Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2: Hello and welcome to another episode of the ath Thoughts Podcast.
Speaker 2: I'm Tracy Alloway.
Speaker 3: And I'm Joe Wisenthal.
Speaker 2: Joe, imagine you are a utilities analyst.
Speaker 1: Yeah.
Speaker 2: Fun, and for years you are laboring in the utility
Speaker 2: analysis mind. Yeah, and you know, we like talking about utilities,
Speaker 2: We like talking about energy. We find pretty much anything interesting,
Speaker 2: that's right, equal opportunity interest people we are. But yes,
Speaker 2: you got to say utilities. For a while, some people
Speaker 2: would say it was a.
Speaker 3: Little POORI no, that's right. I mean for most of
Speaker 3: our careers. I think if you were utilities analyst, a
Speaker 3: really big part of your job. And maybe I'm wrong,
Speaker 3: but I just didn't the popular discourse was like talking
Speaker 3: about yield relative to treasuries. Right, they were seeing a
Speaker 3: sort of bond like instruments, et cetera. Maybe a little
Speaker 3: bit of growth, but real.
Speaker 2: Reliable, safe haven ish dividend plays.
Speaker 3: I guess totally. And since I know where we're going
Speaker 3: with this conversation, one of the themes of the last
Speaker 3: few years has been what I would say is the
Speaker 3: old industries that were either stable or cyclical becoming secular
Speaker 3: in the way they grow.
Speaker 2: I think that's right. So what is happening now is
Speaker 2: if you were I don't want to say, a lowly
Speaker 2: utilities analyst, but you know, maybe a sort of forgotten
Speaker 2: utilities analyst outside of your sector, suddenly you are very
Speaker 2: in demand, right because all you hear about nowadays is
Speaker 2: the AI build out and energy constraints on that, and
Speaker 2: so obviously a lot of people want to look at
Speaker 2: it from a utilities perspective.
Speaker 3: Totally. I always think, like, what a great luck that
Speaker 3: some people have in their careers. You know, you could
Speaker 3: be an analyst and learn modeling skills and all kinds
Speaker 3: of stuff, and then you get allocated and someone gets
Speaker 3: allocated I don't know, farm equipment, and another person gets
Speaker 3: allocated to they wind up in utilities in twenty twenty two,
Speaker 3: and it's like, man, they're on TV all the time.
Speaker 3: My old boss at Business Insider, Henry Blodge, it it's
Speaker 3: like he was there as an Internet enalyst in like
Speaker 3: the late nineties. What amazing timing and luck and.
Speaker 2: So it's like journalism and the Yeah, it's it's the
Speaker 2: exact same thing. I started out covering airlines, yeah, of
Speaker 2: all things, but those were interesting. Anyway, I'm glad to
Speaker 2: say we do, in fact have the perfect guests. So
Speaker 2: we're going to be speaking to a utilities analyst, someone
Speaker 2: who happens to have a very contrarian take on the
Speaker 2: data center build out and how much energy is actually required.
Speaker 2: We've been hearing a lot from people who are very,
Speaker 2: very bullish on the data center build out, so this
Speaker 2: will be a useful I love their point.
Speaker 3: I love it.
Speaker 2: Okay, So, without further ado, Andy Devreese, head of Investment
Speaker 2: Grade Credit and head of Utilities and power over at
Speaker 2: Credit Sides, thank you so much for coming on all thoughts.
Speaker 4: Thank you the pleasure mine.
Speaker 2: So is it great to be a utilities analyst right now?
Speaker 2: Even better?
Speaker 4: Well your your Bloomberg News reporter Josh Saul wrote an
Speaker 4: article about the how much it's changed for being a
Speaker 4: utilities analyst now the data centers are here. But to
Speaker 4: push back, we did have the largest bankruptcy of all
Speaker 4: time in Enron, Oh yeah, the largest LBO of all
Speaker 4: time in TXU, which then went bankrupt, and the largest
Speaker 4: private equity return ever in Calpine twenty five billion, which
Speaker 4: exceeds Apollos, Lioned, l Trade and Blackstones Hilton Trade. So
Speaker 4: we have had a lot of fun along the way.
Speaker 2: Have you been a utilities analyst throughout that entire timeline?
Speaker 2: How long have you been doing it?
Speaker 4: I started with the first packcast bankruptcy and then went
Speaker 4: through the second and here we are with data centers,
Speaker 4: so twenty five years.
Speaker 3: Wow, So you really have seen it all. It is
Speaker 3: fair to say. So, you're absolutely right. There have been
Speaker 3: some disasters and home runs and utilities. You know, they
Speaker 3: do get central in the news, obviously with the fires
Speaker 3: that we saw for example California several years ago, and
Speaker 3: the court trails about allocation of risk in those situations.
Speaker 3: You mentioned ron et cetera. But it is also fair
Speaker 3: to say that much of the discourse in day to
Speaker 3: day has been like these are sort of bond like instruments. Absolutely,
Speaker 3: before we get into that, just like sort of like
Speaker 3: talk to us about what a normal day is like,
Speaker 3: and when you're thinking about you til.
Speaker 4: It before you know, pre data centers, yeah, pre.
Speaker 3: Data centers, five years ago, whatever, Pre data centers.
Speaker 4: You're looking at a lot of rate cases of studying,
Speaker 4: a lot of local news. You're looking at legislation, you're
Speaker 4: reading you know, dry regulatory documents, and then you're tracking
Speaker 4: natural gas prices because that's setting the price of power.
Speaker 4: And then on the federal level you obviously have the
Speaker 4: renewables displacing coal and that's obviously having a big impact now.
Speaker 4: So it's a lot I actually think it's a lot
Speaker 4: of fun.
Speaker 2: My impression was always the policy aspect of it seemed
Speaker 2: kind of the most important thing to keep track of.
Speaker 4: Is that right, absolutely, and that's down to the state level,
Speaker 4: but also the federal as well.
Speaker 2: Yeah, we've done a few energy episodes, still trying to
Speaker 2: wrap my head around the sort of patchwork of that
Speaker 2: seem to cover our energy infrastructure. But anyway, who should
Speaker 2: be a.
Speaker 3: Little aspy about the way? Like you talk to people
Speaker 3: in this space and you're like, well, how is this
Speaker 3: get priced? And they're like, well, are you talking about
Speaker 3: market or central? It's like, okay, I don't know, you know,
Speaker 3: it's like are you talking about a rate board or
Speaker 3: you talk about market prices.
Speaker 2: It's so hard anyway, especially in a forty minute podcast,
Speaker 2: to try to generalize that.
Speaker 3: But I love the people, don't get me wrong, those
Speaker 3: are my favorite people.
Speaker 2: Anyway, Andy, what is the mood like at the moment?
Speaker 2: Among utilities, people, analysts, investors. Wasn't there a conference recently?
Speaker 4: Everyone's gung ho on this. So the biggest conference of
Speaker 4: the year is EI in November and it was packed.
Speaker 4: I was standing and rolling for some of these presentations. Wow,
Speaker 4: your competitors at CNBC were broadcasting from the floor the
Speaker 4: first time. That has probably a sign of a top.
Speaker 4: So yeah, people are very happy, and it just to
Speaker 4: quantify it. Utilities have generally grown around four or five
Speaker 4: six percent a year, and then that's moved to five
Speaker 4: to seven percent a year, and now certain names which
Speaker 4: we'll talk about later are up to eight percent a year,
Speaker 4: and that's driven by data center growth.
Speaker 3: Talk to us a little bit more about that. So
Speaker 3: what is the I mean, I'm like looking at a
Speaker 3: chart of the xl U ETF. I don't think it's
Speaker 3: like done insane, But talk to us a little bit about,
Speaker 3: like maybe quantify the exuberance for us. So it's like, okay,
Speaker 3: we we are no longer just in the business of
Speaker 3: measuring bond proxies and looking at policies, et cetera. There
Speaker 3: was a secular growth driver. Talk to us about like
Speaker 3: the bowl case, and then also how we would see
Speaker 3: the ball case sort of like how it's manifesting into
Speaker 3: tradable instruments.
Speaker 4: Sure, and you pulled up the graph of the XLU.
Speaker 4: Obviously it's still a very interest rate sensitive section. Yeah,
Speaker 4: that's dividends. You can find higher yields and other fixed
Speaker 4: income instruments. So you know, maybe didn't do so well
Speaker 4: last year. But the industry argues that as this EPs
Speaker 4: growth rate goes up to the high single digits, mid
Speaker 4: to high single digits, that it shouldn't be as interest
Speaker 4: rate sensitive. So that's the big debate going on with
Speaker 4: investors right now. And this talk.
Speaker 3: I mean, the exo you has done well to ya.
Speaker 2: If you zoom out, it looks pretty good. That's my
Speaker 2: impression of a bitcoin investor, by the way, zoom outoom.
Speaker 3: All right, think about you've gotten the end. You've gotten
Speaker 3: that coupon, right, so like you get so like you
Speaker 3: might in normal time, just be happy with a coupon.
Speaker 3: You're getting coupon plus.
Speaker 4: I mean, it worked out the Fed zero interest rates
Speaker 4: for so long, so utilities are the place to be.
Speaker 4: That's just math. And then as soon as the Fed
Speaker 4: starts jocking uprates, chat TBT comes on the scene and
Speaker 4: all of a sudden there's data centers. So now, all
Speaker 4: of a sudden, you're taking the leg up on growth
Speaker 4: when you don't need to be so interest rate sensitive.
Speaker 2: Interesting. So one of the reasons we wanted to talk
Speaker 2: to you is because you have that contrarian take on
Speaker 2: the data center build out, and we wrote it up
Speaker 2: in the All Thoughts newsletter, which everyone should subscribe to.
Speaker 2: It got a lot of attention. Your analysis, interestingly, is
Speaker 2: just based on some pretty simple math. So why don't
Speaker 2: you just to start out with why don't you walk
Speaker 2: us through the calculations that you're actually making to try
Speaker 2: to analyze how much capacity the utilities are taking on
Speaker 2: to actually power data centers.
Speaker 4: Sure, so, as you said, it's pretty simple math here,
Speaker 4: so utility, it's so data centers now are consuming around
Speaker 4: forty five gigawatts of power, and you can switch between
Speaker 4: capacity and throughput. I'm going to stick with capacity, so
Speaker 4: forty five gigabats of power. And then there's lots and
Speaker 4: lots of third party estimates for where they're going to
Speaker 4: be in twenty thirty and they center around this, you know,
Speaker 4: ninety ninety five gigawatts, so you need to add fifty
Speaker 4: for two thousand and thirty five, there's a lot fewer estimates.
Speaker 4: You come around one sixty. Now, these estimates, they you know,
Speaker 4: they're all over the place. They come from sell side banks,
Speaker 4: they come from consultants, they come from everyone. Bn EF
Speaker 4: has one there, I think, one of the best out there,
Speaker 4: so we use them a lot. So that's on the
Speaker 4: demand side and where you're going to come out of these.
Speaker 4: And then you look at the supply, and everyone talks
Speaker 4: about the demand, right, But then you look at the
Speaker 4: supply and all these tech are too cool to actually
Speaker 4: look at the supply and do utility analysis, right, Who
Speaker 4: wants to be a utility analysts? You were making fun
Speaker 4: of us before, but if you look at this.
Speaker 3: But when we realize our pity is misplaced. But we
Speaker 3: were not making fun anyway, it's great.
Speaker 4: So you look at the supply and these utilities are
Speaker 4: tracking all these data centers connecting to the grid because
Speaker 4: they've got to do a lot of work, spend a
Speaker 4: lot of money and transmission distribution, new substations, transformers. It's
Speaker 4: a lot of work, but a boost the earnings growth,
Speaker 4: so they're happy to talk about this. And so you
Speaker 4: look at where they're at and where they see things coming,
Speaker 4: and they've got around one hundred and forty gigawatts a
Speaker 4: near term supply. Now, kudos to the utilities. They break
Speaker 4: out what's firm committed, signed, contracted versus pipeline behind it,
Speaker 4: because there's a lot of double, triple, quadruple counting. So
Speaker 4: if you're gonna build a data center in the Southeast,
Speaker 4: you're gonna tell Duke, You're gonna tell Southern, You're gonna
Speaker 4: tell Dominion you're gonna build one. So that's the pipeline potential.
Speaker 4: But looking just at the firm committed whatever they want
Speaker 4: to call it, you around one hundred and forty gigawats.
Speaker 4: Now that's you got a pe adjust So when you
Speaker 4: connected data center, yeah, when you connect the data center
Speaker 4: to the grid, you've got lights, you've got cooling. Those
Speaker 4: third party estimates I gave you are just for raw compute.
Speaker 2: Why did you split those out though, because I mean,
Speaker 2: all data centers are going to need to be cooled
Speaker 2: down right, what's the point of splitting it out.
Speaker 4: I'm not splitting out, I'm just adjusting it downward. Because
Speaker 4: the third party estimates are just compute. So if you're
Speaker 4: connecting to the grid. You're going to ask the lights,
Speaker 4: the cooling and everything. So I want to go apples
Speaker 4: to apples.
Speaker 3: Versus the third party, So what power usage effectiveness or
Speaker 3: power usage efficiency?
Speaker 4: So they're at one forty, so that PUE is down
Speaker 4: to one ten on apples to apples. So just to
Speaker 4: go back, you only need fifty on the demand side
Speaker 4: between now in twenty thirty and the utilities are working
Speaker 4: at connecting one ten. So the utilities are working on
Speaker 4: already connecting almost as much as you need by two
Speaker 4: thy thirty five. So again just to make sure, on
Speaker 4: the same page, third party estimates forty five gigabatser data
Speaker 4: centers now going to ninety fives. That's fifty of these
Speaker 4: are working on one to ten. They don't give timing
Speaker 4: for that. Some of it's going to be past twenty thirty.
Speaker 4: What I'm starting to say is there is a lot
Speaker 4: of supply of data centers coming and it's very unclear
Speaker 4: if there's going to be demand for this. So that's
Speaker 4: the issue there, and then it might be worth pausing
Speaker 4: that and just saying how we're tracking these things. Yeah,
Speaker 4: So what we do for the demand side is we
Speaker 4: use the original AI agent, you know, that is a
Speaker 4: Gmail alert the best. So anything that's not on our
Speaker 4: trade pubs, not on Bloomberg News, we get picked up
Speaker 4: by a Gmail alert and so then we get all
Speaker 4: that in a spreadsheet. So that's on the demand side.
Speaker 4: And then on the supply side we use Diego and
Speaker 4: that's not a large language model. That's my junior sitting
Speaker 4: several blocks best of us right now, so he tracks
Speaker 4: all this on utility calls. Just yesterday, next to Era
Speaker 4: moved another two gigawatts from the potential into the committed.
Speaker 4: And these utilities are chopping at the bit to sign
Speaker 4: more and more of these deals, and I think it's
Speaker 4: just going to be oversupply. We're going to overbuild these things.
Speaker 2: Just to be clear, the commit the firm commitments, those
Speaker 2: are signed agreements to actually build this capacity. Yes, okay.
Speaker 4: And so I was talking with the CFO of Encore
Speaker 4: and they made these comments on their call as well.
Speaker 4: They're owned by Sempra, and I said, you know, no
Speaker 4: one really believes these DAMA and estimates. Texas is a
Speaker 4: wald off market, as you guys know, eighty seven gigawatt
Speaker 4: peak market.
Speaker 3: It is the one thing I know about energy Texas.
Speaker 2: Is it market?
Speaker 1: There?
Speaker 4: You go, so eighty seven gigap peak market and the
Speaker 4: demand estimates or they're going to add thirty gigawatts by
Speaker 4: twenty thirty. And I said to the CFO of on cars,
Speaker 4: there's just no way. He said, it might not be thirty,
Speaker 4: but it's going to be closer to thirty than it
Speaker 4: is zero. And I said, I just the forward power
Speaker 4: curves don't reflect that at all, and he said, then
Speaker 4: they're mispriced. So just for the entire market, just for
Speaker 4: the benefit of your users, you cannot trade forward power
Speaker 4: in Texas on interactive brokers. I know that. Oh that's fair, audience,
Speaker 4: That's too bad. Everyone's like looking up there, That's what
Speaker 4: I said.
Speaker 3: Great, And this gives us a bunch of technical questions
Speaker 3: to get into. Let's just keep talking about Texas. Explain
Speaker 3: to us kind of what the forward power curves are
Speaker 3: and how you can back out the implicit assumptions that
Speaker 3: traders are making based on those forward power curves about
Speaker 3: how much demand there's going to pay.
Speaker 4: Sure, So I mean, obviously, if you're gonna go from
Speaker 4: eighty seven and you're gonna add fifteen or thirty whatever,
Speaker 4: it is you'd expect that curve to go higher?
Speaker 3: How much the curve measuring? Okay, you say there's a
Speaker 3: forward power, so the forward.
Speaker 4: Power curve is a round the clock peak or off peak.
Speaker 4: There's three separate curves, and the difference between peak and
Speaker 4: off peak is actually you know, narrowed because data centers
Speaker 4: run twenty four to seven, so it depends on your
Speaker 4: North Texas or South Texas and those are in the
Speaker 4: high fifties.
Speaker 3: But what would we be seeing in the curves for like,
Speaker 3: or is there trading happening every twenty ten.
Speaker 4: Thirty might not be so liquid, but twenty seven and
Speaker 4: twenty eight certainly are.
Speaker 2: But there's other energy markets. So if you look at
Speaker 2: nat gas for instance, although exactly gas traders are really
Speaker 2: weird about the future's curve in gas, which I don't
Speaker 2: really understand. But if you look at that, you point
Speaker 2: out that over the longer term it's downward sloping, which
Speaker 2: suggests that there isn't going to be as much demand
Speaker 2: or maybe there's going to be more supply out in
Speaker 2: the future.
Speaker 4: I love it we're morphing into natural gas because that
Speaker 4: is the main driver of power prices, especially in Texas
Speaker 4: and the forward curve for gas is much more liquid
Speaker 4: than it is for power, and the forward curve for
Speaker 4: gas is inverted. It goes from three seventy to three
Speaker 4: sixty by the end of the decade. So, as my
Speaker 4: energy unlest Charles Johnson points out, the bigger driver there
Speaker 4: isn't data center demand. We're at six pcf day there
Speaker 4: a lot of people are at at ten twelve. We
Speaker 4: can get into that. But LNG exports. We're exporting eighteen
Speaker 4: bcf day. Now we're going to add another twelve. Like
Speaker 4: you'd think that curve would be at least upward sloping
Speaker 4: by twenty five cents. Cents by the way, you can
Speaker 4: trade that and your attractive broker's account. So that goes
Speaker 4: into is there going to be a lot of LNG.
Speaker 4: It starts getting outside of the expertise. But that's what
Speaker 4: we heard from a lot of clients last week when
Speaker 4: we went on the road all over New York City.
Speaker 3: This is very interesting. Actually want to ask another question
Speaker 3: about the pure power curve. But since we are on LNG,
Speaker 3: and then we can get back to the power curve,
Speaker 3: just setting aside data centers, et cetera. Intuitively, you would
Speaker 3: think that what is a growth business in the United
Speaker 3: States LNG exports. And in fact, one of the sort
Speaker 3: of policy debates around the whole question of building out
Speaker 3: LNG terminals is it's going to make gas more expensive
Speaker 3: for American consumers because now we're going to be competing
Speaker 3: with European buyers, Whereas when we didn't have LNG export terminals,
Speaker 3: we were just swimming in it because it had nowhere
Speaker 3: to go, nowhere to go. So it's very interesting to
Speaker 3: hear that, even with everyone acknowledging a booming domestic demand
Speaker 3: and be the expansion of international demand that downward sloping
Speaker 3: gas curve.
Speaker 4: Yes, maybe, I don't know. Maybe there reflecting world peace
Speaker 4: in Europe and Russia, LNG isnunacceptable to the rest of
Speaker 4: the world. That could be a driver.
Speaker 3: Then they'd have to rebuild that pipeline there.
Speaker 1: Yeah.
Speaker 4: But but back to our visual conversation on demand. The
Speaker 4: reason I was talking to the Encore CFO and asking
Speaker 4: him about this is he said he's holding two and
Speaker 4: a half billion dollars of cash collateral postings from some
Speaker 4: of that demand. And he's like, you're not some you know,
Speaker 4: Joe Schno startup. I'm gonna build a data center and
Speaker 4: connect to your grid if you're posting two and a
Speaker 4: half billion dollars, and he says, and this is what
Speaker 4: he said on their earnings call as well. You know
Speaker 4: that's real demand that is coming. It's it's it's material.
Speaker 3: I'm sorry, just now to go back to the power curve,
Speaker 3: which I get is much less liquid out there. But
Speaker 3: there are trades that happened. These are price, like, how
Speaker 3: do you infer volume from price? Because these are price, we.
Speaker 4: Don't get the volume. But it's a it's a yearly curve,
Speaker 4: and then right before the year starts us listen to
Speaker 4: twelve month curves and then it goes into weekly before.
Speaker 3: What I'm saying is, how do you infer what it
Speaker 3: expected volume in twenty twenty eighty. It goes from a price.
Speaker 4: Curve, Sure it's flat, it goes up a dollar from
Speaker 4: here to twenty thirty. Whereas if you're going to add
Speaker 4: twenty percent to your group demand and you'd expect it
Speaker 4: to go up, okay, several dollars a right gas side,
Speaker 4: I'd want to see forty cents fifty cents.
Speaker 3: I assue what you're saying, okay with pat.
Speaker 4: And then just to go back to the fore your
Speaker 4: upper fifties in Texas, low sixties for peak, and the
Speaker 4: data center companies are paying ninety five. So Vistra just
Speaker 4: did a deal off tenny five dollars a megab an hour, okay,
Speaker 4: for round the clock. So Vistra contracted out its commandche
Speaker 4: peak plant Texas ninety five dollars a megab an hour.
Speaker 4: So big Tech is paying a very pretty penny. You
Speaker 4: can argue some of that's for the CO two free
Speaker 4: aspect of it, and some of it's just a lock
Speaker 4: and the supply.
Speaker 2: So just to go back to the math and your
Speaker 2: overall argument, I mean, you're basically saying that utilities are
Speaker 2: already committed to building out. I guess twice as much
Speaker 2: capacity as is forecast to be needed by twenty thirty.
Speaker 2: So wildcard to me seems to be the demand forecast, right,
Speaker 2: and we're already seeing those change pretty wildly. I know
Speaker 2: you mentioned Bloomberg NEF, but you know they've raised their
Speaker 2: forecast because of the data center build out, so they've
Speaker 2: raised their forecast of how much energy is actually needed.
Speaker 2: How much confidence do you have in those demand numbers
Speaker 2: and how could they change over time?
Speaker 4: Moderate confidence. But like, look where we're at now, Like
Speaker 4: open Aye built all of CHATCHYBT using two gigawatts. All
Speaker 4: the big tech hyperscalers they haven't given their twenty twenty
Speaker 4: five volumes yet, but if you take their twenty twenty
Speaker 4: four volumes and then double it, and this is output.
Speaker 4: So I'm going to transfer it back to capacity and
Speaker 4: you assumer sixty percent capacity factor. All the hyperscalers combined
Speaker 4: around fifteen gigawatts, and that's got to be over half
Speaker 4: the data center demand. So to talk about ninety five gigawatts,
Speaker 4: I mean it's a staggering number. And then you get
Speaker 4: more advances in you know, Navidia chip efficiency. Yeah, obviously
Speaker 4: Jevins paradox kicks in. You've had numerous guests talk about that.
Speaker 4: It's just a lot of power, a lot of power.
Speaker 2: Can you just remind us one gigawatt is enough to
Speaker 2: power what I like these comparisons.
Speaker 4: There's a million homes, but it depends if you're in
Speaker 4: Florida or the Northeast, but generally speaking that's.
Speaker 3: Where you're at. Not only do I find electricity markets,
Speaker 3: so in market structure and electricity very difficulty at my head, around.
Speaker 3: Even after all of these conversations, I have built no
Speaker 3: heuristics or intuitions for what these A gigawat kill a
Speaker 3: lot mega like you say these things, and I know
Speaker 3: gigawats bigger than a kill a lot like what does
Speaker 3: actually mean? And then the fact that even there we're
Speaker 3: talking about the difference between a gigawatt and a gigwot
Speaker 3: hour and the like, I've yet to develop the sort
Speaker 3: of intuitions that I haven't.
Speaker 4: Haven't you seen back to the future, Yeah, oh, there
Speaker 4: you go.
Speaker 2: We got to print out, you know, a little tape
Speaker 2: like the way we used to do for credit ratings
Speaker 2: the financial crisis. We need that up there. And actually
Speaker 2: credit ratings are going to be interesting from a utilities
Speaker 2: perspective as well.
Speaker 3: Could I just ask, you know, obviously one of the
Speaker 3: sensitivity is in general with all of thics, data center
Speaker 3: and utilities, is this view, and I think it's kind
Speaker 3: of overstated. Is the average ratepayer going to end up
Speaker 3: paying for a lot of data centers or we'll raise
Speaker 3: our electricity bill? And I understand, like these are complex
Speaker 3: questions and the math isn't so clear. And also from
Speaker 3: what I understand, the emergence of a data center can
Speaker 3: actually lower the consumer's electricity bill because there's just that
Speaker 3: simple math, which is, if there's more buyers splitting the
Speaker 3: cost of the buildout, than actually your price tag can
Speaker 3: go down. But in the scenario you're laying out in
Speaker 3: which there's a bunch of upfront capital investments and everyone
Speaker 3: is very excited to build it out and at cart
Speaker 3: wires and you have to buy transformers and gear and
Speaker 3: all this stuff, if the demand does not materialize is expected,
Speaker 3: that does sound like conditions in which we could see
Speaker 3: consumer rates.
Speaker 4: Go up absolutely. So that's what we're spending all our
Speaker 4: time on. And it's state by state, and even within
Speaker 4: the same state, you've got numerous jurisdictions. So is it
Speaker 4: legislatively mandated or is it done by a rate case
Speaker 4: or in the case of Northern Indiana, have the companies
Speaker 4: themselves data center companies themselves gotten ahead of it and
Speaker 4: said we're going to put in a solution where rate
Speaker 4: payers are absolutely protected and get money back. So you
Speaker 4: look at nice source with Midwestern Utility. They own Northern
Speaker 4: Indiana Public Service NIPSCOE, and they've got a deal where
Speaker 4: they've got an inside rate base they've got a separate
Speaker 4: gen Co. So they and that Genco is doing a
Speaker 4: deal with Amazon and they're going to kick back a
Speaker 4: billion dollars over fifteen years two rate payers. So rather
Speaker 4: than have a debate, oh who's funding what it's like
Speaker 4: done and you get sixty seven million dollars a year
Speaker 4: and that's the blueprint, that's the gold standard.
Speaker 3: Yeah.
Speaker 4: I keep in mind, six months before that Genco was launched,
Speaker 4: nice Or sold twenty percent of Nipsco to Blackstone. So
Speaker 4: you could argue Blackstone said, hey, let's go ahead and
Speaker 4: do this. And then the utility right north of Indiana
Speaker 4: or northeast of the Indiana is Ohio, and the CEO
Speaker 4: of First Energy is a next black Stone guy, So
Speaker 4: maybe they look at doing a GENDO or something like that.
Speaker 4: That's pure speculation. I have no idea pack gas specific
Speaker 4: gas electric. They've done a deal where they've got rates
Speaker 4: in place that protect presidential rate payers Amerin has, but
Speaker 4: a lot of utilities don't. They don't have these protection.
Speaker 3: The point is someone if it turns out that there's
Speaker 3: an overbuild and there's not as much demand for it,
Speaker 3: someone's paying for it, and it either it's going to
Speaker 3: be the customers or perhaps the utility shareholders.
Speaker 4: I mean, you just the political risk of having mom
Speaker 4: and pop bail out, you know, Mark Szuckenberg, Jeff Bezos
Speaker 4: is just you can't have that happen. But again, six
Speaker 4: months ago this was coming up on the tail end
Speaker 4: of conference calls, and now these utility CEOs are having
Speaker 4: in the prepared remarks, so I'm pretty confident they're going
Speaker 4: to figure it out.
Speaker 2: You mentioned Blackstone just then. I do want to talk
Speaker 2: about who is currently making a lot of money from
Speaker 2: the data center build out, but just to stress test
Speaker 2: the thesis a little bit more, because it is a
Speaker 2: contrarian take, and so I think we should ask a
Speaker 2: bunch of questions about it. But does it take into
Speaker 2: account time lags for projects? So I think, you know,
Speaker 2: capacity build out in the energy sector is notoriously bureaucratic.
Speaker 2: That is one thing that Joe and I do actually
Speaker 2: know about the sector. Is it possible that a lot
Speaker 2: of these committed projects actually take much longer to get
Speaker 2: working on the ground than currently forecast.
Speaker 4: I think the delays will be on building the new generation,
Speaker 4: not the data center. So data center takes two three years,
Speaker 4: Even if that slips to four or five years. The
Speaker 4: power plants take six seven years, and as you know,
Speaker 4: you can't get a g Rnova gas turbine for years
Speaker 4: and years, which is obviously a bullish backshop here.
Speaker 3: Yeah, talk to us more about that element of it
Speaker 3: all because building out that let's if you overshoot on production,
Speaker 3: then that's a problem in itself. If you overshoot on
Speaker 3: production at a time when it's gotten really expensive because
Speaker 3: there's massive inflation in the construction sector, that's an even
Speaker 3: greater problem. Talk to us just about like, per any
Speaker 3: giving unit of productive capacity on the utility side, how
Speaker 3: much more expensive is it gotten and what do you
Speaker 3: think we're casting for that?
Speaker 4: Sure, so to build a combined cycle gas plant ten
Speaker 4: years ago is one thousand and twelve hundred kW to build.
Speaker 4: Then it got to two thousand. Then utility analysts like myself,
Speaker 4: I was like, WHOA, that's insane. Now we're up to
Speaker 4: three thousand, and then it's like, who's actually spending this?
Speaker 4: But that three thousand dollars a kW for a new
Speaker 4: gas plant compares to the data center itself that cost
Speaker 4: forty thousand dollars. So for Big Tech to spend another
Speaker 4: three to lock in their gas price, its their fuel source.
Speaker 4: It's like it's nothing. Oh, it's to Minimus, which goes
Speaker 4: back to the output four powers fifty five sixty and
Speaker 4: pick TeX's paying ninety five in the grand scheme of things.
Speaker 4: So the cost of the data center, it's nothing. So that's
Speaker 4: why our utility and just jaw dropping on how shocking
Speaker 4: it is Big Tech's willing to pay these amounts.
Speaker 3: What about if you don't measure production of new plants
Speaker 3: and dollars, but new plants in time and again, if
Speaker 3: you're talking about okay, well we can't get this turbine
Speaker 3: that is several years ago we could have got delivered
Speaker 3: next month. How much longer are these projects taken?
Speaker 4: So if you can figure this out, I think you're
Speaker 4: lusing this. If you figure this out, you can make
Speaker 4: a lot of money. Because obviously Inflation Production Act had
Speaker 4: enormous I'm going to vibe.
Speaker 3: Code a thing to figure it out.
Speaker 4: Keep going an inflation Production Act, enormous tax credits for renewables,
Speaker 4: and then the one big beautiful bill. Obviously clip those
Speaker 4: if you're not aligned by a certain date. So all
Speaker 4: this data center numbers are weighted towards the end of
Speaker 4: the decade, whereas the new solar is right here, right
Speaker 4: now rushing power prices. So you actually want to be
Speaker 4: a little short power for the next few years and
Speaker 4: then flip to being long. And if you can figure
Speaker 4: out when that flip is, you can make a lot
Speaker 4: of money in either the forward power curves or the
Speaker 4: natural gas curves. But as far as your original question,
Speaker 4: as I said, data centers two three years to build
Speaker 4: new power plants, four five, But then you don't need
Speaker 4: as many new power plants as everyone's saying. So Constellation
Speaker 4: CEO set on a call the other day he said
Speaker 4: he used the Texas market. He said, eighty seven gigawat
Speaker 4: peep market. You could add ten gigawatts to Texas tomorrow,
Speaker 4: which would be the equivalent of sending every single Navidia
Speaker 4: chip for an entire year to Texas and running them
Speaker 4: twenty four to seven. That's ten gigawatts because you can
Speaker 4: run it right now, existing grid, existing plants, for all
Speaker 4: but forty fifty hours a year. We stress tested it.
Speaker 4: There are some coal plants that can ramp up capacity factor.
Speaker 4: There's plenty of gas plants that can. So I don't
Speaker 4: know if it's forty hours, one hundred hours, one hundred
Speaker 4: and fifty hours, But it makes more sense to pay
Speaker 4: someone else not to run their chemical company, their refinery
Speaker 4: company for forty fifty hours a year, rather than have
Speaker 4: the utilities go out and spend ten billion dollars connecting
Speaker 4: far away wind farms. That's the argument. We're sort of
Speaker 4: come in the middle of it. But there is plenty
Speaker 4: of existing capacity on the grid that could ramp up
Speaker 4: to meet it and then have other guests to point
Speaker 4: it out on the odd bots, you know, the peak
Speaker 4: demand of the grid is eight hundred and fifty gigawatts,
Speaker 4: the overall size of the grid is are twelve hundred gigawatts,
Speaker 4: and then you're adding fifty gigawatts a year of solar,
Speaker 4: and then you're gonna start adding twenty gigawatts of gas.
Speaker 4: I mean, we're gonna handle it. I'm not really worried
Speaker 4: about any rochesters or anything.
Speaker 2: Oh yeah, talk to us about regional transmission, because this
Speaker 2: is something that we hear a lot. It's not necessarily
Speaker 2: the power generation that's an issue here. It's the transmission,
Speaker 2: which the US you know, seems to struggle with to
Speaker 2: put it mildly.
Speaker 4: So there's regional markets MISO, Midwest, the Mid Continent.
Speaker 3: ISO.
Speaker 4: These guys are tired the most amount of coal, so
Speaker 4: I think they're going to be in the worst shape.
Speaker 4: And then Texas, and then it depends if anyone builds
Speaker 4: anything in New England. New England's got the faraway more
Speaker 4: expensive power prices seventy dollars the rest of the countries.
Speaker 2: You know, I'm well aware.
Speaker 4: Yes I have two because I live in Connecticut. So
Speaker 4: if anyone builds a data center in New England, they're
Speaker 4: going to be the tightest. But after that it's really
Speaker 4: MISO and.
Speaker 3: No one's building data centers in Vermont where they occasionally
Speaker 3: have to switch over to oil and wood, right.
Speaker 4: I mean they ISO New England app, which we all
Speaker 4: have on our phone. Right, they were getting forty percent
Speaker 4: of their power from oil.
Speaker 1: Yeah.
Speaker 4: Yeah, the cold snap the other day and it's tough
Speaker 4: to talk about New England power without talking politics, and
Speaker 4: we're not going to go down that. So transmission is
Speaker 4: very important because you've got to connect all these far
Speaker 4: away renewables to the grid.
Speaker 3: You said something that I think is actually kind of important.
Speaker 3: There's this narrative meme you know, people talking about the
Speaker 3: AI race US versus China, and that one of the
Speaker 3: things I've seen people say China is going to win
Speaker 3: because they could just build out power more easily than
Speaker 3: we can. It sounds like, I know you're not an
Speaker 3: ai an list, but sounds like from your perspective, we
Speaker 3: don't know like what it means or who's going to
Speaker 3: win US versus China. But then from your perspective, power
Speaker 3: is not going to be the decider.
Speaker 4: Here, not in China. It's not, but it doesn't.
Speaker 3: You said, like, you know that we could ship every
Speaker 3: current with existing capacity. We could put every in video
Speaker 3: chip in Texas today and we could run them for
Speaker 3: fifty hours for all the all exception of a few
Speaker 3: really hot hours in the summer.
Speaker 2: I like the imagery of all the invidio chips going
Speaker 2: on a field trip to Texas, Texas.
Speaker 3: But it sounds like to your view, that really isn't
Speaker 3: going to be from the US perspective, that won't be
Speaker 3: the binding constraint.
Speaker 4: It's it's going to be a little tight. But I'm
Speaker 4: not one of these dooms theors. Oh, it's the absolute
Speaker 4: gating factor. It's all going to stop. I was in Shenzhen,
Speaker 4: China last year, and a robot got in one floor
Speaker 4: and the elevator went up and got off another one, Like,
Speaker 4: what is going on here?
Speaker 2: There's another reason we wanted to talk to you, aside
Speaker 2: from your capacity analysis, which is one of the interesting
Speaker 2: things that's been happening in the credit market is obviously
Speaker 2: private credit has been a big story for the past
Speaker 2: few years, but now private credit is getting in on
Speaker 2: the data center build out as well. There's sort of,
Speaker 2: I guess, getting on your turf a little bit in
Speaker 2: the public bond market, But what sort of activity have
Speaker 2: you seen there?
Speaker 4: Sure, so we think that's where the risk is going
Speaker 4: to is going to happen. And frankly, Bloomberg News broke
Speaker 4: the story and Pimco made two billion dollars on day
Speaker 4: one loaning to the Meta data center in Louisiana. So
Speaker 4: they priced twenty five billion dollars debt debt at two
Speaker 4: twenty over treasuries and it immediately started trading at one
Speaker 4: forty and handed Pimco two billion. Great for Pimco, but
Speaker 4: then everyone else nice to be Pimco. Is nice to
Speaker 4: be Pimco, especially the weather in Newport Beach. But everyone
Speaker 4: else in private credit is like, oh, these guys just
Speaker 4: made two billion dollars, we need to start lending to
Speaker 4: data centers. And we all know how this ends. Covenants
Speaker 4: start falling, great start falling. And again, if you're big tech,
Speaker 4: who cares if you overspend? Like you think AI would
Speaker 4: be all end all, you've been overspend. It's when you
Speaker 4: get down to the second tier. The QTS is the
Speaker 4: vantages of the world, and then you get down to
Speaker 4: sort of the ones below that, and you get like,
Speaker 4: you know, the core weaves and the nebiuses of the world,
Speaker 4: and you know there's a lot of shorts going out
Speaker 4: on Equinix, and obviously your guest Jim Chanos, and it's
Speaker 4: all about the chips. I'm not going to get into
Speaker 4: the chip debate, but it's interesting you look at a
Speaker 4: core even they got a fifty billion dollar market cap.
Speaker 4: That's a real company. You're gonna be around for a
Speaker 4: long time. But the bond market is saying we want
Speaker 4: a ten percent yield to win you twenty and thirty paper.
Speaker 4: You might not be a real company. And if you
Speaker 4: look at our supply demand outlooks, we're kind of in
Speaker 4: the camp of the bond market. But timing, which you
Speaker 4: mentioned earlier, Joe, is so key because this data center
Speaker 4: is you're gonna ramp for a couple of years, and
Speaker 4: the oversupply is really a twenty thirty event. So good
Speaker 4: luck timing that one.
Speaker 3: You said something you talked about that Pimco Meta deal,
Speaker 3: and this question has come up, and I still don't
Speaker 3: think got a totally satisfactory answer to it. Meta is
Speaker 3: a very highly rated company as you see it as
Speaker 3: a credit analyst. What is it about the private credit
Speaker 3: you know to talk about, Oh, it's flexible, et cetera.
Speaker 3: But your two twenty spread over treasuries is not nothing
Speaker 3: at all and is real? Is that two twenty spread
Speaker 3: really like worth it for like a little bit more flexibility,
Speaker 3: et cetera? Like what are they paying for exactly in
Speaker 3: the private credit market that they couldn't get it cheaper?
Speaker 3: I would think in the public bond market.
Speaker 4: I don't know, but I could speculate. There's okay, couple
Speaker 4: if the metal question is why did you put this
Speaker 4: off balance sheet? Yeah, so you've got the state of
Speaker 4: the art data center with the best Navidia chips out there,
Speaker 4: and you're a tech company in AI is the be all,
Speaker 4: end all for everything. Did you kick it off your
Speaker 4: balance sheet because you didn't want to damage your balance sheet?
Speaker 4: But the agencies are imputing it, but maybe quant funds
Speaker 4: running their screens, they don't impute that, So maybe that helps.
Speaker 4: Or maybe you didn't want the depreciation running through your
Speaker 4: income statement, maybe that helps, or maybe you want to
Speaker 4: walk from this thing in five years. I don't know,
Speaker 4: but one of those is definitely the reasons, because why
Speaker 4: else would you pay that much bigger spread one hundred
Speaker 4: and fifty BIPs over their borrowing costs.
Speaker 3: But so the key thing is here when you talk
Speaker 3: about that pimcoat meta deal, technically this is not meta debt.
Speaker 3: It is not it's okay, right, okay, So they create
Speaker 3: a vehicle, they're not gonna okay, that's I think that's
Speaker 3: an important element that they're not just arbitrarily paying a
Speaker 3: lot more for like a sort.
Speaker 4: Of and if you read the credit docs, they've guaranteed
Speaker 4: this debt even if the data center shuts down. But
Speaker 4: our understanding of the docks is if they sell it,
Speaker 4: then the guarantee goes away, and so that would create
Speaker 4: a little risk. But back to my utility routes. What
Speaker 4: happens that the data center shuts down for rate payers,
Speaker 4: and they actually have an explicit guarantee from META to
Speaker 4: protect rate payers, So they have that a lot of
Speaker 4: other utilities don't, so a lot of states Louisiana, Mississippi, Tennessee, Texas,
Speaker 4: they need to do better job protecting their rate payers.
Speaker 4: And by the way, that's just one line in the
Speaker 4: dock that could fall away in other new data centers.
Speaker 4: And that's what we spend our time looking at.
Speaker 2: You mentioned the credit ratings just then, So the rating
Speaker 2: agencies they look at the off balance sheet vehicles, even
Speaker 2: though it's not officially part of the company's.
Speaker 4: Debt, they impute the least payments and include that as debt.
Speaker 3: I see, and.
Speaker 4: For Meta specifically, they won't do that until the least
Speaker 4: starts when it comes online, but everyone's doing it.
Speaker 2: And then I was just thinking, I don't mean to
Speaker 2: labor this analogy too much, but you know, you started
Speaker 2: out by talking about all the exciting moments in the
Speaker 2: history of being a utilities analyst, and one of those
Speaker 2: was Enron, which I assume means you know, you have
Speaker 2: some experience with circular deals. But what do you think
Speaker 2: about all the sort of incestuous financing deals that seem
Speaker 2: to be happening between all the various players in the
Speaker 2: data center industry.
Speaker 4: You mean, we'll buy your equity so you can buy
Speaker 4: our chips.
Speaker 3: Yeah.
Speaker 4: Again, I'm on the side of bondholders in that one.
Speaker 4: Just look at the market caps, look at the bond yields, and.
Speaker 3: Explain what you mean by that. For so, like people
Speaker 3: who don't have a Bloomberg, so we've goes people like
Speaker 3: me who have a Bloomberg but are too lazy.
Speaker 4: So these names are going out and yeah in either
Speaker 4: open Ai or Navidia is going out and buying equity
Speaker 4: in these neocloud companies. So then they can go out
Speaker 4: and either supply the compute to open Ai and buy
Speaker 4: the chips from Navidia. So it's all very circular. And
Speaker 4: I think the example people used twenty years ago is
Speaker 4: Nortel was doing this called the vendor financing. So there's
Speaker 4: a little lot of skepticism on that.
Speaker 2: Okay, so we can't do a utilities episode. I know
Speaker 2: we've been focused on data centers, but we can't do
Speaker 2: a utilities episode without mentioning nuclear power. What's it going
Speaker 2: to take to actually get some capacity from nuclear sure.
Speaker 4: So obviously the Vogel plant was the last big nuclear
Speaker 4: plant in the line. Was supposed to cost fourteen billion.
Speaker 4: It ended up costing thirty two billion. It came online
Speaker 4: ten years late. No utility wants to take that risk.
Speaker 4: Now everyone's talking about these small modular reactors, and I
Speaker 4: think that's what you're going to start seeing is more
Speaker 4: talk of these. The only way we think a small
Speaker 4: module actor goes final investment decision FID is if big
Speaker 4: tech agrees to do two things. They agree to buy
Speaker 4: some SMRs and they invest equity in those SMR manufacturers
Speaker 4: to give them the capex to build.
Speaker 3: Which sounds like something they would do to be honest
Speaker 3: for sure.
Speaker 4: And I think that's the only way you get one
Speaker 4: of these off the ground. And I think if those
Speaker 4: stocks rally on that deal, they're all shorts because they're
Speaker 4: already reflecting several of those deals happening. So the big
Speaker 4: ones are our new Scale and Oaklow and Sam Outman
Speaker 4: of open AI used to be the chairman of Oaklow
Speaker 4: and then he stepped down so they could do a deal.
Speaker 4: So something along those lines would happen. That being said,
Speaker 4: Donald Trump has talked about doing work with Westinghouse and
Speaker 4: taking equity ownership to build another AP one thousand and
Speaker 4: Obviously President Trump is all about taking equity, but none
Speaker 4: of the utilities in my coverage are going to build
Speaker 4: something without some sort of backstock.
Speaker 3: We did an episode recently with an infrastructure investor and I,
Speaker 3: you know, I'm a journalist. I look at the past.
Speaker 3: I don't talk about the future. But I was put
Speaker 3: on the spot and I said, I think off the
Speaker 3: next twenty years. Gun to my head, we will never
Speaker 3: have another local We're not going to have another project
Speaker 3: like that in America. And sounds like you agree.
Speaker 4: I agree. I do think you see some SMRs. I mean, frankly,
Speaker 4: our country has been making nuclear submarines for sixty seven years.
Speaker 4: That's an SMR there. So I think that's the way
Speaker 4: it happens, is big tech goes in and does that.
Speaker 2: For sure, in twenty years, we'll have you back on
Speaker 2: to see whether or not both of you.
Speaker 4: This is my only writer.
Speaker 3: Wrong, I don't nothing about the future. This is my
Speaker 3: only one call. And I just don't think we're going
Speaker 3: to ever get them right. That's we're not going to
Speaker 3: get a bunch of those times.
Speaker 4: I'm with you on that, and in twenty years hopefully
Speaker 4: I can dial in from the beach.
Speaker 2: All right, we see you in twenty years then, no,
Speaker 2: probably before because this was a fantastic, this is great conversation.
Speaker 4: Thank you so much for coming on off of Thanks
Speaker 4: for having.
Speaker 2: Me, Joe. That was a really fun conversation.
Speaker 3: That's super fun. I love that.
Speaker 2: My the opinion or framing that I'm sort of coalescing
Speaker 2: around is that AI can be simultaneously under hyped and overvalued,
Speaker 2: right and actually throughout history, that's kind of what we've
Speaker 2: seen with transformative technology, right, Like think about the Internet bubble.
Speaker 2: The Internet changed the world, but it was a bubble.
Speaker 2: Think about railroads. Railroads in the eighteen hundreds changed the world,
Speaker 2: but also a bubble. So I think that's kind of
Speaker 2: it's kind of what I think. The key issue, which
Speaker 2: Andy and you both touched on is the timing, right.
Speaker 3: The timing, And yeah, I mean I think it's it's
Speaker 3: very interesting because of course his argument doesn't even you know,
Speaker 3: doesn't even rest on any valuations right now. It's like
Speaker 3: there's all of this expectation for build out there is
Speaker 3: you know, as he put it, there is a number
Speaker 3: for the amount of the volume of data centered demand.
Speaker 4: There is an.
Speaker 3: Amount that's being built up, and he's like, the second
Speaker 3: number looks bigger, and that's going to be a that's
Speaker 3: going to be a problem. Yeah, and the time to
Speaker 3: your point, like I thought, you know, really interesting observation
Speaker 3: he had was a little bit not tangential to his
Speaker 3: core idea, but this idea that some of our energy
Speaker 3: policies are encouraging a lot of production right now, particularly
Speaker 3: the expiring solar credits. At the same time, a lot
Speaker 3: of this demand is going to come online in the
Speaker 3: back end, et cetera. I do think, you know, it
Speaker 3: seems like a really definitely seems like a fun space.
Speaker 3: It's very far from when we were just talking about
Speaker 3: like utilities as raat proxy. So I think for old
Speaker 3: people to get income.
Speaker 2: Well, the other thing I was thinking about on the
Speaker 2: demand side is I think there's a tendency among AI
Speaker 2: bulls vibecoders such as yourself that's right to think that
Speaker 2: demand is just going to go one way, right, So
Speaker 2: there's going to be more demand for AI because I
Speaker 2: don't know every piece of software is going to be
Speaker 2: replicated through clod code or whatever, and so power demand
Speaker 2: is going to go up as well. But what we've
Speaker 2: seen so far is that these things are getting more
Speaker 2: and more efficient.
Speaker 3: They're definitely getting right, more and more efficient.
Speaker 2: Like faster than anyone expected.
Speaker 3: Yeah, you know, this is a little bit tangent to
Speaker 3: the point, but I do think like one of the
Speaker 3: recurring phenomenons that we're seeing across this industry is that
Speaker 3: every I mean and this is I guess it's a
Speaker 3: bowl case, which is that you know, even the optimist
Speaker 3: keep getting turned out to be too pessimistic. The pace
Speaker 3: of say like efficiency gains for the cost of processing
Speaker 3: a token dropping faster than people expected this morning, recording
Speaker 3: to this January twenty eighth ASML the big chip equipment company,
Speaker 3: way better than expected. The emails, the benchmarks for the
Speaker 3: models where it's like the optimists say, like maybe it
Speaker 3: could code at this level by twenty twenty seven, turns
Speaker 3: out it hits there by like you know, early twenty
Speaker 3: twenty six, etc. So like if you want to just
Speaker 3: make I'm not making any case here, but if you
Speaker 3: just want to make a bowl case, it's like even
Speaker 3: the optimists keep getting surprised to the upside. On the
Speaker 3: other hand, it's fascinating to hear him say, look at
Speaker 3: what the markets are saying. They're not pricing in any
Speaker 3: of these expectations. And I was particularly surprised because I
Speaker 3: didn't realize this that even like you know, for all
Speaker 3: of the talk of LERG export terminals, et cetera, that
Speaker 3: gas is expected to be cheaper a few years. Yeah,
Speaker 3: no than it is right now. Very interesting dissonance between
Speaker 3: that and the popular narrative.
Speaker 2: Maybe gas traders just aren't vibe coders yet.
Speaker 3: Then they would understand exactly how much more of this
Speaker 3: UH plan going.
Speaker 2: To Just from an energy perspective, though, there is a
Speaker 2: push and pull factor here, right, So on the one hand,
Speaker 2: everyone could use AI and demand goes up, But on
Speaker 2: the other hand, maybe it gets super super efficient and
Speaker 2: then demand goes down. I think that's that's the difficulty, or.
Speaker 3: It's just there is a number that's out there. It's
Speaker 3: like some sort of like some reasonable inferences about where
Speaker 3: it's going to go, and it's very high. And it
Speaker 3: was actually very striking listening to him talk about some
Speaker 3: of those super the hyperscaler numbers, because it's like where
Speaker 3: is it at up right? As he pointed out, Okay,
Speaker 3: chet GPT like came out two gig loots, et cetera,
Speaker 3: Like there are a ton of chet GPTs out there, right,
Speaker 3: and that's one of the most computationally intensive things. Like
Speaker 3: maybe there are reasons to think this is all going
Speaker 3: to go great, there's gonna be a ton of money
Speaker 3: made in AI, but you can't really just like get
Speaker 3: to the number. I don't know, I think he it
Speaker 3: was this was a very useful perspective, just sort of
Speaker 3: on some of this simple math, and the math sounds
Speaker 3: like a subtraction, like this sounds like what the sun
Speaker 3: is learning about.
Speaker 4: Well.
Speaker 2: The other thing I thought was really interesting was the
Speaker 2: response to your question about why would you finance these
Speaker 2: things off balance sheet if you're you know, this massive
Speaker 2: cash rich technology giant, and the suggestion there was, well,
Speaker 2: maybe at some point in the future, like five years
Speaker 2: down the line, you need to get rid of this liability.
Speaker 2: You don't want to deal with it.
Speaker 3: This is why we did that episode with the guy
Speaker 3: who has you know, the company doing the legal docs right,
Speaker 3: et cetera. This is why it's pretty crucial to understand
Speaker 3: some of these things, because some of the questions sound
Speaker 3: like Facebook's or Meta's option to walk away. Right, there's
Speaker 3: some call option implicitly to walk away, et cetera. And
Speaker 3: they how they what they could do, what scenarios, and
Speaker 3: what they would allow it to be do is obviously
Speaker 3: going to be pretty crucial for any investors in this
Speaker 3: off balance sheet paper. I did not know until you
Speaker 3: asked this whole idea that the ratings agency is, well,
Speaker 3: they don't look at his debt, they do back out
Speaker 3: a lease cost, and therefore it can inform their overall
Speaker 3: credit sustainability.
Speaker 2: Well, the other thing, you know, we touched on this,
Speaker 2: but there's more and more demand from investors for data
Speaker 2: center debt, right, like the space is getting more for
Speaker 2: some reason, the space is getting more competitive, and so
Speaker 2: naturally what you see in any other credit cycle throughout
Speaker 2: history is as demand pros and people are competing for deals,
Speaker 2: the documentation and the protections tend to be weird.
Speaker 1: You know.
Speaker 3: I find the existence of hype cycles for debt to
Speaker 3: be a little bit weird because I get like, oh,
Speaker 3: I really want to get into AI equity, right, because
Speaker 3: that could one hundred x next year, right, And it's
Speaker 3: like I'm really excited about getting into data centered debt
Speaker 3: because it might maaybe fifty BIPs more I find to
Speaker 3: be very strange, or one hundred BIPs more. It's like,
Speaker 3: if I haven't fixed look, I'm a simple, simple guy.
Speaker 3: But if I have a fixed income allocation, all I
Speaker 3: care about is minimizing downside and I don't really care,
Speaker 3: like what sector it is. I'm not participating in the upside.
Speaker 2: You're not going to get greedy, You're not going to
Speaker 2: get rich.
Speaker 3: I gotta get super rich. I'm like, I just don't
Speaker 3: want to lose my like for fixing COF. I just
Speaker 3: don't want to lose my money.
Speaker 2: Fair enough, all right, shall we leave it there?
Speaker 3: Let's save it there.
Speaker 2: This has been another episode of the All Thoughts podcast.
Speaker 2: I'm Tracy Alloway. You can follow me at Tracy Alloway
Speaker 2: and I'm Joe Wisenthal.
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