TMTB: The Non-Bubble that disappointed both Bulls and Bears -- how Sam's Splurge changed everything
The worst kept secret among Tech market participants — just something AI bulls don’t admit out loud: they want a price-action bubble every bit as much as the bears do.
Both want to see that steep, “blow-off” ascent that characterizes parabolic tops. Why? The AI bulls are all fully loaded for a vertical melt-up and AI bears want the aftermath so they can yell “I told you so.”
It’s obvious to AI bulls (us included) that we’re not in an AI bubble. The non-argument is simple: valuations are reasonable (NVDA near 20x), the equity risk premium is almost 300bps above where it troughed in the tech bubble, operating margins are rich, and we’re still very early in the demand/build out of the AI supercycle.
But bulls will typically follow this argument up by saying “‘it’s more like ‘97/’98.”
Implicit in that statement is that they’re hoping the inevitable outcome is a ‘97-’99 style ramp, with all hoping it would occur as soon as possible. Why? The simplest answer is usually the right one: everyone likes bigger bonuses as soon as possible.
Stated succinctly: the “AI bubble” ascent was the paradigm that both bulls and bears were operating under for most of this year, or longer.
Bad news for the AI bulls and bears: the past few weeks has brought an end to that paradigm and led us to an unexpected turning point in the dynamics of the AI trade/narrative. On the 3 year anniversary of ChatGPT’s release, no less.
And we have Sam’s $1.4T 30GW splurge to thank for it.
Sam’s Splurge (we’ll call it “SS”) opened up AI “pandora’s box,” shifting the AI narrative in unexpected ways.
First, the overarching discussion has shifted to a greater focus on OAI’s ability to monetize and what that means across the Tech ecosystem, from ad platforms to software/services companies to GPUs to infra hosting like ORCL. Despite the behemoth it already is, the market began to appreciate it was taking implicit bets on what is still a 3 year old start up industry/company.
Second, SS and connected deals brought more focus to the interconnectedness of the whole ecosystem, OAI’s outsized role in it, circular financing, and “too big too fail” discussions.
Third, SS and his “Give us a few months and it’ll all make sense … We are not as crazy as it seems. There is a plan.” opened up discussions about government’s role in AI. While government intervention would help accelerate the AI buildout, it also opened a doorway of investor doubt. Reader CIO At CG expressed these opposite outcomes well in TMTB Chat:
“It’s bullish if/when it happens. But until it happens it creates doubt if it is gravy (more upside) or if it’s needed to execute the 1trn+ commitments. Any doubts on ability to execute the 1.4trn is just bearish sentiment vis-à-vis today. So Friar opened a door that was closed. And by opening it, it opened both the left and right side of the distribution. It also makes people realize that they are too big to fail: if they fail to execute they will bring the entire ecosystem multiple down. And hard.”
Fourth, the sheer scale of the SS $1.4T plan, which is nearly the size of the whole private credit market, nudged both public and private lenders to reprice AI-linked risk, most notably seen in the rise of Oracle and Coreweaves’ CDS spreads. At the same time, off-balance-sheet structures—e.g., Meta’s $27B Hyperion SPV with Blue Owl— didn’t help by concentrating risk with private creditors and muddying system-wide leverage mapping.
The ironic thing is, if SS would have been half the size, things would have continued to grind along, investors would have enjoyed the ‘27 and ‘28 visibility, maybe even building the energy for a large vertical ascent in price action. Instead, it had the opposite effect: pouring too much gasoline on the fire and drowning out the energy for a big move up.
Fifth — by locking in commitments eight years out, SS dragged the long-horizon AI debate into the present. Over the last few weeks I’ve heard an increasing amount of bulls give voice to risks they’ve been able to normally wave away over the first 3 years of the AI trade, in an unusual sign of humility. Some of the key existential questions that now feel more present in the discussion:
How does the grid support the post-’28/’29 buildouts and what about water, land use, and local pushback? We’ve already heard of local governments slowing DC buildouts, and this week the WSJ wrote how Bernie and others are dialing up scrutiny of Data Centers
If inference moves to phones/PCs/cars, how does that rebalance hyperscaler capex, useful life assumptions, and who captures value? What’s the risk of stranded assets if models plateau or workloads shift to cheaper/edge solutions?
The AI catch-22 no bulls want to talk about: If enterprise agents and automation work as advertised, what’s the path for unemployment and wages? If white-collar unemployment rises, what happens to ad spend and consumer wallets — remembering that GOOGLE and META are cyclically exposed ad businesses at their core? How does the seep into their top line and capex trajectory? If AI models don’t deliver, do we get a capex hangover and productivity disappointment?
All of this sits against a U.S. backdrop that’s still skeptical of AI — worried about job loss and asking for a slower, safer rollout — which can swing sentiment and policy quickly. Will the current administration still be as supportive of the AI rollout if sentiment and unemployment shift in a more negative direction?
These are issues that will be a lot more prominent in the next 3 years of the AI trade than they were in the first 3 years of the AI trade.
This all began to seep into the price action of AI stocks several weeks ago: ORCL giving back all of its “monster RPO” move and more, very speculative sectors like Nuclear/Quantum rolling over, and the AI ecosystem progressively rallying less and less on each Open AI deal that was announced.
It all culminated in the last two weeks. We can give thanks to some hawkish fed speak and Sam’s now infamous BG2 pod appearance for providing the spark needed to ignite the fire spreading. In a period of time where nothing has changed fundamentally in respects to the AI trade, the market began more heavily digesting the overarching effect of SS: more unknowns and more uncertainty in the minds of investors. After all, the market isn’t just a mechanism for discounting fundamentals and perceived risk, but also the current emotional state of participants. With belief shifting from inevitable euphoria (read: vertical ascent price action) to verification, SS has had the opposite effect of what Altman likely intended: more multiple compression and less belief in out year estimates.
With greater uncertainty, it’s no wonder certain pockets of the market have underperformed: names with perceived questionable business models / debt issues (ORCL, CRWV, NBIS, Miners, etc.), names with perceived AI top of funnel / structural issues (DUOL, MNDY), names with rising opex as the market is less confident in how long heightened spend will be here to stay (META).
It’s also no surprise that as the market digests these new developments, the profitability factor has outperformed while names with good narratives and fast growth but little in the way of valuation support have underperformed: NET, PLTR, SHOP, TSLA, U. This is also why memory has been so strong: EPS revisions are currently happening —> there’s nothing uncertain about opening up your favorite DRAM/NAND spot price checker, seeing how much DRAM/NAND has risen overnight, and plugging it into your model. These names are arguably more attractive in the current environment than they were before.
The market is currently doing what it always does after a narrative/paradigm shock: digest, recalibrate, reassign risk premia. NVDA EPS and Gemini 3 are the next events on the docket to absorb. We’re running low gross while we let the market do its thing, letting the overarching narrative/price action stabilize and become clearer.
Dylan at Semianalysis joked this week that time is now divided in BC (Before ChatGPT) and AD (After Da Launch of ChatGPT). We think the AI trade will eventually be divided between BSS (Before Sam’s Splurge) and ASS (After Sam’s Splurge). BSS and ASS.
Wait - that doesn’t have a nice a ring to it, so let’s say it differently. We think the straight-line giddy phase of the AI trade will give way to something healthier: a phase where fundamentals and idiosyncrasies matter even more. Tech will always be a narrative and boom and bust heavy investing sector (that’s part of the fun), but in a landscape where sentiment is more balanced, stock-picking will become more relevant. That’s a good thing.
SS popped the non-bubble. But the AI trade isn’t broken: it’s simply entering a more mature, scrutinized phase.