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SemiAnalysis · · 34 min

Ep. 007 - The 3 Choke Points Killing the AI Boom (Core Research) | Nick Doyle, Nigel Chiang, Konrad Wang, Jordan Nanos

Jordan NanosNick DoyleNigel ChiangKonrad Wang

Podcast
TL;DR
  • The AI infrastructure supply chain is "constrained at almost every layer," and the market is trading it exactly that way — hyperscaler spenders are down big year-to-date while investors chase "whatever has the biggest shortage." Konrad Wang's three choke points: TSMC N3, "where everything starts... sold out through 2027"; InP-based continuous-wave lasers for co-packaged optics; and PCB/CCL substrates, with shortages running all the way down to the drill bits.
  • PCB is a bottleneck because AI servers need 30-40+ layer boards versus sub-10 for consumer electronics, and only a handful of suppliers can make the high-grade materials. Ajinomoto is one major ABF film supplier, and perhaps one-to-three vendors (Doosan named) can produce the thick, high-voltage CCL — low yields, long lead times, and much higher premiums than these vendors previously commanded selling into commercial electronics. Taiwanese PCB names Unimicron and Kinsus are up over 100% YTD and "keep hitting the limits" of Taiwan's 10% daily move cap; a literal drill-bit stock is up 92%.
  • Nigel Chiang's construction call: modular data centers are ~10-15% of builds today and there's "no reason why that can't go north of 50%," because modular solves the scarcest input — field labor. He expects standardization to create single-vendor lock-in for a hyperscaler, with Comfort Systems the name he flags; and in gas power, labor is "probably the most binding" constraint — GE Vernova, Siemens Energy, and Mitsubishi have roughly 100GW of combined global capacity, but can't divert slots to higher-priced US demand even if they wanted to because there is not enough labor to build the plants. Argan, which Nigel calls the only pure-play gas EPC, rose about 9% on earnings and 30%-plus the next day.
  • On memory, Nick Doyle concedes the bear logic — OpenAI/Sam Altman letters of intent and LTAs locking in pricing have "typically been the sign of the top" — but argues this cycle is different because of prepayments. The team thinks prepayment terms will be priced "way higher than everyone expected," changing memory players' through-cycle financials, and "that's not understood" — they are "incrementally even more positive" and would defend the pullbacks, including Micron's sell-off on "an incredible print."
  • Top signals, per the desk: a rising frequency of Twitter victory laps from "the same retail names," and unambiguously positive news getting sold — which Micron just demonstrated. The self-aware joke lands too: Jim Cramer calling SemiAnalysis "the gospel" and Dylan Patel asking how to short himself may itself be a sign. Konrad's comfort check: as long as hyperscalers and neoclouds keep spending, and free-cash-flow/ROI analysis holds up, "diamond hands." Wega's aunt is reportedly getting "a lot of alpha" by watching Taiwanese Jim Cramers pitch stocks.
  • AI adoption still looks early: Nigel says his former investment-banking colleagues "are not using AI at all," while Jordan jokes that they may be buying "the Anthropic basket without using any AI" to analyze it. Jordan says the product is "crossing over 25 billion in ARR, like 4× in 3 months or something crazy"; SemiAnalysis estimates vary from roughly 70 people to Jordan's later count of 79 in the general channel, and the firm spends $5M annualized on Claude with some $10,000 days. Nick's pitch problem: even computer-savvy friends won't install Claude Code — "I'm trying to sell you fire insurance to a burning house."
Digest · the substance, structured for research

1. Everything is short — N3, lasers, and substrates

  • Nick Doyle's explanation of Core Research: ten vertical teams each deliver "extremely detailed models," and the Core Research desk "sits beneath all 10" distilling technical work into actionable insights for hedge funds, long-onlys, and now "even some quant guys." The context: GPU rental prices are rising — Jordan's image from last week, "trying to get the last flight out."
  • Konrad Wang's map of the choke points: "TSMC N3 is where everything starts... it's sold out through 2027," with hyperscalers doing internal allocations to manage trade-offs; second, InP-based continuous-wave lasers for co-packaged optics — a major theme this year; third, PCB/CCL substrates, where shortages extend "even to the drill bits."
  • The tape confirms it: "people don't like the spenders" — hyperscalers down big YTD — while the market buys "whatever has the biggest shortage."

2. PCB: 40-layer boards and a handful of suppliers

  • Konrad's primer: AI server PCBs run "30, 40 plus layers" versus sub-10 for commercial electronics, requiring specialized fiberglass grades such as T-glass, low-Dk glass, and L-glass, with "much lower yield" and longer lead times, plus more precise — and more numerous — drills. The supplier base is tiny: Ajinomoto is one major ABF film provider, and only "maybe one or two, maybe three suppliers" (Doosan named) can make the thick, high-voltage CCL — hence much higher premiums than these vendors previously commanded when supplying commercial electronics.
  • Nick's framing of why this suddenly matters: "It just didn't matter a couple years ago. It all has to do with the end of Moore's Law" and the move to GPU-based compute demanding new materials.
  • The price action, per Konrad: "this year is the year of networking. Last year was probably the year of ASIC accelerators" — Lumentum +100% YTD, AAOI +200%, Unimicron and Kinsus up over 100% and repeatedly pinned at Taiwan's 10% daily limit, Elite Material (CCL) +70%, and Nigel's favorite story — literal drill-bit companies, one up 92%.

3. Time-to-market: modular construction and the labor choke

  • Nigel Chiang's thesis: modular is ~10-15% of data centers today with "no reason why that can't go north of 50%," because it moves the scarcest, most expensive input — aggregated field labor — into a factory. He expects standardization to create lock-in: "what's the point of having two guys doing it" once one design is set, making Comfort Systems his name to watch.
  • Behind-the-meter power and modular are "different expressions of the same thing, which is time to market... The moment you bring GPUs online, revenue flows" — install plants on site rather than wait three years for grid interconnection.
  • The unappreciated angle: labor is "probably the most binding in gas power plants." GE Vernova, Siemens Energy, and Mitsubishi have roughly 100GW of combined global capacity, but "even if they wanted to, there's not enough labor to build these power plants." Argan, which Nigel calls the only pure-play gas EPC and which the team first highlighted in November, rose about 9% on earnings then 30%-plus the next day — "evidence of higher pricing power... coming through into their P&L."

4. Memory: the LTA top signal versus the prepayment counter

  • Nick grants the bear case its logic: OpenAI letters of intent and long-term agreements that lock pricing have "typically been the sign of the top" — once buyers say "just give us a price and we'll lock it in for three years," upside is capped and "the stock prices don't work anymore."
  • His counter, hedged as team view: "we think that this time there'll be a really big prepayment aspect that completely changes the financials of the memory players through cycle," with prepayment pricing "way higher than everyone expected — and that's not understood." He'd defend the pullbacks, is "incrementally even more positive," and notes that Ray and Mats That Matter were early in calling out that capacity is not arriving as quickly as people think — even '27-into-'26 CapEx pull-ins don't fix supply.
  • On top signals generally, Nigel offers two: rising "victory-lapping" screenshots from "the same retail names" on Twitter, and stocks trading down on "unambiguously positive" news — which Nick says Micron just did, "selling off an incredible print." Nick's joke candidates: "We just saw Dylan go on CNBC, and we just saw TBPN get bought." Plus Wega's aunt in Taiwan getting "a lot of alpha" by watching Taiwanese Jim Cramers pitch stocks.

5. Claude Code: fire insurance for a burning house

  • Nick's adoption puzzle: even "very computer-savvy, computer-programming-type friends" won't clear the install hurdle — "I'm trying to sell you fire insurance to a burning house." His own conversion came only because "my boss is pushing me to do it": after Doug told him that his plain-Claude IRR calculator was wrong and "not what I'm talking about," Nick went back in, asked it to manipulate data and produce outputs, and his "jaw dropped" — a moment even bigger than ChatGPT in 2023.
  • Jordan says the product is "crossing over 25 billion in ARR, like 4× in 3 months or something crazy," alongside Super Bowl ads and New York Times coverage. Konrad's version: GenAI "turned from reactive to proactive" — he's building a personal RAG, running scraping bots, and "Claude for Excel is just so good." Konrad estimated about 70 people at the firm; Jordan later counted 79 in the general channel. SemiAnalysis spends $5M annualized on Claude, with some $10,000 days.
  • Nigel's confirmation and kicker: his ex-IB colleagues "are not using AI at all" — Jordan's gag is that they may be buying "the Anthropic basket without using any AI" — which Nigel reads bullishly as early innings. Using Claude for Excel, "if someone tells me that this is AGI... I wouldn't have a strong pushback," and this is on current-generation hardware, before the Blackwell- and Rubin-vintage models come in.
  • Closing hedge from Konrad: expect volatility from macro and "the war"; the desk needs to tie supply-demand to CapEx sustainability via free-cash-flow ROI work. Until then: "Diamond hands."
Jordan Nanos

All right. Hello, everyone. Welcome back to SemiAnalysis Weekly, episode 7. We're here with the Core Research boys, Nick, Konrad, and Nigel. We're going to chat about what Core Research is, talk a little bit about our latest newsletter note, which we covered a little bit last week, and then go into some of the research that these guys do. Welcome to the show, guys.

Nick Doyle

Hey, thanks for having us, Jordan.

Konrad Wang

Happy to be here.

Jordan Nanos

Awesome. For those who don't know, let's start with a quick introduction to what Core Research is. This is probably our flagship product. The boys are sitting back-to-back in New York City, in the office, in the pit, heads down and grinding every day, and we're going to try to avoid mic feedback during this podcast. Outside of that, what do you guys work on every day? Give me the high level.

1. Core Research Distills The Data

Nick Doyle

Yeah, let me jump in there, just because I feel like I explain this a lot to our clients. Even our own clients don't really understand how it works when they're first starting. The way that I explain it, hopefully in a way that makes sense, is that this side of the SemiAnalysis research house is structured into 10 different teams. I call them verticals. They each deliver their own model. These are extremely detailed models supported by very technical drivers, and each of the team members on each of the teams is extremely intelligent. The talent pool here is incredible.

What these different teams deliver with their models and technical updates gets sent out to clients via email. We, the Core Research boys, sit beneath all 10 of these verticals and try to distill this technical information into actionable insights for investors. Our customers, the people we interface with the most, are investors: big funds, hedge funds, long-onlys, and even some quant guys are starting to drip in here. That's a little bit of what we do at a high level. Does that make sense, Jordan?

Jordan Nanos

It makes sense to me because I know what you're explaining. Hopefully, it makes sense to the audience, too. I also know what your backgrounds are. You guys have diverse backgrounds, both working in finance and as investors on the sell side or buy side, but then also working in the industry a little bit. Thinking about you, Konrad, with your software engineering background as well, it's not like you guys are strictly focused on finance. Maybe it's just the fact that the industry vertical lead, or model lead as we would say at SemiAnalysis, takes the lead on that range of research, and then you guys distill it down to the investors who are trying to make decisions.

Let me set the stage here. We put an article on the free-tier newsletter about GPU rental price increases and how much things have changed. Dan and I were joking last week that it feels like trying to get the last flight out because prices are rising, and then they're just gone. There's no more capacity left.

But you guys have been swimming in choke points for the last few weeks or months, right? Everybody is trying to understand what happens when all of this CapEx is poured in by TSMC, by many of the players and hyperscalers on the cloud side, and by all the labs. There are some choke points that bubble up, right? Maybe we can walk through those one at a time when it comes to things that are top of mind, like memory, construction, and wafer fab equipment. Konrad, maybe we can start with you, going all the way back to the beginning of the supply chain at TSMC. You've got your TSMC jacket on.

Konrad Wang

Yep. Yep.

Jordan Nanos

Very nice. What are they thinking about most right now when it comes to choke points, in terms of how they can deploy their CapEx and expand?

2. The Supply Chain Choke Points

Konrad Wang

Yeah, absolutely. I think the AI infrastructure supply chain is constrained at almost every layer. Obviously, with the big article today, the conclusion of the choke point is that we're seeing higher GPU rental prices, right?

It's also pretty interesting if we look at the price action for stocks. People don't like the spenders, like the hyperscalers. They're all down big year to date, and then people are trying to buy whatever has the biggest shortage. From my side, and then Nigel and Nick, feel free to jump in and add your coverage as well, I think TSMC N3 is where everything starts. That is the biggest shortage. It's sold out through 2027.

Hyperscalers are all doing internal allocations to offset the trade-offs. That has a lot of implications for clean rooms and wafer fab equipment. I know Nick is doing a lot of big research. We haven't published it yet, so I can't really dig in, but there are lots of implications on wafer supply and demand.

The second big one, at least in my coverage, is lasers—namely, InP-based lasers used in optical transceivers. A big theme this year is co-packaged optics, where they use continuous-wave lasers, these very powerful lasers that use a lot of InP. So there are lots of shortages there as well.

The third one that I see is PCBs and CCL substrates. For our audience that doesn't know what they are, PCB stands for printed circuit board. Every single chip, GPU, or accelerator has a printed circuit board, and the sizes are getting bigger and bigger. We're not seeing a lot of substrate availability. CCL is copper-clad laminate, which is the material used to build PCBs. There are lots of shortages there as well, extending even to the drill bits used to make these PCBs. So at least those are the big 3 that I'm seeing. Nigel and Nick, feel free to jump in, or Jordan, if you have any follow-up questions.

Jordan Nanos

No, all good, man.

Nick Doyle

Yeah, I want to jump in and ask Konrad more questions, just because it almost takes us a step back and a little bit higher level. I think, first, it speaks to the incredible nature of SemiAnalysis as a firm. All 3 of us come from different backgrounds, generally finance backgrounds. I wasn't a specialist in wafer, raw wafer silicon, or in the hyperscalers. I barely looked deeply at hyperscaler CapEx until I came to this firm.

Konrad wasn't diving into co-packaged optics testing and PCBs until we joined. It's through the incredible talent pool that's sharing ideas and collaborating that we're able to really accelerate our learning and, of course, use Claude Code—we can get into that later—to take us to the next level and to the leading edge of what the bottlenecks are. Everyone cares about bottleneck investing lately.

Going back to the PCB question, what are PCBs, why do they matter, and is the PCB environment changing so much? Why are we seeing this become a bottleneck? What about the technology is so different with GPUs that we need different substrate materials?

Konrad Wang

Yeah.

Jordan Nanos

Also, just to double-tap on Nick's earlier point about us really going deep on semiconductors, Dylan Patel, our CEO, was on Jim Cramer yesterday. Jim Cramer said they think we're the god of semiconductors, and that when we bless something, we're apparently always right and we're the most honest guys. I don't know if we're always right, but—

Konrad Wang

I think you're really—

Jordan Nanos

We strive, yeah. We are truth-seeking for sure.

Konrad Wang

Yeah, we strive to be as objective and go as detailed as possible.

Jordan Nanos

Specifically, Jim referred to the SemiAnalysis research as the gospel, and then Dylan tweeted out asking everybody if he should short himself or how he could short himself.

Konrad Wang

Short semis?

Jordan Nanos

Yeah.

Konrad Wang

Please don't. Please don't.

Jordan Nanos

All in good fun. I think I'd probably go find some local San Francisco craft stores that are making these one-off T-shirts, flowy T-shirts, and flowy pants that Dylan uses everywhere. I think we've got to find a way to short those boutique fashion stores where he's getting all his nice clothing.

Konrad Wang

Yeah.

Jordan Nanos

I don't know any other Dylan Patel-specific stuff. Maybe headphones?

Konrad Wang

Headphones.

Nick Doyle

Maybe headphones, yeah. The flowy pants are a big hit in New York, I think.

Jordan Nanos

Yeah, we need a proxy for this guy. Hot pot, headphones—something in the San Francisco area. I think they'll do fine without him anyway.

Let's dig in on PCBs. Let's use that as an example because maybe you could run us through what they are and why people think about them. If people think of a GPU shortage, they think of NVIDIA or Amazon.

Konrad Wang

Right.

Jordan Nanos

Who's a PCB vendor? What is it used for? Can you take me through that?

Konrad Wang

Yeah, absolutely. I think the biggest ones are all Taiwan-based local suppliers.

3. Why AI Boards Are Bottlenecks

Konrad Wang

PCB itself—PCB stands for printed circuit board. Think of it as a board that connects different parts together. If you ever build a laptop, it’s the green or black board that chips are mounted on.

AI server PCBs are extremely complex. Commercial electronics might have fewer than 10 PCB layers, but as things get more intense, you’re looking at 30, 40, or more layers. Those require specialized materials and more precise drilling. Because they’re thicker, they require more drills as well. Broadly speaking, you can think of it as the motherboard of a server.

The raw materials that make PCBs are sheets of fiberglass, per se, with copper foil bonded on each side. Those are what we call copper-clad laminate. If we go even a step deeper, these fiberglass materials have different levels as well, like T-glass, low-Dk glass, and L-glass. These all signify different levels of performance. As you can tell, higher-performance, higher-grade ones have much lower yields, and because of that, they have longer lead times. We’re seeing a big backlog in all of this.

With that, these companies, because it’s only being sold by a handful of suppliers, are able to charge a much higher premium than before, when they were only supplying commercial electronics.

Jordan Nanos

Is this the same style of shortage as memory or NAND flash? It sounds mildly complex, but producing fiberglass with copper at a high level, for a general audience, doesn’t seem quite as complicated as producing a GPU. Is it raw materials or production capacity? Are the PCB companies just being opportunistic and jacking up their prices? That doesn’t quite seem like the Taiwanese cultural way that we’ve seen. What’s the price action in the market?

Konrad Wang

I think it’s just that there are so few suppliers in this space. For example, if we look at the substrate side, there really is 1 major supplier, which is Ajinomoto Build-up Film, or ABF, the ABF provider. If you look at CCL, there are only maybe 1, 2, or 3 suppliers that can really make the really thick, very hard CCL.

For these materials, I think Doosan is one, and then there are probably a couple more. Those materials also have much lower yields because they’re much thicker. They’re much harder to produce: They need to withstand higher voltages, and the production process is a lot harder than it is for lower-end glass, for example.

Nick Doyle

I’m going to add that this just goes back to the fact that this didn’t matter a couple of years ago. It all has to do with the end of Moore’s Law and the move to GPU-based compute. Going to the next level of GPU-based compute requires all these new materials, and I think that’s the coolest thing, frankly.

Jordan Nanos

Yeah.

Konrad Wang

With Nigel writing about construction companies and the power electronics guys, I don’t think they ever thought they would be selling into data centers. Now there’s this massive boom in TAM, which is pretty crazy.

Jordan Nanos

Do you have any favorite higher-level stories about massive price action in some of these companies, or just weird stuff going on across clean rooms, lasers, and PCB construction? What’s a favorite story that you’re seeing right now?

Nick Doyle

Clean room hasn’t really moved. I think it’s the optics that have been the most chaotic.

Konrad Wang

Yeah. Optics are crazy. Lumentum is up about 100% year to date. AAOI is up 200%. I think this year is the year of networking. Last year was probably the year of ASIC accelerators. This year, everyone’s talking about CPO and lasers. Substrates are all up as well because of the shortages.

The big 3, right? Unimicron and Kinsus are both up over 100% year to date. In Taiwan, the stock market has a limit, so you can’t go up further than 10% each day. They keep hitting the limits. Quite wild. CCL, Elite Material, is up 70% year to date. It’s a crazy time to be in the market.

4. Modular Construction Accelerates Data Centers

Nigel Chiang

I think in the industrial space, which is where I spend most of my time, the trend of data centers moving to modular construction is going to be big, and it’s still in its early innings.

Call it 10% to 15% of data centers today that are modular. We see no reason why that can’t go north of 50% if you really listen to what the guys at Meta and Google are saying. The reason for that is that SemiAnalysis has been really good at keeping on top of data center delays, and that has partly to do with labor shortages and other constraints.

What modular does is solve for that in a way, because now you don’t have to aggregate your field labor, which is the scarcest, most difficult-to-gather, and most expensive form of labor, and send it out to a site to actually construct the data center. You construct these modular blocks of electrical systems off-site in a factory and then ship them to your project location to be assembled.

We think the modular story is really going to be big. There’s 1 company that’s really good at that: Comfort Systems. What people don’t appreciate is that as a hyperscaler does more modular, it becomes standardized. It doesn’t make sense for, say, Google or Meta to have Comfort Systems and No. 2 doing it, because what’s the point of having 2 guys doing it if it’s going to be modular and standardized?

There’s going to be 1 standardized design that Comfort Systems has done for Google. So there’s going to be lock-in for a certain hyperscaler customer. I think this is really within the construction space, which we’ve recently done more work on. This is something worth paying attention to.

Jordan Nanos

Can you comment at all on modular and its relationship to behind-the-meter power generation? It seems like some of those are intertwined, where, 3 or 4 episodes ago, we had Jeremy on talking about how next year, over 50% of new data center builds are going to be behind the meter for generation. That has to impact not just the shell itself, but also turbines and all sorts of switchgear and equipment that’s actually going to power the thing as well.

Nigel Chiang

Behind-the-meter and modular data centers are all different expressions of the same thing: time to market. The faster these guys can stand up data centers, the better, because we’re in a supply-constrained environment for AI. The moment you bring GPUs online, revenue flows. Behind-the-meter is the same thing: Instead of waiting 3 years for that grid interconnection, you install power plants on-site to power those data centers.

Where it also overlaps with modular construction and Comfort Systems is the labor aspect. When we were looking into construction, we realized that labor shortages are probably most binding in gas power plants. If you talk to GE Vernova, Siemens Energy, and Mitsubishi, and ask them, “Globally, between the 3 of you, you have, I don’t know, 100 gigawatts of capacity. Why can’t you divert your slots from, say, the Middle East or Europe to the US, where your prices are much higher?” what they’ll tell you is that even if they wanted to do that, there’s not enough labor to actually build these power plants.

I think what Jeremy was talking about was how a majority of, or an increasing share of, data centers that are going to be built will be behind the meter. I think there’s also this unappreciated labor angle to it that’s really worth paying attention to. Some of these stocks are really moving on this trend.

Jordan Nanos

What’s a stock exposed to labor in this space? I don’t know if you’re going to give away all this, but I can’t even imagine what 1 of the stocks would be.

Konrad Wang

Well, memes aside, I think there is only 1 pure-play gas EPC. These companies are called EPCs—engineering, procurement, and construction. That’s Argan, and we’ve been positive on the name for a long time. I think we first called that out when, Nick, you were working on that.

Nigel Chiang

Or was it Konrad?

Nick Doyle

That was Derek—

Nigel Chiang

Yeah, called that out.

Nick Doyle

In November.

Jordan Nanos

Okay. Yeah, that makes sense.

Nigel Chiang

The earnings a couple of days ago were interesting. I think the stock reaction on the day was up 9% or something, and the next day it was up 30-plus percent.

Jordan Nanos

Really? Okay. Wow.

Nigel Chiang

Just evidence of higher pricing power.

Jordan Nanos

Because—

Nigel Chiang

Because they have a shortage of labor, and it's coming through into their P&L.

Jordan Nanos

Makes sense. Okay. The last thing that obviously jumps to mind, that we've talked about on what feels like 3 sequential shows, is memory. You guys kind of covered both ends of the spectrum: the inputs to the fab and some raw materials, and then the inputs and raw materials to the data center itself. But as both those things flow together, they actually create some products. Are there different ways in which the different components have been moving most recently when we think across GPU, CPU, memory, networking, and all the other stuff that's actually going to go inside those data centers when TSMC expands and pours in its $56 billion in CapEx, or whatever Shravan said they were going to do on last week's show, and that filters its way through the industry with more chips?

Nick Doyle

For memory, there are a lot of different angles you can talk about. It's been in investor focus for the last 6 months, and I think Ray, our memory expert, and Mats That Matter were a little early in calling out that capacity isn't coming online as quickly as people think. Even with these CapEx pull-ins from 2027 into 2026, it still doesn't impact supply.

Not to give too much away, but I think incrementally we're even more positive on the theme itself. I think we would defend the pullbacks in memory stocks because there are a couple of different dynamics that make these players even stronger through the cycle than in prior cycles.

Jordan Nanos

Yeah. Let's talk about the stuff that's in the news right now. There's been a lot of discussion about how these OpenAI letters of intent that Sam Altman was signing could be impacting memory stocks and why sentiment is down. What's your impression of public sentiment around memory stocks right now, and why has there been recent price action in those stocks?

Nick Doyle

I think it makes a lot of sense why there's negativity. Historically, when we're starting to see these LTAs—these long-term commitments that lock in pricing—that has typically been the sign of the top. Everyone gets excited because demand is skyrocketing, supply is capped, and prices go through the roof. That's been happening.

Now we're saying, “Okay, we don't want to see any more price increases. Just give us a price, and we'll lock it in for 3 years, and then we can keep moving on.” When that happens, historically, the stock prices don't work anymore because it's kind of capping the upside. So it makes sense that the public is seeing that, because, like you said, there are hints of this happening.

But I think what Ray and we think is different—there are a couple of different dynamics. I don't want to share too much, but the main thing is the prepayments. We think that this time there'll be a really big prepayment aspect that completely changes the financials of the memory players through the cycle. Also, the pricing that those terms are based on is way higher than everyone expected, and I think that's not understood. That's why we're still bullish on the theme.

Jordan Nanos

Last week, I had the guys that went around the horn. I said, “When we get to the top, there will be signs,” right? Do you have any creative interpretations for how you answer that question from investors—what's the sign of the top in any cycle? It could be the broad AI—

Nick Doyle

We just saw 2. We just saw Dylan go on CNBC, and we just saw TBPN get bought.

Jordan Nanos

Oh, this is the top. New media selling out.

Nigel Chiang

On my end, I'll offer 2 signals. I know we all have Twitter accounts, et cetera, and one thing I like to look out for is an increase in the frequency of people victory-lapping screenshots of their personal accounts. Usually, if you squint, it's all the same retail names. That's one.

Second, I think, as stock guys like Konrad and Nick, you guys will agree with me: when news comes out unambiguously positive, but the stocks trade in the other direction, I think that's also pretty indicative.

Nick Doyle

We really saw that with Micron, and that's another thing that was fueling the fire about, “Okay, this round is over. We're selling off an incredible print. Let's move on to the next thing.”

Nigel Chiang

I just want to add that we have one of our employees, Wega, who's based in Taiwan, and he was telling me that his aunt has been getting a lot of alpha just by watching the Taiwanese Jim Cramers pitch stocks.

Back to your earlier point, Jordan, one of my favorite stock stories that I just remembered is these PCB drill-bit companies. They are literally drill-bit companies, and their stocks are up. I just looked at the chart. It's up 92%.

Konrad Wang

So if Wega's aunt is making easy money, you'd think people would start to get a little jittery. But I think as long as the big hyperscalers are spending, neoclouds are spending, and we're going to do some free-cash-flow analysis on how this all ties back to ROI, I think that'll give us comfort.

Jordan Nanos

Makes sense. Yeah.

Nick Doyle

I do just want to get out there: I heard those guys talk a week ago, 2 weeks ago, and I think they all agreed—and I totally agree—that it does feel early in terms of the cycles that are going on. I say that just because the incremental use that I get out of Claude Code and similar CLI tools is just—

Jordan Nanos

Okay. Yeah.

Nick Doyle

Incredible. And I know that hasn't flowed through enterprise. People still don't even know what it is. I've said at the beginning of the year that by the end of the year, everyone will know what it is. I don't know that everyone will be using it, but I'm leaning into the thesis that by the end of the year, my family—my grandparents—will start asking me questions about Claude Code. So my point of view is pretty positive.

5. Claude Code Crosses The Adoption Hurdle

Jordan Nanos

Yeah. Let's talk about Claude Code, though. From personal experience, there was this moment: December 2022, ChatGPT launches. In January, February, or March 2023, something happens, and my grandmother asks me questions about this thing, ChatGPT, right?

I'd been personally using GPT-3 in the OpenAI Playground since 2020. But when they obviously ran the SFT and had a chatbot, it was so different that it made it all the way to my grandma.

What do you think it takes to get Claude Code there? They're crossing over 25 billion in ARR, like 4× in 3 months or something crazy, right? They have Super Bowl ads. They have New York Times articles about them getting into a war with the Department of War. What more does it take to get broad industry recognition—to make Claude a household name like ChatGPT?

Yeah. Go for it.

Nick Doyle

It's a great question. I honestly don't know the answer because I've pitched it to so many of my friends now, and even some of my smartest friends still don't want to use it. There is a hurdle of understanding—basically understanding what it is and what it can do—and then installing it on your PC. For whatever reason, that hurdle is really high even for some of my very computer-savvy, computer-programming-type friends.

Jordan Nanos

Well, that's—

Nick Doyle

From my point of view, it's awesome because that just gives me more time to use the tool before everyone else.

Jordan Nanos

Yeah. Good alpha for you.

Nick Doyle

Right? I'm trying to sell you fire insurance to a burning house.

Jordan Nanos

What did it take to get you over the hurdle, and when did you get over that hurdle to start using Claude Code for the first time?

Nick Doyle

Right. Totally applicable because I think Doug had mentioned in December, “Hey, this is amazing. You should use it.” And I was like, “Okay, I'm going to try and use it.”

I used just Claude, right? I think this is everyone's experience—or not everyone's, but I would assume a lot of people's experience. Okay, I'm using Claude to build a program, or whatever it is. Then I get back, and I'm all proud: “Hey, I built this IRR calculator.” And he just looks at me, and he's like, “That's not what I'm talking about. That's wrong.” And I was like, “What?”

So I go back in, and I figure it out. Just like that ChatGPT moment that I had in 2023, I typed in a couple of questions and literally my jaw dropped.

Just like that, but even more so this time, I was asking it to manipulate data and give me some outputs. My jaw dropped. So, coming back to your question, I think the reason I jumped over the hump is because my boss is pushing me to do it, right? I think not everyone has that situation.

Jordan Nanos

Yeah. Yeah. Makes sense. Konrad, how about you?

Konrad Wang

Yeah. On that point, I think the real Claude Code moment for me—I mean, obviously, we have Doug and Dylan really encouraging us to use it—was that I realized generative AI turned from reactive to proactive. It used to really just be a chatbot, and I also had to keep questioning where the source was: Is ChatGPT hallucinating things? With Claude Code, it really brought agentic AI to life.

For me personally, my biggest use case is that I’m building my own personal RAG. I’m constantly having bots scrape certain information so that I can be as up to date as possible. And then it improves a lot of my efficiency. I don’t really draw charts anymore. I was an Excel-heavy user, but now Claude for Excel is just so good. It is so good. There are just a lot of use cases there.

For adoption to really grow from here, enterprise use cases just need to increase. I have a lot of friends who are in banks, in consulting, and in these more traditional industries, and I think the adoption rate is just not there. Obviously, there are a lot of compliance reasons, but very few firms are like SemiAnalysis, where we’re very forward-thinking and very encouraging in terms of AI tool usage. And rightfully so, because this is our bread and butter.

I think very few companies are willing to spend. For us, we have, what, 70 people today working at the firm, and we’re spending $5 million on Claude. Is it each month or each year? I forgot.

Nick Doyle

It’s a year—an annualized number.

Jordan Nanos

Yeah, but we’ve had some $10,000 days at this point.

Konrad Wang

Right, right, right, right. So I’m very grateful that I’m able to be part of this curve.

Jordan Nanos

Yeah. And by the way, we have—

Konrad Wang

So it’s really a good time.

Jordan Nanos

We have 79 people in the general channel. I just checked.

Konrad Wang

Absolutely crazy.

Jordan Nanos

Almost at 80, whenever the next person starts, which is soon.

Konrad Wang

Yeah, I was employee 42.

Jordan Nanos

Yeah, yeah, yeah. Now you’re in the 50th percentile almost, man.

Konrad Wang

Yeah.

Jordan Nanos

Of tenure. Nigel, how about you? Are you using Claude Code?

Nigel Chiang

Yeah. Yeah. I just want to follow up on what Konrad said. Personally, I was in investment banking before this gig, and I still keep in touch with those guys, and they are not using AI at all. It’s kind of crazy to think about, but to me, there’s also an upside to it, which is that we’re probably still in the early innings, and there’s still a long way to go for adoption.

Jordan Nanos

What stocks are these guys buying that are not AI-related? They’re buying the Anthropic basket without using any AI to do that analysis.

Nigel Chiang

Exactly. Yeah, that’s really one way to think about it. Claude for Excel has been incredible. This last week, I was shipping out a note and really using Claude for Excel, and more than once I had this thought in my mind: If someone tells me that this is AGI, I don’t think it would be a statement I would strongly push back against because it’s gotten so good.

To think that it’s still running on current-generation hardware, before the Blackwell-vintage and Rubin-vintage models come in, is frankly crazy to think about.

Jordan Nanos

“Vintage,” man. That’s such a good word for these models trained on this BF16 Hopper model. I’m going to put these weights aside from this 2025 vintage and let them age for a little bit. See what Llama 3 tokens taste like in a few years’ time, after they’ve had some time to age. I love that.

Okay, guys, I think this has been awesome. Great to get to know Core Research in a little bit more detail. Any final closing comments on Claude Code, the memory cycle, or CapEx? Stunned silence. Awesome, man.

Konrad Wang

Diamond hands. Diamond hands.

Jordan Nanos

Okay, last one.

Konrad Wang

I think we’re going to have a lot of volatility with the macro stuff and with the war. On our side, we really need to figure out how all this ties in together with supply and demand, the sustainability of investing, and all this high CapEx. For our institutional subscribers, we will have something out soon. For our public audiences, we will have some form of synthesis coming out as well.

Jordan Nanos

Subscribe for more. All right, guys.

Konrad Wang

Subscribe for more.

Jordan Nanos

Pleasure having you on today. Look forward to the next one and, yeah, good job.

Ep. 007 - The 3 Choke Points Killing the AI Boom (Core Research) | Nick Doyle, Nigel Chiang, Konrad Wang, Jordan Nanos | BidClub