Jack: Welcome to the Excess Returns Weekly Wrap. I’m Jack Forehand, joined as always by Matt Zeigler. Matt, what’s going on?
Matt: Oh, man. I’m excited to do this, you rapscallion ragamuffin, you.
Jack: That was, yeah, that was in the... We had a comment about that. But what’s funny about these comments we get, by the way, is you are clearly more plugged into pop culture, but also just the world than I am. So half the time we get these comments, they’re something that I just don’t understand that I should understand, and the other half of the time, they’re just complete nonsense. And I cannot distinguish between which one is which. So I don’t know if this comment actually was referring to something I don’t know about, or if it actually just made no sense.
Matt: We are here for the things that make no sense. I am also here for... To the person who shouted out the Tiger Shark, thank you, number one. Number two, I’m still offering those extra bonus points if you know where that restaurant is that’s on the cover of that album. Just throwing that out there. If you have that deep knowledge, I’m awarding bonus points.
Jack: You get so many comments on what’s behind you in these episodes, like, all the time. I literally have just nothing behind me, which probably says a lot about me versus you. But there’s always stuff about the random... I don’t even know what’s behind you, ‘cause you’re always small when I’m talking to you in the thing. But each poster, each painting, everything gets commented on.
Matt: It’s deliberate. It’s all deliberate, and I appreciate it because I obsess over this in everyone else’s backdrop, as you well know.
Jack: Yeah.
Matt: So this means the world to me. Thank you for commenting on the random record that’s out next to me over here.
Jack: Well, if mine says I’m the most bland guy of all time, it’s probably correct. I mean, I got a printer back there. I don’t know why.
Matt: What that’s supposed to mean. There you go. So you got the two office chairs. I always love the two office chairs. I imagine, you know, maybe the kids are in the seat next to you. You’re reading them Ben Graham or some quantitative data handbook. That’s what goes on up there, right?
Jack: It was funny. When I was doing one of the macro ones, I think it was Tian Yang recently, my daughter just comes up here, starts printing stuff. She’s just taking the printing stuff off the paper. I’m trying to keep the episode going. The guy’s looking at me like, “What’s going on?” She’s like... The printer just, stuff just keeps coming out of the printer, so.
Matt: This is—
Jack: That’s my life now. That’s what happens when you have kids, though.
Matt: This is the real world. This is real podcast life. Take that, TV studios. Who are we talking about today?
Jack: So today, we got Jim Paulsen and Dom Rizzo, and it’s really good. We’ve got a balance of different things and maybe different takes on similar issues. But people who’ve watched the podcast know Jim. We have him on every month. And Dom runs the T. Rowe Price Global Technology Fund, an $8 billion fund, so it was really great to get him and talk about AI. So we got three good clips from them, and let’s get into it.
Matt: Let’s get right into it. It’s also fascinating, the comments that these get. I am endlessly... There’s a sentiment indicator in there. We were talking about this before. There is a sentiment indicator in the comment sections of these videos.
Jack: Yeah, definitely. And especially right now, because you can tell right now — and I don’t know if that’s general YouTube, ‘cause everybody knows negativity works on YouTube. I don’t know if it’s general YouTube or right now, but you can definitely tell when we put out something that is negative about AI, people love it. They’re like, “This is the greatest idea of all...” And then when we put out something positive about AI, the commenters don’t like it.
And that says nothing about the quality of what these people said. The quality of what Dom said was very, very high. We’ve had other people on who’ve talked positively about AI, and the quality of it was very high. But that’s just the world we live in right now, I think, that the negativity is playing with AI right now.
Matt: Yeah. And our goal is to try to get these thoughts and ideas out on the table, not because — as the disclosure says and actually means — not because you should be taking advice from these people, not because we’re taking advice from these people. Because it’s expansive, even in that Dom Rizzo episode. I am looking for those counterarguments because I think about the Brent Donnelly episode. I do not harness some of these arguments inside of myself. They don’t naturally occur. So it takes somebody like Dom explaining things in a certain way about TAMs and other stuff that I go, “Okay, great. I needed somebody to tell me what that case was.” And that’s why we’re asking these questions. It’s also why we’re not bickering with them needlessly over these questions in the interviews. Sometimes we push back, sometimes we don’t. We’re trying to get this stuff on the table. It’s useful to hear it from all these perspectives.
Jack: Yeah. The argument you need to hear the most is always the one you disagree with.
Matt: Absolutely.
Jack: And that’s 100% true, and that’s why I love doing the tech, ‘cause I tend to be a value guy. I tend to think these things always end the same way, like that stuff. I always love bringing on the tech guys. I love talking to Dom. I love talking to Gene Munster when we bring him on, and Doug Clinton. I love doing those episodes because I wanna see the positive side of this. I wanna see the other side of it because that may be contrary to the way I think personally.
Matt: Yeah. I’m waiting for the robot overlords to come. Come on, Cylons. That’s all I think, is my brain. It’s Cylons and Terminators, and it’s just all going to hell. So speaking of Skynet, take us to this Jim Paulsen clip.
Jack: Jim, yeah. So this first clip with Jim is really interesting, and I always think when we do these episodes with Jim, I always find things where I’m like, “I did not know that.” Or I maybe knew that that worked fundamentally, but I didn’t see it happening right now or what’s going on right now. And this is one of those, which is this idea that a lot of people want rates to fall because they’re like, “If rates fall, stocks are going up.” But Jim made the argument that maybe in this case the opposite will be true. So here’s Jim talking about that.
Jim: Right now what’s happened is people are going, “Okay, Fed’s not gonna raise rates maybe right away, but I’m still worried about inflation.” And I say that is the case ‘cause I still think — I’ll come back to it in a minute — that the relationship or correlation between stocks and bonds is such that that’s what it suggests is the situation, that investors are more worried about inflation than growth.
But just to start out, this chart, the blue line here is the 10-year Treasury yield going back to 2023, and the red line is Bloomberg’s Hard Data Economic Surprise Index. I’m just backing out the survey data. I wouldn’t have had to, but it’s a little better relationship. If I back out the survey data, what you find is just hard data reports, actual economic reports, how are they coming in above or below expectations.
You can see they’ve dropped off considerably of late, and what I find most interesting about this chart is that red line has been leading bond yields rather consistently throughout this bull market, up and down. Study that chart. Red goes up first, then blue. Red goes down first, then blue, all the way across for the most part. And right now it’s suggesting that we might, in the not-too-distant future, see us with a three handle on the 10-year again, not a five handle, as maybe what a lot were expecting just a couple weeks ago.
That’s just to set the page. Now, if we’re gonna get something like that, you gotta have a sentiment shift, I think. People have gotta give up the inflation ghost and worry a little more about growth if we’re gonna actually go back down to those levels.
So let’s look at where that relationship is at here in the next chart. And I’ve shown this next chart before. The red line is just the 10-year Treasury yield. And the blue line is the correlation on a trailing one-year basis between stock and bond yield movements. And it’s on an inverted left-hand scale, that blue line.
All this says is right now we have been in, during much of this bull market since 2022, we’ve been in a negative correlation position between stocks and yields. That is, most of the time when yields rise, stocks go down. When yields fall, stocks go up. Why is that? That’s a sign that investors are mostly worried about inflation, because when yields go up, that suggests inflation is becoming more intense, and stocks fall. And when yields go down, that says, oh, inflation’s cooled a little, stocks go up. In the last few days since the job report, stocks have gone up, every day yields have gone down. That’s kinda what’s going on. People are still in the inflation mode.
But if that correlation starts to go south on that chart, goes more positive, that reflects an anticipation changing towards worried more about growth than inflation. If you’re worried about growth, if yields are falling today, stocks may fall, too, ‘cause they’re both fearful about a recession. And if yields go up when you’re worried about recession, you go, “Oh, boy, that’s good. Economy’s strong enough to lift yields.” And so there it turns from a negative relationship to a positive.
Look how close the bond yield corresponds to this one-year trailing correlation. When you’re mostly worried about inflation and the correlation, that blue line’s high, yields are high. When you’re more worried about recession, yields get low. I think we’re shifting sentiment in the rest of this year from being worried about inflation to worried about growth. We’re gonna have that blue line head south towards positive correlation, and yields are gonna go down. Right now, when they go down, it’s pushing stocks up. But if sentiment shifts, we’re gonna start finding a week where yields fall, and so do stock prices. And that’s kinda what I think we might get into a little.
Jack: So the key here, Matt, is why are rates falling? You need to know that to know whether rates falling is good for stocks. If they’re falling because inflation is moderating, that’s fantastic. If they’re falling because a recession is on the way, not so good. And that’s an important thing to distinguish because people are always looking at that. They’re like, “Oh, let’s just look at rates, and if rates go down, I expect stocks to rally.” And Jim expects economic weakness here, so he expects a situation where we could see rates and stocks fall simultaneously, which many people do not expect.
Matt: Yeah, and was not fun. I mean, let’s be clear. When stocks and bonds move in a correlated way, when rates and stocks move — like, you have to think about this stuff at an allocator perspective. What I thought was interesting here was the part that you started with. There is a good reason for rates falling, and there’s bad reasons for them falling. Jim depicting it in this chart, which what’s leading what and why — another Jim Paulsen chart. I hadn’t seen it presented this way before. What’d you think about this?
Jack: The great one was this hard data versus the 10-year chart that he had in there.
Matt: Yeah, yeah.
Jack: So you can see they move together and the hard data is on its way down. The 10-year has not moved down yet. So you see a lot of that in Jim’s work where he’ll look at a relationship that’s held historically, and then he’ll kind of carry it forward and say, “Oh, based on this separation, something might be happening here.” This is a great use of that. If you believe this hard data indicator, the hard data continues to get worse. And if that’s the case, then you would expect rates to fall, which is the opposite of what a lot of people think right now. I mean, a lot of people think rates are high right now, and a lot of people think they’re gonna keep going up.
Matt: Yeah, ‘cause they’re looking at it from the inflationary angle, that that’s gonna drive the rates up. He’s saying negative economic surprises, negative hard data are gonna drag rates down. I think this also gets interesting where you pull in stuff like credit spreads, you pull in liquidity, and you pull in how that can be the counter to this. Because what this can do is this can trigger lower rates, but if it triggers also rate cuts or injections of liquidity or anything that helps close credit spreads, this is how this chart flips and moves in the other direction however many months forward too.
Jack: So as we move to Dom Rizzo here, we asked him about a lot of different things in this clip, and I made it a long clip because there was a lot of good data he gave us in here. But this idea of productivity and AI and value capture in the AI ecosystem — so he talks about all that here. So here’s Dom.
Dom: Every single question is really downstream from this concept of what do the frontier labs look like in a few years? And let’s just take a step back, right? And think about the past year. When I did the Anthropic round last year in the global technology strategy, they were doing $5 billion of run rate ARR. This is last summer, right? The latest rumors on Twitter or whatever, any third-party data source, would put that number well north of $70 billion.
Okay, I’ve never seen a company grow that fast. I mean, how many ServiceNows is that? That’s like three ServiceNows or something. It’s really stunningly fast growth. And why is that? It’s because coding as a use case went completely vertical, and then Claude Code and OpenAI Codex really just caught complete virality within the enterprise, right?
And why did coding go vertical? It’s because you clearly made your average coder 20% to 30% more productive, and your most successful AI native coder is probably, like, manyfold more productive. And what’s so amazing about that is, ask any engineer in the world right now, has that resulted in any decline in their day-to-day work, or are they working harder? I mean, every software engineer is working the hardest they’ve ever worked right now, despite being 20%, 30%, 40% more productive, right?
And so when you’re in the world of making white-collar labor more productive, I think there’s very, very high returns because enterprises are willing to pay for that productivity inherently, right?
And so how big is the coding TAM, right? It’s a question I get all the time. Well, there’s 30 million people who write code for a living. Let’s say we pay them each $100,000 a year, so we spend $3 trillion on coding knowledge work as a society globally. Let’s say we make them each 20% more productive, that means that the $3 trillion of spend is $600 billion more productive. And then you say, “Okay, what right does OpenAI or Anthropic or Cursor,” I would argue, maybe, have in that $600 billion spend? I don’t think it’s crazy to say half. It may even be more than half, right? And so that’s $300 to $400 billion. And then you compare that to the overall application software business being $300 to $400 billion of revenue. And you’re like, “Wow, coding in and of itself is as big as all of application software,” and that doesn’t even include HR, legal, finance, all these different TAMs.
Okay. So then your question is, what if you have open weight models commoditize that TAM? What if you have N minus one models come in and the returns aren’t to frontier intelligence, but they’re to N minus one models that are simply good enough? Or what if that’s way too much money to spend on coding and enterprises aren’t seeing the return, right?
So, one, I think enterprises are not stupid in general. I think actually most enterprises are quite thoughtful, and clearly they’re getting some value or they wouldn’t be spending this money, right? This concept that people would spend money and not get any return on it I find a little silly, but let’s put that to the side.
I do think what we’ve learned is that almost all the economic return is accruing to the frontier from a revenue perspective, even though the vast majority of tokens may actually be open weight or open source or N minus one to be more efficient, right? And I think a really good analogy may be Apple versus Android. But broadly speaking, I think we’re gonna live in an 80/20 world where 80% of the tokens are probably open source or open weight or N minus one, and 20% of them are frontier. But then the vast majority of the value accrues to those frontier models as they orchestrate the other models, as they make it more efficient.
And then I think there’s a real question structurally whether or not OpenAI and Anthropic are best positioned to give you that whole spectrum of models, right? Are they actually the most profitable and willing to give you... I don’t know if you guys saw the ChatGPT pricing decreases for the lower models last week. I think that was Sam’s bet, that you wanna be the most efficient at every level, the most efficient per task at Sol, Luna, and Terra, right? At all the different levels of the model. Or do you want a Palantir or a Microsoft to sit on top and help you kinda model swap to the most efficient model? I think every enterprise is gonna make a different decision on that. My gut is just being at the frontier with the frontier labs is the best way to do it. But let’s see.
Jack: This seems like the question we’ve been talking to so many people about is productivity and AI, and we’ll get into this in the Jim Paulsen clip in a second as well, but is AI making us more productive? How do we even measure that? How do we even figure that out? And that seems to be a very tricky thing to do.
I mean, if you think at an economic level, productivity is basically output per person. That’s kind of the way you would look at productivity. And so the question is, what is output? Is output more code? Well, that’s not really productivity. And how is that more code translating into more revenue or more income or... It’s all very complicated to me, but he made a strong case here in terms of how you could take numbers and say, “We are getting more productivity from all of this stuff.”
Matt: He’s explaining the what, and I think this was some of the sentiment indicator in the comments, is the frustration with the why around this. What I value the most in Dom’s perspective here is he’s explaining the what of the productivity stats, of how this market could expand, what those TAMs look like, what we might value that engineer’s salary, wage, whatever you wanna call it, as part of the input to this equation.
What that doesn’t tell you, though, is why, and that’s what you have to look at, because your assumptions on why does an engineer cost this much? Why do we value this productivity at this rate? Why does the person who’s getting the increased productivity but is working harder than ever wanna keep doing it? All of those become fundamental questions that are actually limiting factors on what this can or will or might do. And none of us have the answer on it.
But this is an incredibly useful framing to say, take for a second all of this productivity and map it forward to say, where does the benefit accrue now? Who gets a return now on this productivity boom as it continues to expand out for at least a little ways longer? That was very eye-opening to me, to hear it explained at this level and then say, “Here’s why you wanna just live on the frontier until that frontier changes.”
Jack: We’re clearly gonna get way, way, way more code per person. There’s no question about that.
Matt: We already have.
Jack: Yeah. And it’s not like per developer, by the way. It’s per Matt and Jack and people who never even wrote code in their life. They were producing zero code. I was writing code before, but you probably weren’t producing any code before this. And now you’re producing a bunch of code.
Matt: I’ve written enough code for both of us.
Jack: Yeah. Exactly. So really the question is, how does that translate into things like revenue, reduced costs, efficiency? How does that translate? And we don’t know the answer to that.
The other thing I think he said that is really important is he said enterprises aren’t stupid. And to me that is very much a bullish case for this that you have to think about, which is the idea that, first of all, the Satya Nadellas of the world that are spending the money — he wasn’t talking about them when he said that, but those people are not idiots. They’re spending a lot of money in this with the expectation that they’re gonna get a return on that money. But second of all, the end user isn’t an idiot either. So if enterprises continue to use this stuff more and more, they’re only gonna do that because they’re getting value from it.
Now, the counterargument to that is if I go back to 1999, the CEOs of those companies were also not stupid. But they saw something in front of them and they maybe over-invested in that thing. But I do think that’s one of the strongest bull arguments for AI right now, is the level of intelligence of some of the people that are really all in on this, both at the high level like the Satya Nadellas, but also the companies that are using this to improve their efficiency. All of that wouldn’t be going on if there was not some significant benefit here. Now, how can I measure it? I have no idea. How does it measure relative to the amount of money that’s being spent? Who knows. But that to me is a very bullish argument for this. I don’t know what you think about that.
Matt: Yeah. In all these technologies you overinvest, and the question is whenever you hit the wall — and we will hit whatever that wall is, don’t know what it is, don’t know when it’s gonna happen — we will overinvest until we hit the wall, and then the question becomes, what level do we fall back down to? Well, I don’t think we’re going back to the pre-AI era. So now where on that are we gonna fall back down to?
You have the giant run-up in the tech bubble. You have the tech boom. You have September 11th, a recession, a tech crisis. Nobody stops using email. So this is gonna come back to a floor at some point. The question is, where is that floor? What does that productivity allow for?
And inside of myself, what I still keep contending is this is still more valuable than the fax machine. This is still more valuable than email communication. This is still more valuable than Zoom during the pandemic. So whatever that wall is, I know we’re coming for it, and there’s gonna be over-investment into that wall. But I think where we settle out on what the productivity gains are and the efficiency, that’s a very interesting market, and it’s another part that makes this really hard to value, and that’s why these valuations are being allowed to persist. People wanna dream, baby.
Jack: I always like to think about this internally for what we’re doing. So if you think about Excess Returns, I was just explaining to you before we started recording, all the stuff we’re doing right now in terms of using AI both for each individual task we’re doing, but having like a high-level thing that’s sitting on top of it — I built like a crazy AI system. But even in my own business, can I tell you yet what the benefit of that is from a revenue and cost perspective? I can’t really tell you that. I don’t know how much it’s translating into more people watching our YouTube videos, which for someone like us is how we make money.
Matt: So is this just a giant Rube Goldberg machine to do... It’s the beginning of Back to the Future where the giant elaborate thing makes his toast or whatever and ruins his coffee. It might just be that, and that’s terrifying. But I don’t think it is.
Jack: But if I don’t know that for sure yet, how the hell do we know that at the economic level across everyone?
Matt: Exactly.
Jack: And that’s the... I think everybody is struggling the way we are, in terms of, we know we’re getting value for this. We don’t know how much it is yet. We don’t know how much it’s gonna lead to more revenue or reduced costs or whatever it is. And I think that’s where we all are right now. But I think we also all watch what it does, and we ultimately believe that that’s going to be there. I don’t know if it’s to the degree the market’s pricing it. That’s a completely different question. I think we all think it’s gonna be there, but the question is when, and how are we gonna measure it? And I don’t know any of that yet.
Matt: Yeah. We’re gonna hit that wall, which is why when Jim Paulsen says something about how productivity rises in a recession, I just go full existential crisis. I pull the Camus off the bookshelf. I try to imagine that we must imagine Sisyphus happy and, uh, yeah. This next one is a hard clip for me, but so interesting.
Jack: This is one I didn’t... I mean, I didn’t really know to the extent he was talking about it before he mentioned it on the podcast first. So here’s Jim talking about productivity and recessions.
Jim: A big part of this AI story, no doubt about it, is for it to be successful, it’s got to raise productivity. Otherwise, it’s not going to be successful. And the problem is, it’s really hard to measure productivity, and it’s getting harder and harder in the new era age, and particularly harder to measure services productivity. We’ve had that problem for some time.
But we still only have the one measure of productivity, the annual productivity index, and that’s shown in this chart, annual growth rate going back to 1948. And the first thing I want to point out is that we currently have productivity that’s like two and a half percent, and people already are going, “Hey, man, we’re already experiencing a productivity boom.”
And I don’t think we are. I think that a lot of what’s going on today is kind of a false productivity signal, and we have a lot of them. If you look closely on this chart, I put recessions on there, and the best productivity periods we’ve ever had are when we’re in recession. Look at those spikes. You get one maybe not right during the recession, but it starts in the recession and then goes up for a quarter or two after the recession. And every time that happens, we spike upward.
I would suggest that a lot of our current productivity improvement has been because the growth’s been so sluggish, not because it’s been booming, if you will. And that’s kinda what I wanna get into just a little bit more, is that actual productivity booms in post-World War II history, I think we’ve only had really two that qualify for that. The rest of the time, we see kinda false bubbles.
Look, the highest productivity on that entire chart was in the middle of the 2020 pandemic recession when the economy collapsed. Why is that? Because when you get into recession, companies start to downsize operations in order to survive the recession. And when they downsize operations, they cut their staffs, they lower marketing costs, and then sales haven’t completely died yet, so measured productivity goes way up, even though sustainable productivity hasn’t. And I think that’s kinda what we got going on here.
If we look at the next chart, this is just a real quick calculation back to 1948. I looked at all the quarters in the chart before where we were either in a recession or in a growth recession, or I should say real close to a recession, a couple quarters after. I think I went from one quarter after recession started to two quarters after it ended. And look, our productivity during that period of time was three point three percent. Then all the rest of the time during expansions, we only had two percent productivity growth. Our measured productivity is mainly about how weak is the economy, more than it is about how really sustainably productive is it, and I think we’re misinterpreting that even as we speak.
Jack: And this is obviously a very relevant question, Matt, because there’s a lot of talk that we’re in a productivity boom right now, and we don’t know if we’re in a productivity boom yet. But the idea is, during a recession — he had the chart in here — historically productivity always rises in recessions. I mean, people are tightening, they’re probably cutting costs ahead of revenue coming down. So you’re seeing a temporary effect in recessions where productivity goes up. It’s never a lasting effect. It’s a temporary effect.
And so when you think about, are we getting more productivity? We could be getting more productivity right now because of that reason and maybe not because of AI. And we don’t know the answer to that. But I love when we hear something in the podcast and I’m like, “I did not know that.” So the extent to which this always happens in recessions was something I didn’t know.
Matt: So I think about, you’re in elementary school, you’re taking a test, the teacher’s out in the hall talking to somebody, everybody’s talking to each other. You’re throwing stuff at your friends, you’re copying answers, you’re sharing answers, whatever’s going on, whatever debauchery is happening inside the classroom while the teacher’s talking in the hall. Then the teacher comes back in and they realize order must be restored. And in that moment it’s like a recession, in the sense that now the teacher’s gonna walk up and down those aisles. But you are now laser focused on your page. You are now scrupulously looking and checking out where the teacher is. You get more productive when stuff gets focused and when that sense of risk is there.
To me, I also look at this and wonder what this is telling us about where we are right now. ‘Cause a lot of the data we’ve seen suggests that there’s pockets of this economy, there’s parts of these markets that are in some form of a recession. And whether that’s the traditional labor recession — that’s possible in the places where we’ve seen job turnover, we’ve seen a loss of jobs, we’ve seen a loss of high-paying jobs — or whether that’s in these companies that just haven’t gone anywhere or have gone a much more limited distance compared to the large cap averages.
So I wonder how much of this increased productivity we’re seeing kind of like below the surface and something we’re all experiencing. Maybe this catches traction, and this is part of what takes us on the next leg higher, or maybe this is just part of digesting where we are now. I just hadn’t thought of productivity relative to the recessionary cycle until he said it this way.
Jack: And what’s interesting is this is kinda unique to this period that we’re in right now, where we can argue... Like, Jim doesn’t think we’re gonna have a recession, but we are in a period where you could argue that’s a possibility, or a significant slowdown is a possibility, but we also have this huge thing in AI. That was not the case in the ‘90s. The ‘90s, nobody was arguing we’re about to have a recession. Economic growth was much stronger. And so it’s kinda unique right now, because if you do get that boost in productivity, it’s harder to attribute what’s causing it, because we have these simultaneous things going on together.
Matt: Yeah. And again, it’s like the wheels are just spinning like crazy right now. The question is, do we get that traction? And again, it forces the question in my head: why are the wheels spinning so aggressively right now? This isn’t the normal thing. Are we experiencing more of a downturn that’s being masked by what’s going on with capital, that we’re just experiencing this a little bit differently, that’s why this data looks so bizarre? It’s a fascinating thing to put a light on.
Jack: Yeah, and I don’t think anybody has the answer, and that’s what we’re trying to do on this show, is we’re trying to bring... And we’ve kind of done that right here. We talked to Dom about a very positive case for productivity, and we talked to Jim about, like, maybe that’s not it. And that’s what we wanna do on this show. We wanna get different opinions from different people and — as we’ve been criticized for, correctly, to some degree — we try not to grill the people too much in the episodes themselves. But we let them speak for themselves, and we let people judge for themselves. Our goal is for our guests to educate our audience. And hopefully that’s what we’ve done with these types of episodes.
Matt: I think that’s what we’ve done. I think we get a gold star. This thing will get 2,000 likes.
Jack: Do I get a... Is it gonna flash on the screen or something?
Matt: It’s gonna flash on the screen. It’s gonna be one of those weird TikTok kid things that they figured out how to do that you go, “Oh, my God. You can do that?” That’s what’s gonna happen. It’s gonna be all positive comments and likes.
Jack: Yeah, exactly. It’s gonna be nothing but positive comments.
Matt: Nothing but positive comments.
Jack: Or at least if they’re negative, at least make it so I can’t understand them, like those last ones, so I have no idea what you’re talking about.
Matt: Yeah. Embed the metaphor or say something funny.
Jack: Reference some book from the 1800s or whatever. Reference something that I just have no idea what you’re talking about, because then I won’t get it.
Matt: Mention Pimp by Iceberg Slim. Yeah, I don’t know.
Jack: Don’t even get into that again. Let’s not go there.
Matt: Well, we got another good week in the books here, Jack.
Jack: Yeah. Why don’t you bring us home?
Matt: All right. Excess Returns, make sure you check us out on the Substack too. We’ve got stuff going up on the regular, transcripts and everything from these episodes and more. Wherever you’re watching or listening, thank you. Like, comment, subscribe, all the things below, and we are out.