whether it’s, you know. Macro guys who are outstanding or trade or chart guys or options traders, like they, they think in probabilities. They think, well, if we get close to this JP Morgan collar, it’s likely, or there’s, there’s a pressure towards these strike prices.

That doesn’t mean, and what happened in this case, and this is why we were talking about it, is on, on March 31st, Trump tweeted something about the end of the war. And basically we were near the strike price know, and it was no longer a magnet. Basically, the market closed up. it, it touched that strike price, but then it closed up on that day, and so I, I just think that’s the more important context here is to think about like, whenever you see anything, it’s not like a hundred percent set in stone.

These are just things where everybody’s playing in probabilities.

Matt: What I love about Brent explaining this and explaining just this trade now, for how many quarters have we been talking about this with him?

Jack: A long time. I mean, almost since we started doing the OPEX effect. We’ve been talking about this.

but it gets more and more like the, the regular media picks it up more and more and more It gets talked about more and more.

Matt: So what’s fascinating is how we, he always is very careful to frame this is like, this is just like a magnet. This is just this thing that needs to happen. This is the equivalent of stuff.

Anything that has to happen on a calendar basis like this. Is going to produce like weird little bottlenecks in markets and they’re gonna tell you they’re gonna help test or measure the health of the market by like how stuff passes through this bottleneck. And I think even when this isn’t giving you necessarily new information about the story, you can insert Brent’s commentary on this and to just seeing like, what’s the broader health.

Of the market, of the economy around it, of the way this is going by, how strongly did leading up to and leading past this thing did this magnet pull stuff into like its vortex just to pass it through because it’s got now another quarter till it’s gonna go. I, I think this is actually a really interesting and insightful snapshot for understanding where we are.

Jack: And for me it’s really good just to know when I see something happening in the market, it’s good for me to understand. Like why it’s happening. And sometimes there have been quarters where the market kinda gets sucked in, you know, by the JP Morgan collar. And it’s just, it’s good to know I’m not trading it.

I wouldn’t know, I wouldn’t even know to put flyer or whatever trade I would have to put on to, to do that. But nonetheless, it’s just, it’s just good to understand it. So that’s what I really like about talking to Brent.

Matt: I wanna talk more about, and I think this is from Tony again, comparing stuff to the, to the dot coms.

Can we

Jack: go, yeah, we ask this all the time. you know, we’ve kind of talked about it before with the fiber build out, but we, we ask people all the time to talk about. What we’re seeing now versus the.com. So here’s Tony, while I’m talking about that.

Tony: I think that’s a great question. I mean, you look at like the 2000, tech boom and bust there, like I think it was a very different setup. Like one is that when they’re laying the fiber down, like utilization was never more than 20%. It was really a build it and hope they come. And then, so that’s number one.

Like GPUs right now are at max capacity. Like you have a GPU, you have a business essentially. You got some GPUs you can stream together, you can sell it out like free, immediate. And even the old gpu, the pricing. You know, has actually held up really well and you don’t, you’re not seeing declines there, which is like pretty, pretty wild, right?

Like a 10-year-old GPU is still like renting out for, for similar amounts. And so, one is utilization, two is like a cost curve. You know, fiber laying down like, you know, telecom, that was like a declining cost curve, like as in the more you did the cheaper it got. Here is like the opposite, you know, inflate cost curve.

Like, you know, chips are becoming harder to make. HBM is three times the wafers as a normal dram. And, and so the fact that we have like, you know, very rational supply in terms of like, it’s really expensive and really, and it was really expensive and these tech jumps are not easy. You know, that’s where I think we have a different setup.

It’s like, it’s like oil. You know, if oil’s super easy to drill, everyone can do it, it’s gonna be too much. But if oil’s super far to drill, that is gonna be like pretty, pretty rational. And there’s not that many players, it’s gonna be scarce. So I, I think if it’s like the abundance of compute, is becoming more scarce in some ways versus what it was like, you know, the fiber build out in 2000.

Does that make sense? Yes. Yeah, it does. Yeah. So you would lean on the side of, if you talk, listen to someone like Jensen, he’s telling you like the demand is, is really, really strong for a really, really long time. You know what, what people on the opposite side will say was like, fiber builders would’ve told you that back in the day too.

Jack: But it does seem like it’s more real this time. Do you, do you agree? I mean, you are seeing anytime. Data centers don’t up, they immediately get, utilized. So I do think the utilization is a big point, and these are companies that I think a lot of the demand is funding by free cash flow versus, you know, kind of what it was in tech level where, you know, company like essentially have a.com behind it.

Tony: And then like, you know, the with no customers like this is, this feels a lot more real. And I think that you are seeing the. We’re all using ChatGPT and all of our lives as far as language models. Right. And, and it is, you can see it, you can use it versus like the internet was like very much so TBDI think in terms of what they’ve had at the time.

Jack: So there were a couple points he made here. First of all is like the high utilization of the infrastructure that’s being built now, like whatever infrastructure they can build is getting used.

Like it’s basically a hundred percent utilization. Like whatever Nvidia can pump out is, is getting used at the beginning of the.com. That was a little bit different. Like the fiber wasn’t getting a hundred percent used. They were kind of, he said like, build it and they will come type of a thing. So that is a very, besides the debt thing we talked about before, that’s another difference here is right now.

And who knows that might change in the future, but right now. Like everything, the capacity utilization is basically a hundred percent.

Matt: This whole idea of thinking about stuff from, you know, the demand being there, to your point, Nvidia makes a chip. It’s not sitting on a shelf for six months. It’s not somebody going like, I don’t know what to do with this.

It’s people going like, you’re late, basically, even if you delivered it on time, like, I’ve been waiting for this. I want this and I’m putting it to use now. That’s a very different thing, building in demand of that strength at this part of this cycle, because whatever that growth curve looks like, when you have demand that’s strong, that’s gonna carry you to a certain point.

And especially when you bring it back to the point of like the, the cash stacks too.

Jack: Yeah, the other thing with the fiber is like, the fiber is useless until it’s connected at both ends. So, you know, to, to some extent there was a lot of work to be done on the fiber to build it out before it was useful.

Like, these things are coming off NVIDIA’s, you know, plant and they’re basically getting installed and they’re getting used. So it’s a very different thing. And the other thing that I thought was, and this is something I wanted you to comment on because you’re much smarter than me, but this idea that the, the declining cost curve versus the increasing cost curve.

So I was asking ChatGPT about this. ‘cause I, I wanted to figure it out and it’s like, the idea was with fiber, it was more investment. Led to lower marginal costs, which led to being cheaper over time here, more advancements leading to higher marginal costs and escalating spend. So I, I thought that was just interesting, this idea of a declining cost curve versus increasing cost curve.

I hadn’t heard that before.

Matt: Yeah, I, I thought that was really insightful too. . There’s, there’s so many tricky parts of this that I think are still hard to think about, and it’s interesting to get really smart investors to tell us how they’re thinking of this, because one of the ones I always go back to is the fax machine, and I think about how the fax machine, the classic example is that with, with fax machines, this is how.

One. I think that one of the easiest ways for somebody my age at least, to understand network effects because if only I have a, a fax machine, it doesn’t matter. Like I can’t fax anybody anything. I need Jack to get a fax machine so I can send Jack a fax and he can send one back and forth. And now we’ve started a network effect.

But the demand for that and the way that’s gonna come is other people going like, I want part of this network effect and I want part of syncing up so that I have this new mode of communication of data, information processing, batching, whatever. And like what we have going on right now is basically like the network effect is already so strong.

Across plugging into Claude or plugging into being able to go to chat GPT and do this stuff where it’s not like we’re adding incremental fax machines and then we’re gonna get to a point of saturation and then the costs are gonna come down. Like we don’t see where that part is yet. I’m looking for people.

I’m looking for people like him to help explain what those cost curves are because it does genuinely feel like this is a different type of, network effect than we’ve seen in prior examples when there’s been this type of infrastructure build out required to create, to create this end product.

Jack: Yeah.

And that, that’s what’s great about what we’re doing in the podcast is we’re able to get a views from different people. Like Tom Hancock is a quality investor. Tony Wong is very deep in technology. We get to talk to all kinds of different people, and it’s just good. There’s no right answer to this. I mean, nobody knows how this is gonna play out, but it’s just interesting to get it from different perspectives.

And this, this next clip gets into that as well. we’re back to Tom Hancock. And, you know, one of the things that we’ve been seeing here, obviously is a, a massive amount of CapEx from the hyperscalers. but we wanted to talk about the idea, and they, they touched on it in their paper, is this idea of growth CapEx.

Versus maintenance CapEx, which is the idea that once all this is built out, it’s still gonna have to be maintained. There’s gonna be some level of maintenance CapEx that’s gonna be required. So here’s Tom talking about that.

Tom: Yeah. So, imagine you’re Microsoft, you’ve been spending all this money and building up, this Azure cloud computing capability, and you have GPUs and CPUs and networking chips and all that. And if you were just to keep your present capability of compute going. This stuff depreciates, and you can argue about what the schedule is from accounting point of view or in the real life lifespan of these companies.

But say every five years, you’re replacing it. If you just said, oh, we have enough compute now we can actually do everything we need to. Your CapEx would be. It’s just kind of a fifth of what you, your value of the account stuff now just to re replace it. But these companies are, right now, they’re growing CapEx, like 60% and virtually all that growth or more.

And all that growth is adding on new capabilities. So if you look at what the CapEx of these companies are today, we’re splitting between a steady but being diluted level of just. Keeping things running and this investing for future capability, that’s the growth CapEx. now if you’re Nvidia receiving that CapEx, actually most of what you’re receiving is the growth CapEx.

So if Microsoft were to say inflect a little bit down and say, no, we’re not gonna grow realistically, but we’re gonna grow a little bit less. We don’t need to grow as quickly as we were. We wanna keep balanced with our cash flows or whatever, then that would have a much bigger impact on. Companies down below where in the, in this, in these four layers where they are getting more of the growth CapEx and the maintenance CapEx from the people above.

which speaks to kind of the volatility these people talk about, like the whip of the economic cycle, right? Who’s at the end of the whip and who’s sort of close to the handle. As you go down these four, four layers, you’re getting close to the end of the whip, and then for better or worse, you see a lot more volatility in revenue.

Jack: This growth or maintenance cap back is so interesting to me because I think it’s one of the big questions right now. I mean, we don’t expect these companies to keep spending at this level probably for a really long period of time, but like how much the maintenance cap back is gonna be, once this thing settles down seems like a very interesting question and a question that’s gonna impact these companies a lot.

Tom: Yeah, and I think one, it’s actually. There’s actually been a fair amount of controversy, say over the last year about what the right depreciation schedules are and whether their companies are not depreciating assets, but the fact is, the youth useful life of these chips is fairly long. They just, they do wear out, but it, it takes a while.

So that’s been one of the things in the industry is generally you can have fully depreciated assets that are still. Useful have still useful lives, like people are still using Ampere chips, right? There’s just so much demand that even if they’re not as efficient as the new ones, you still get a lot of utility out of them, and so.

that, that’s a good thing from the people who are buying this stuff. They get extra, extra usage out of it. It’s a little bit of a, I’d say risk for people lower down in the stack in that maybe the rate at which the, the level maintenance CapEx, the rate at which you just need to renew your current capacity is a little bit less than what you would think if you just looked at depreciation schedules and financial statements.

Matt: I’m fascinated by this maintenance capital, concept inside of this. Because if there’s one thing that’s still not clear to me, it’s like, okay, so you keep on building this stuff, you keep on doing it, and then I go back in my mind to, I, like, I think about the DeepSeek thing.

I think about some of the, some of the other advancements we’ve seen since DeepSeek of like where you get more use outta these chips and I think about are we replacing these things every five years? Like is this like my washing machine that is just inevitably gonna die randomly on me on like a Tuesday and I’m gonna have to go out and buy a whole new thing Is not worth replacing the one thing inside How to think about maintenance capital in this?

That’s blows my mind.

Jack: That’s been the big question, is the useful life of these things. And he mentioned it in the piece because it’s been longer than people think so far. Like a lot of those old GPUs are still being used, and that’s a bad thing for Nvidia because there’s gonna be less growth, growth CapEx, but it’s a good thing for your consumer at the top because you know it is keeping costs down.

So. Like, and, and there’s been all kinds of stuff about, you know, there’s been podcasts about that there’s fraud going on here and that they’re, they’re overestimating the useful lives and all that. But e irrespective of that, it’s, it’s the key question right now, which is how long are these things actually gonna last and, and how often are they gonna have to be replaced?

And that’s something we don’t know yet. And that’s also a function of what NVIDIA’s building at the new end. Like if obviously what they build is some massive step function, then people are gonna replace it. but it’s just, it is something nobody knows. But it is just really interesting to think. Like this is not just a growth story.

Eventually there’s going to be like, these are not gonna be, and we will get into why I’m wrong about calling these capital light companies before in, in another clip. But this isn’t gonna be a thing where like, they’re gonna spend off this money and then these companies are gonna go back to being what they were before.

Like they’re not gonna have CapEx spend, there’s gonna be maintenance CapEx spend and we just don’t know what it’s gonna be yet.

Matt: Yeah. Or, or what we’re gonna get out of it because it might just be the case that we’re. I don’t know. We have, we have energy constraints that are placed on the use for some of these things.

We stopped hyper scaling at the rate, we’re hyper scaling now we’re making better use outta of the stuff that’s there. So now we treat it differently and we start to pay for it differently. There’s lots of ways for this to play out still. I, I love how little anybody knows about where this is gonna go. I genuinely,

Jack: we’re knowing little is our strength, Matt.

So this is like we, if, if people know little, we’re, we’re like right in our sweet spot.

Matt: Great. In our sweet spot.

Jack: So let’s, let’s move on to Tony Wong again. and, and this is, we were talking about the, the different layers of the stack, but we were also more interested in talking about software as well, because software’s obviously in the news right now, these software companies are getting killed.

So here’s Tony talking about that.

Tony: I think that, you know, there’s been this whole debate of like semis versus software, right? And when does it go to the application layer? The tricky thing is that like you have new incomp, new players come into the application layer, in the form of large language models, and they’re, what they’re doing is like very different than what the existing software companies are doing.

And so. There’s a real innovator, it’s a laptop, essentially a software, you know, for example is like you essentially use, it’s designed for humans versus this is like agent agentic. And so can you make that transition? And so I think it’s more important that you’re the platform and not just a feature because you’re a feature of like, you know, the cost intelligence is cost of coding, the cost of software creation is like plummeting, right?

And so you, you have to have like data, data. Gravity. You have to be entrenched. There has to be regular foray probably. So it, it just makes it so that I think where it shows up in the application layer can be look very different. And then like the unit economics right, is just super different now, in terms of what existing application software companies are used to charge, right?

They’re used to charging per person. But now you have agents that. It’s really hard to charge and you gotta charge outcomes base, perhaps, and that’s like inflationary because the customers expect that to be passed on to themselves. And you can think about like, you know, Adobe, you know, it’s an interesting debate because like, you know, they’re, they, they essentially, you know, have like, me nearly like they’re the dominant place they were before.

‘cause people will creating content right? But like, you know, if you use it t you could essentially create, generate images for unlimit images for 20 bucks a buck. Right. Whereas like, there’s innovators with I think Adobe where they have to essentially like charge button token, you know? So, so you’re, so it’s just like a really hard, I think, and it’s now that they can’t make this transition, but, it just like.

Then the value creation could come from a different set of companies that have a different set of unit economics that they, that they need adhere to. I’m curious, just since you mentioned software, do you think the whole idea that AI is gonna disrupt software, do you think that’s being overblown right now?

Jack: I mean, obviously the software companies have been, many of ‘em have been killed by this. Like, do you think that’s overblown or, or do you think it’s a case by case basis? Like how do you look at software in a, I think there’s definitely, it can be overblown the short term, but it does feel like. A lot of, there will be companies that make the transition, but they’re also, I think, the disruption risk is very real.

Tony: And, and, probably most software companies, because essentially like, I think there’s a few different things. I think the first kind of stepped down valuation is probably just like being a little bit too overvalued from 21, you know, zero interest rates. And then these, these golf capabilities are also like.

A more mature like uptake. So when I think about investing, I also think about like, where are we invest from adoption, right? And so, you know, software operate the world for, you know, good 20 years. And so clearly it’s just like they’re more mature and now we have this terminal value question. what do agents do?

What does AI do? I think now you also have cust companies that. Across the enterprise that we’re used to just paying more for software every year. Maybe it was like, oh, this is another year. We’re gonna pay 10% more. You know, probably ‘cause we’re hiring more people we’re just used to like, it cost inflation and, and now it’s just like soft work.

And so, but now you have this new disruptive technology that you have to invest behind. So now it’s like, oh, like we need to. Really safe here. So, and we’re also, you know, probably over higher in many instances, so we’ve got to like rationalize. So, so I think we’re seeing some of that, like is it a macro, but I do think that, you know, the, the software companies, they’re not gonna go away, but it’s just like, are they gonna be relative winners within and lead technology, you know, in the technology index over the next 10 years?

And I think most of that is just like, they are more mature. As a, as a segment. And, and I think you’ve got just a, just new way of doing things, delivering intelligence when you think about software, right? It’s really said a conduit to deliver intelligence in action, right? So now only have agents that are, you know, driven by large language models that, are doing that.

And so, and at a much lower cost, I think.

Jack: So I, I like this idea that, I thought you would like this when he said you wanna be a platform, not a feature, like talking about software. So I thought you probably have something interesting to say about that, but I think that’s a good way to look at it.

Matt: I like the way he’s doing it.

I’m gonna take this very, very specifically. Like you go read all the Ben Thompson stuff, like go spend your proper time on like Eckery with this. But yeah, you wanna be a platform, you wanna be in a space where people are coming you to you to use the different things that are there to use the features that your platform grants access to.

As a, as a host of different features, you want to basically go to the mall. You wanna be the mall where you’re leasing out all the different spaces and like, oh, you can go over here and visit, I don’t know, KB Toys, and you can go over there and get some sneakers at the Foot Locker or something, and then go to the food court.

You want to have all that stuff nested on your platform. If all you’re doing is trading in the wares of the features, you’re gonna find yourself in a funny spot.

Jack: Yeah, that kind of like a, Salesforce is a good example of a platform, like if you use Salesforce, I used to, I don’t anymore, but like there’s all these plugins you can put into Salesforce and like if you’re a company that’s plugging all this stuff into Salesforce, like that’s much harder for AI to disrupt that.

But if you think about the actual things that are plugged into Salesforce, those are kind of your features. Like those are gonna be easier to disrupt, like any one of those individual things. So I, I just thought that was a good way to think about it, like thinking about it from that perspective.

Matt: Yeah, and this is a really useful framing of like the software problem that you have right now, or you know, with the companies that you’re seeing getting hit the hardest by this stuff, where it’s like, oh, can AI just replace you?

And it’s like, yeah, you’re just another shoe store in the mall. At the end of the day. Now the good news is there’s still a lot of sneaker heads out there and they know what they’re collecting and there’s a good market for these stuff. But you’re gonna have to transition if you’re in that space or understand what’s your actual moat around software that can just come in and replace all your features and give somebody the same basic experience.

There’s more defensibility in some of these names I think they get credit for, but that platform example is wonderful.

Jack: The other thing I liked is the idea of being charged for outcomes instead of seats. And it seems like that’s where this is gonna have to go. I mean, obviously with agents doing all kinds of stuff, but like if you, right now, if you use something like Salesforce, you pay per seat for it, but they’re either gonna charge for like usage tokens or something like that, or based on outcomes.

It seems like something like that has to be the way pricing goes in the future and in a world of ai.

Matt: Yeah, I’m sure it will. And I think this is one of those hard lessons from like, you know, from marketing where you have. You know, broader brand related stuff, and then smaller direct campaigns, and you have different things in both worlds where it’s like, are we just trying to make sure everybody knows when they think of Coca-Cola, they think of the, you know, the cozy polar bears and they, you know, all the, all the positive things come to mind and the brand recognition, or are we actually doing like direct response copy where we’re gonna pay for a result?

Both of those worlds are probably gonna emerge. They’re gonna emerge in a parallel fashion, and we’re just gonna see more and more ways to approach pricing that’s inevitable. It’s going on all the time in a million industries, no matter what. We’re just about to see it in software for probably the first time.

Jack: So our, our final clip gets back to Tom Hancock and back to what I alluded to before, which is, I’ve been asking this question on the podcast forever. What does it mean that these hyperscalers are turning, you know, from capital light companies into capital intensive companies? I was wrong to ask the question because it’s, it’s, I’m thinking about it in the wrong way.

So I asked Tom about that.

Tom: Amazon is sort of the famous one for investing through the income statement and sort of in an accounting sense really never, at least not consistently earning very much money at all. but it’s the same time being success, fantastically successful and growing. Of course, Amazon’s also a fairly capital intensive companies from the warehouses and stuff, even before you got into AWS and cloud computing.

And we have with cloud computing that is. A case where we’ve sort of seen this movie before, like that was the critique of AWS and of Azure when they first came up is, oh, we thought these were software companies and they have super high gross margins and now you don’t. ‘cause you have all this like dirty crimey hardware that collects dust and you have to replace.

And I, they’ve proven that can be a good business. Like capital light is great, but. Capital heavy. If you’re getting a high return on that capital, that’s, that’s fine too. So I think the question is not so much, are they capital intensive and is that therefore bad businesses? Okay. Yeah. They’re getting these.

Things that are capital intensive. And is that a good business? A-T-S-M-C, right? Very capital intensive. Been a great business for a long time. now nearly these are the exceptions rather than the rules. Like most capital intensive businesses aren’t as great. but there is, something to the moat that Great scale provides in these capital intensive industries that, I mean, you can.

If the need to invest is really, really big in dollar terms, that means there aren’t that many people who can do it and say if it there’s a real economic value to being it, to it being done, you aren’t able to get high returns out of doing it. So I’d say we’re not. Overly worried about just the fact that capital intensity is high.

I think when you do see in capital intensive industries is the lead time between when you make that capital investment and when it pays off can be high, and that. It does present risk, but that’s also true to your point about r and d spending, whether it’s in tech or pharma or any of these areas where they’re r and d intensive.

You’re talking about payoffs decades out. Yeah. A lot of the things you try don’t pay off when you’re thinking about the return on capital and not investing, you’re sort of kind of playing the odds that on average it’ll deliver high return. In some ways, the CapEx that they’re doing now, it’s a little more certain.

I think it’ll get a return. Maybe it’s. The timeframe isn’t so certain, but the eventually, I think is pretty certain it’ll be used. So again, we’re not, we don’t see that as a huge negative in and of itself, capital intensity. Yeah. To your point, the question I should be asking is maybe not the changing nature of these businesses, but the question I should be asking, is there, there investments in RD in the past paid off massively, and the question is are, are there investments in this tangible assets?

Are they gonna pay off similarly? Yeah. I mean that, that’s really the question that determines what happens from here, right? Yeah. and I think just some extent they won’t pay off as much as the initial r and d. I mean, we’re sort of seeing kind of survivorship bias here. Like lots of people trying to start internet companies, a lot of them went nowhere.

A few of them, achieved escape velocity and because they’re the few that skate velocity to get to where they are today. They were, they were lucky, they were skilled, they were in the right place at the right time. They got these reproducibly high rates of return, so they’re not gonna see quite that again.

But I think they are in a position where they will can get well above average, exceptional rates of return on this investment. So not as great as the past, but still pretty darn good, I guess would be our forecast.

Jack: So this, this comes from Michael Mauboussin and the reason I recognize that I’m wrong, and, and it’s, it’s something I just, I just, it was like a light bulb when we interviewed him, is this idea that these companies have always been spending, they’re spending way more money now, so we have to put this in the right context, but they’ve always been spending a ton of money on their business.

They’ve just been spending through the income statement, it hasn’t been going on the balance sheet. And so it’s not, it’s not totally fair to look at these companies and say they’re completely different companies now. They’re just spending in a different way. And accounting is treating that spending in a different way than it did before.

Matt: It. The Amazon example is almost too good here. And basically, and when he says it’s from the income statement, what he’s saying is they’re expensing r and d. So instead of research and development going into something that gets capitalized over time, they’re literally taking it as a one-time expense saying, we had to spend that money today, and now it’s just a deduction from income, but it’s not getting capitalized at any point in time.

And we’re seeing this shift on what’s getting expensed right away versus what’s getting capitalized. It seems like annoying count accounting speak because it is, but it’s really telling to start to think about like what that transition looks like. And candidly, I gotta believe the CFOs, the people who are up guiding these processes, like the textbook they’re studying now includes.

The Salesforce and the Amazons and all these other companies who taught them how to do this. So it’s like they’re not just looking at what did GE do 20 years ago? They’re looking at what did Amazon and Salesforce and all these other companies do, and then how do we balance these two things next to each other?

That’s, that’s a fascinating evolution in accounting. Jack: And the key with any investment is what is the return on the investment, not what type of investment it is. And, and that’s the key here. And I was, I, I mentioned the event. I was with Michael Mauboussin last night, and he has just. Such amazing insights on anything.

It was funny, like somebody asked him about. Taylor Swift becoming a billion dollar company, like someone with the audience, which is like, how do you even answer? I don’t even know what to do with that. And he’s like, here are the 12 frameworks I’ve thought about. You know, that, that help explain Taylor Swift becoming a billion, like really the most, the smartest answer you could come up with.

Like, coming at it from seven different angles. Like I’ve never, I’ve never seen anybody that could do it, but what I took from him is like, the idea is we don’t, what we don’t know about this ai CapEx is what the ROI is gonna is gonna be. And that’s what matters. What mattered is the RD before had a massive, massive ROI for these companies.

It was incredibly profitable. If this is the same thing, then who gives a crap? Like what, what kind of investment it is. If it’s not, and if it’s a disaster, it’s gonna be a problem for them. But that’s the key question. The key is not, is it RD spending or is it CapEx spending? It’s what the return is gonna be.

Matt: It’s a, it’s an amazing way to look at it. And it’s great to, again, remind you of like, what’s the output of this investment? What’s the return on the investment that you were making that return on that invested capital where the company said, we have, we have earnings. We have a margin, we have something that we see as still worthy investing in within the company.

And you know, extra Taylor Swift bonus points to the degree she can keep making albums that sell, sell and selling out tours and doing like all the other stuff that’s money better reinvested in the franchise. And that’s a tremendous opportunity for a compounder. The minute you can’t do that, the minute you’re, I mean, I guess Bob Dylan’s still going on tours and this is not.

To equate Bob Dylan to Taylor Swift, although dare me and I will, but it’s like the guy has no business really being on tour and doing stuff anymore. But he’s still gonna go out there for like the cash grab. But you can’t reinvest in that. The times are not, they’re not a change in, like that’s not gonna, there’s no more hard reins are gonna fall from that guy.

Like it’s gonna be on a cover version of something on YouTube probably is the best shot it’s gonna get. But the reality is like. Compounding works because you can reinvest in that core business. And of course, moison can answer that. I love it. Did he make any Taylor Swift references? Did he, did he name check anything?

Jack: He, he didn’t do anything like you did. he’s not, he’s probably not as up on the pop culture as you are, but, he, he definitely answered the question about as intelligently as you could conceivably answer that question, which I would’ve been like, if somebody asked me that for the audience, I’d be like, I, I don’t know what to do with that.

But, he was right there.

Matt: Michael Mauboussin said, if you want me to explain John Mayer disc tracks from Taylor Swift, you just let me know. We’ll sit down for a session.

Jack: You and him sitting down for an interview and talking about that would be, would be fantastic. Well, I guess that’s probably a good note to wrap up on.

Matt, I’ll let you bring it out as you always do.

Matt: This is fantastic. No better way to come back from vacation. Let me tell you dear listeners, than to catch up on some excess returns episodes. This was a murderers row here. So Jack, thanks for doing this. Make sure you check out excess returns on Substack.

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