Arthur Hayes's Long Article: When Will the AI Wave Crest? Why Am I Still Buying ETH?

Original Article Title: Situationship

Original Article Author: Arthur Hayes
Article Translation: Azuma, Odaily Planet Daily

Looking around, humankind has transformed the Earth's natural environment into a different landscape. Some changes are awe-inspiring, some are heart-wrenching, but without exception, they all started with one or more evolved primates—humans—conceiving an idea in their minds.

As the brain needs to process a vast amount of information every day, we constantly create various narratives to make the world coherent and meaningful. It is for this reason that narratives themselves ultimately shape reality.

For investors, to predict the future price fluctuations of the market, they must understand which "collective illusions" market participants commonly believe in. The same company, under unchanged future cash flows, may receive vastly different valuation multiples simply because the market has bought into different stories.

The simplest way to achieve a "valuation reset" for a originally dull and uninteresting company is to replace its narrative with a new one that aligns with the current market trend, compelling investors to eagerly embrace it regardless of the cost.

Is There Really an AI Bubble?

This also raises the core question of determining whether AI is currently in a bubble.

However, before discussing the AI bubble, it is more worthwhile to first answer a more fundamental question, "What exactly are we investing in"—in relationship terms, it's like asking, "What exactly are we?"

At least to me, a somewhat "Luddite" leaning individual, the key lies in how the market defines AI Capital Expenditure (AI CAPEX)—does it fall under Technology, or Real Estate?

The mainstream narrative in the market today considers this multi-trillion-dollar-scale AI infrastructure construction to be part of "Technology," and therefore should enjoy a highly elevated growth valuation.

But my view is quite the opposite. AI CAPEX is fundamentally nothing more than another dull and uninteresting real estate investment. The only difference is that this time, the data centers are filled not with office buildings but with computing power. This computing power will eventually give birth to silicon-based lifeforms, driving the advancement of human civilization, a significance that may even surpass the railroad revolution of yesteryears.

The reason why it is necessary to distinguish between "real estate" and "computing power" is because nowadays those nascent yet matured hedge fund managers, banks, private credit funds, and even governments mistakenly believe that they are lending to a tech giant like Apple, rather than providing real estate financing to a Lehman Brothers.

I believe the ultimate reason for the AI bubble to burst will be that financial intermediaries will overbuild data centers, along with all the necessary supporting infrastructure around data center construction, including energy, power, and everything needed for AI chip training and inference.

Therefore, the AI bubble is more akin to a 2008-style credit bubble rather than a profit bubble like the 2000 Internet bubble.

During the 2000 Internet bubble, most publicly traded Internet companies had almost no revenue, let alone profit, for example, Pets.com. Thus, that bubble was fundamentally a problem of the "earnings story."

However, the 2008 financial crisis was different. What truly triggered the crisis was the slowdown in U.S. house price appreciation, leading to concerns from banks and financial institutions about the repayment capacity of mortgage assets, making it a credit story.

The AI bubble will also follow a similar logic. The real inflection point will not be when AI leaders stop making money, but when the growth rate of data center construction starts to decelerate, or when the hyperscalers revise down future data center construction guidance.

Even if AI leaders continue to earn massive profits, their forward multiples will still contract due to declining growth expectations. The first to fall will be the most financially fragile, highly leveraged AI companies.

Subsequently, these risks will quickly transmit to financial institutions with large AI debt assets and similarly high leverage on their balance sheets. Eventually, the government will once again intervene in the name of "national security" to ensure that these overly leveraged AI companies and the financial institutions behind them do not collapse.

And this misallocated capital will ultimately flow into the crypto market... sending Bitcoin "to da moon" once again.

AI CAPEX Credit Risk

Whenever someone claims that "AI is in a bubble," AI advocates almost always bring up the "Jevons Paradox" as a rebuttal. Jevons believed that when the price of a commodity falls, its usage increases significantly, causing the overall market size to continue to expand, even exponentially.

If you think that AI capital expenditure itself represents a demand for computing power, then according to the Jevons Paradox, there is indeed nothing to worry about. As the cost of computing power continues to decline, the demand for AI Token-consuming applications and AI Agents will experience exponential growth. Therefore, lending to AI infrastructure is naturally a foolproof (money good) business.

However, I believe this is actually a misinterpretation of the Jevons Paradox. To understand why the Jevons Paradox does not mean that all credit flowing into AI CAPEX will be rewarded, let's take a look at what a hyperscaler is really doing when building a data center.

Fundamentally, it is first embarking on a real estate development project. It constructs a building to house server racks and then acquires the latest generation of semiconductor chips for AI model training and inference. And as industrial technologies—especially semiconductor manufacturing—continue to advance, the floating-point operations per kilowatt-hour of electricity (FLOPs) will continue to grow exponentially.

In a few years, whether it's Nvidia, AMD, Intel, Huawei, or SMIC, they will all introduce a new generation of AI chips that are far more efficient than today's. At that time, the same data center will be able to output over 1000 times more Intelligence while consuming less power.

This means that two things can coexist: on one hand, the construction of physical infrastructure like AI data centers could reach saturation; on the other hand, the consumption of AI Tokens can still experience exponential growth.

So, the real question to consider is, do you want to hold onto a real estate business—that is, what today's cloud computing giants are doing; or the AI application layer?

The common retort from AI advocates is that the hyperscalers are both landlords and tenants. They rely on the massive cash flow generated from the "attention economy" of the Web 2.0 era to support debt issuance for data center construction; at the same time, they leverage their AI capabilities to sell the "Apple of wisdom" from their Garden of Eden to the world.

If you truly believe in this story, then I hope you hold their stock, not their bond. There is a reason why bonds are called Fixed Income—no matter how successful a company may become, bondholders' best-case outcome is merely getting back their principal plus a little interest.

If Google, by successfully betting on AI, creates a revolutionary product capable of altering the course of human civilization, and the stock price soars, then shareholders certainly have a reason to cheer. However, what bondholders can receive remains just the principal.

Conversely, if Google eventually degrades into a "data center landlord" renting out a large number of depreciated NVIDIA GPUs, yet fails to earn sufficient income to repay the debt and interest, then bondholders will suffer heavy losses. The worth of a data center filled with outdated chips is also highly questionable.

The CFOs of cloud computing giants and Wall Street financiers are not fools. They are aware they are essentially in the real estate business. Hence, they must find some "greater fools" to make them believe they are investing in high technology, not real estate.

These greater fools include insurance companies under alternative asset management giants like Apollo, as well as taxpayers of various countries who will ultimately foot the bill for government implicitly guaranteeing AI credit.

If you carefully pore over those deliberately convoluted financial statements, you will discover that a significant portion of the debt issued to finance AI CAPEX is almost entirely kept off the balance sheet, with little clear connection to the core profit-generating business supporting stock valuation.

How we define AI CAPEX determines how we understand the entire AI investment cycle. This narrative explains why there is a severe capital misallocation and why the scale of this bubble may surpass that of the railroad bubble.

More importantly, since the AI bubble is a credit bubble, not a profit bubble, when the crisis erupts, the government will undoubtedly step in to rescue those ultimate greater fools who mistakenly mistook traditional real estate debt for new tech equity assets.

Do not assume the AI bull market is over just because of recent corrections in the AI sector, especially in leveraged markets like South Korea. On the contrary, the truly insane "blow-off top" phase may just be getting started.

Just last week, the Fed had the opportunity to address persistently above-trend inflation across various metrics through a rate hike, but it chose not to do so, opting to stay put, with even former Chair Powell casting a vote in favor of holding rates steady.

So, for those crypto players who have been forgotten by the market and can only struggle in a sideways bear market, is AI credit allocation a good thing or a bad thing, and what does it have to do with anything? The key is that it determines how and why governments around the world will ultimately print money to fill the financial hole created by runaway AI CAPEX investment.

The following content of this article will revolve around this theory and explain why governments will ultimately have no choice but to resort to printing money to rescue the economy.

With AI CAPEX growth slowing down while credit continues to expand, Bitcoin will bottom out and begin a long-term uptrend. When decision-makers finally realize that the highly anticipated AI GDP growth is essentially just another regular real estate bubble, they will have to embark on a monetary easing even larger in scale than the 2008 Global Financial Crisis (GFC).

Ultimately, this will drive Bitcoin to surpass $1 million, and even higher.

The Second Derivative Determines Everything

I always have to remind myself: "What truly matters when investing is not the growth itself, but the acceleration of growth."

In other words, what we are actually focused on is the second derivative—whether the growth is accelerating or decelerating.

This actually makes a lot of sense. When an asset is still in an accelerating growth phase, people will constantly weave stories about its infinite future possibilities. Thus, in the market, you will hear declarations like, "I would rather see a cloud computing giant go bankrupt than miss out on the opportunity to build AGI (Artificial General Intelligence)."

However, all growth will eventually enter a deceleration phase. The issue is that the price trend of most assets is often:

· Accelerating Growth Phase: Prices continue to reach new highs;

· Decelerating Growth Phase: Prices move sideways in consolidation;

· Only when growth itself (i.e., the first derivative) turns negative do prices truly begin to drop.

No one can accurately predict how long the transition from growth deceleration to actual negative growth will last, but many investors, myself included, tend to subconsciously believe—even as growth starts to decelerate, asset prices can still infinitely rise.

If the AI bubble is essentially a credit bubble, then the importance of the second derivative becomes even more pronounced. Because the entire society's willingness to continue financing AI CAPEX is based on an assumption—that the scale of AI investment will continue to accelerate indefinitely.

Once this acceleration disappears, continuing to increase debt becomes increasingly dangerous, but the reality is, no one knows when to stop until they've really been punched in the face.

You either wait for a financial crisis to erupt; or for "Kenny G" (Odaily Planet Daily Note: here, it refers to Ken Griffin, who recently took over the AI stock god position at a low price)

to take away all your assets at the market bottom.

Therefore, even though investment growth has begun to slow down, the credit scale often continues to expand. Only when the AI CAPEX budget truly starts to decline, will the market usher in that classic "Wile E. Coyote" moment—where the character has already run off the cliff, only realizing there's no ground beneath when looking down, and then plummets instantly.

At that time, the market will begin to identify who has become dangerously leveraged due to holding a large amount of junk AI CAPEX debt.

Let's apply this logic to the U.S. subprime crisis. My favorite course during university was one that studied U.S. housing policy and the mortgage market. The instructor had served as the Deputy Secretary of Housing during the Clinton administration. Interestingly, I took this course in the spring of 2008—the exact time when Bear Stearns collapsed, talk about timing.

The core point conveyed in this course was that in order to achieve the social equity goal of "homeownership for all," the government continuously encouraged more people to buy homes, leading to ongoing credit expansion. However, by 2006, many first-time homebuyers were actually unable to afford the monthly payments after the loan interest rate reset. The only way they could continue to make payments was if housing prices continued to rise at an increasingly faster rate.

Of course, I'm still waiting for the government to deliver my "forty acres and a mule" (a historical U.S. land compensation promise). In that case, why not just print money and build houses?

The following quad chart illustrates:

· S&P 500 Index;

· U.S. Mortgage Lending and Construction Activity;

· Case-Shiller U.S. Home Price Index.

By the end of 2005, the U.S. housing price appreciation had begun to slow, coinciding with the peak of actual construction investment spending (orange line in the first chart). However, real estate credit (purple line) continued to flow into the market until the stock market peaked and started to experience a slight pullback.

The period from 2006 to 2007 can be described as the "no man's land" before the entire crisis unfolded. During this time, home prices were still rising, but the rate of increase was continuously slowing down. Subsequently, the stock market peaked in mid-2007 (pink dashed line in the chart). The real "Jaws of Death" moment occurred in August 2007 when three credit hedge funds under BNP Paribas collapsed. The crisis then spread continuously, ultimately bringing down Bear Stearns and Lehman Brothers in September 2008... Before that, the S&P 500 had already fallen about 50% from its peak.

What truly triggered the financial collapse was when investors finally discovered who exactly held those toxic "Frankensteinian" financial derivatives. In the end, the government had to simultaneously take over the debts and equity of these institutions to avert a new Great Depression.

This is crucial because when discussing how the government saved the AI industry later in the text, we will revisit this logic.

The second chart is equally worth noting. It illustrates the onset of capital misallocation, precisely when home price appreciation began to slow. If new credit was still being used to build more homes, the issue would not be as severe. However, if the entire system began relying on rolling over old debt with new debt, risks started accumulating. The rising ratio of construction loans to construction investment spending exemplifies this process.

Now, apply the same analytical framework to AI. The key variable here corresponds to each company's CAPEX expenditure plans.

The current market belief is that real estate (here referring to AI) is tech; the more tech investment, the higher future profits. Hence, the market rewards cloud giants that announce increased capital expenditure budgets by boosting their stock prices.

I anticipate that the growth rate of AI CAPEX announcements will begin to slow down in mid-2027, and by 2028, the market will notably enter a "deceleration phase."

Meanwhile, a seemingly contradictory phenomenon will occur. Although the CAPEX growth rate is starting to decline, the scale of credit flowing into AI will continue to expand. The reason is that lenders believe they are investing in technology rather than real estate. In addition, governments around the world keep emphasizing the need to take a leading position in global AI competition. Therefore, continuing to finance any project related to AI CAPEX seems to be the most reasonable choice.

Thus, 2027 will become a "no man's land" similar to 2006 to 2007. The current significant correction in AI stocks is just a normal adjustment in a bull market. The real AI bubble peak will occur next year.

After that, the market will start rewarding the cloud computing giants who "first exit the arms race" and actively reduce their CAPEX budgets. Unlike the early stages of the bubble from 2022 to 2026, future cloud computing giants will find it increasingly challenging to rely on their own free cash flow to support AI investment. They will have to rely more on issuing bonds and issuing more stock to raise funds.

The pressure on the balance sheet will also force management to seriously consider, "Is it really worth continuing to borrow money to build more data centers just to accommodate more chips that will constantly depreciate?"

At least for the American cloud computing giants, the lower-priced cutting-edge AI models from China, with almost the same performance, will completely extinguish their "Silicon Valley deity" fantasy. After all, if two products are of the same quality, or just slightly inferior, the vast majority of people will choose the cheaper one.

With the intelligent output per kilowatt-hour of AI chips continuing to grow exponentially, and under competition pressure from China where the cost per Token keeps decreasing, a rational cloud computing giant CFO would not further deteriorate their balance sheet just to build more data centers.

Even following Jenkin's paradox, the explosive growth in AI Token demand will eventually come, this growth is not happening fast enough to offset the negative impact of the large amount of debt issued several years ago. In the end, the market will first punish the participants with the worst credit. Then, people will truly realize how much capital has been wasted in this AI investment frenzy.

I cannot predict which cloud computing giant will be the first to go overboard, triggering a collective "Oh shit!" from bond investors.

However, before discussing why banks, knowing the huge AI investment risk, still have to continue lending, let's take a look at the following chart. It shows the comparison between the committed CAPEX investment scale of major cloud computing giants and their cash on hand.

What actually underpins the entire AI bull market narrative is a leverage in the scale of trillions of dollars. Among these companies, eventually, one will fall from grace like the once market-darling AI prodigy Leopold Aschenbrenner. The difference is that when the time comes to rescue them, it won't be the greedy and neurotic East Coast hedge fund managers on Wall Street, but the money printers in the hands of Warsh and U.S. Treasury Secretary Bessent.

The Dilemma of Bank Credit

Many believe that the AI CAPEX growth rate is about to slow down, indicating that the AI bubble is nearing its end. If that's the case, why would banks still keep lending?

The reasons are actually quite simple: first, because it is profitable; second, because the government wants them to do so; third, because they know that even if the loans turn into bad debts, the government will step in to help.

Louis-Vincent Gave of Gavekal Research published an interesting article last week. He believes that Warsh's interest rate policy actually follows a very simple logic - actively steepening the yield curve.

Doing so has two benefits. First, it can make bank lending more profitable; second, it can gradually dilute America's huge debt burden through inflation.

Eventually, banks will continue to create new loans, in other words, create new currency. This new additional funding will provide financing for the re-industrialization of the U.S. manufacturing sector and will continue to support the development of AI. This approach is highly consistent with the recent emphasis by Treasury Secretary Bessent on "Hamiltonian Economics."

If we look at all objective economic indicators, the Federal Reserve should have actually raised rates at its most recent monetary policy meeting, but the fact is that it didn't. On the contrary, long-term bond yields subsequently surged.

· Odaily Note: The 30-year US Treasury bond yield surged after the Fed stayed put.

Many believe this was a policy mistake by the Fed, but from a bank's perspective, it was a godsend.

The reason is simple. Banks can fund themselves at nearly the cost of the Federal Funds Rate, a rate deliberately kept by the Fed below the nominal GDP growth rate, and even below the actual inflation rate.

Subsequently, banks lend out the funds in the form of long-term loans to AI data center developers, rare earth mining companies, defense contractors, and so on. The steeper the yield curve, the higher the Net Interest Margin banks can earn.

And as shown by the chart below of commercial and industrial loans outstanding, banks are more incentivized to continue creating new money through lending.

· Odaily Note: The white line represents the 10-year US Treasury bond yield minus the Federal Funds effective rate (reflecting the steepness of the yield curve); the yellow line represents the balance of US commercial banks' commercial and industrial loans.

From a political perspective, this is a sustainable Fed policy. Even though the Trump administration's Department of Justice has investigated and even sued some Fed governors (such as Lisa Cook and Powell), these voting members still support keeping short-term rates in negative real territory.

In other words, Warsh effectively has a "volunteer alliance," including people from the Trump camp and those who have been deeply affected by "Trump Derangement Syndrome" (TDS) but remain within the system.

From a monetary policy standpoint, the Fed's recent actions have also allowed Treasury Secretary Besent to issue short-term bonds (T-Bills) at a yield below the nominal economic growth rate. If the market cannot absorb the massive weekly Treasury issuance, the RMP (Reserve Management Program) will step in to fill the demand gap by printing money.

To suppress the "disobedient" and continuously rising long-term bond yields, Besent can also implement bond buybacks—first issuing short-term bonds monetized by the Fed, then using these funds to repurchase 10-year or 30-year bonds, thereby lowering long-term rates.

It is worth noting that Warsh, who has always been known for advocating for Fed balance sheet reduction, now shows no intention of restricting or even stopping the expansion of the RMP program. All of this is nothing more than a kabuki-style UFC performance on the White House lawn.

If you are a credit officer at a "Too Big to Fail" (TBTF) bank and are looking to advance your career and increase your salary in the future, then you are almost certain to approve loan applications belonging to "Key Industries," such as AI, defense, and so on.

The reason is simple. This not only increases the bank's profit but also aligns with the policy direction of the Federal Reserve and the Treasury Department. Even if the loan ultimately defaults — a very likely scenario from a mathematical perspective — the government will definitely quickly deploy a "Bazooka-sized" rescue plan.

There is almost no downside risk here. This is the true operation of "Window Guidance" in the United States.

I believe that the 2026 version of the "Treasury-Fed Accord" has already quietly taken place, just without formal announcement. Otherwise, how else can you define the current situation?

· The Fed maintains a negative real interest rate;

· The Fed prints money to buy Treasury securities issued by the Treasury Department;

· The Treasury Department encourages banks to lend to Key Industries;

· If there are issues with the loans, the incumbent government will implicitly guarantee to backstop them.

If this isn't considered coordinated fiscal and monetary policy, I don't know what is. So, I am now extremely bullish on the market, as the true large-scale money printing is far from over.

U.S. Sovereign Wealth Fund

Now, let's boldly use our imagination once more. What if the U.S. government not only bails out banks after a crisis but proactively intervenes by buying shares of AI companies at the first signs of trouble? After all, thought experiments with wide-ranging implications are always interesting.

In fact, the Trump era has already begun the rescue of AI. Under the guise of "national security" and "U.S.-China competition," the U.S. government has started borrowing money to directly purchase equity stakes in so-called "Key Industries" companies, such as rare earth and semiconductor firms.

This is essentially a operation to increase the liquidity of the U.S. dollar or can be understood as Equity QE (Quantitative Easing). Because these dollars that were originally sitting in government accounts have been directly injected into the financial markets.

Below are some examples where the U.S. government, using funds borrowed from the CARES Act, CHIPS Act, and the Department of Defense budget, holds equity stakes in relevant companies.

Unfortunately, for those of us crypto investors who rely entirely on the printing press for our wealth expansion, the existing legal framework leaves little room for the government to continue such equity-like investments.

However, the Trump administration, along with Treasury Secretary Bessemer, has shown a clear stance that they will not hesitate to use borrowed money to buy the dip in AI stocks, as long as the law allows.

So, a new question arises: Is there a way to front-run the crisis, print money, and buy AI stocks in advance without needing Congressional approval?

The answer is yes! And this is where it gets interesting.

According to the Federal Reserve Act, under "Emergency and Exigent Circumstances," the Fed can print money directly and provide unlimited liquidity loans to a Special Purpose Vehicle (SPV) established by the U.S. Treasury.

During the 2008 financial crisis and the 2020 pandemic, the Treasury used the Exchange Stabilization Fund (ESF) to support first-loss equity, which was then financed by the Fed to the SPV to purchase various financial assets to stabilize the market.

Currently, there is still around $28 billion in the ESF account. Bessemer could easily use this funding as the initial capital for a new SPV, under the same guise of national AI security.

Traditionally, the Fed is willing to provide up to a 10x leverage to SPVs. This means Bessemer could theoretically leverage around $280 billion to inject into pre-profit AI companies. However, compared to today's AI giants with market caps in the trillions, $280 billion may not pack much of a punch.

Can the scale be expanded further? For example, could the Treasury set up an SPV with no first-loss capital buffer and have the Fed lend without limits? Technically possible, but this would put immense political pressure on the Fed as it would be seen as engaging in stealth unlimited equity quantitative easing (Equity QE).

So, does the Fed really care about political pressure?

The answer is both yes and no. New Chair Wash has always emphasized that AI will soon become the miracle that boosts U.S. productivity. In essence, he himself believes in the grand narrative painted by AI entrepreneurs.

If Trump were to tell him that, in order to save Sam Altman and OpenAI, the government must step in directly to buy stocks. The reason is that there are not enough retail investors willing to put up real money to buy shares of a non-profitable cutting-edge AI company; meanwhile, Dario Amodei's founded Anthropic is not only profitable but also has a stronger model performance.

So, Wash would most likely do so without hesitation. Of course, according to the procedure, approval of the SPV loan still requires votes from three other Federal Reserve Board members. But considering that at the most recent interest rate meeting, including Cook and Powell, are already aligned with Wash (supporting maintaining the interest rate), if Wash does push the Fed down this path, I can hardly see any substantial resistance.

After all, compared to theoretical concerns about printing money, the investment returns in personal stock accounts are always more convincing.

If the Treasury Department uses printed money to support upcoming IPOs of AI star companies, then it is actually cashing out unrealized profits on early investors' and employees' books. This is the purest form of "Liquidity Creation."

Because before the government steps in to support, this capital simply does not exist. It is precisely because the government is willing to provide buy orders for those unreasonably valued primary market valuations that this paper wealth can truly "realize."

From an accounting perspective, the government can obtain two benefits.

1. First, as long as an AI company has the government's backing, investors will flock. After all, following the person with the power to print money to trade stocks, at least in the initial stage, almost always makes money. As a result, this SPV's books will quickly accumulate massive unrealized gains. Trump can easily package these paper gains as government "profits," and even claim that they can theoretically offset the fiscal deficit. If AI is indeed the most important technological revolution in human history, then solely based on paper gains in the stock market, from an accounting perspective, it is even enough to "eliminate" the entire U.S. fiscal deficit.

2. Second, the newly minted millionaires, billionaires, and even trillionaires born from this will have to pay federal and state capital gains taxes when selling stocks. These additional tax revenues can also reduce the fiscal deficit, allowing the government to reduce borrowing and further proclaim that the U.S. debt-to-GDP ratio has decreased. At least initially, the bond market will believe this story, causing bond yields to fall, and the market will reward the government for this "accounting magic."

However, I must emphasize that Trump did not invent the Philosopher's Stone. He simply continued to kick the can down the road, hoping that the next administration—preferably a Republican one—would take over in the end.

Why is this kind of pattern bound to end in disaster? We can conduct a simple thought experiment. Suppose you want to become a billionaire overnight without doing any work. So, you spend a few thousand dollars to register a company and issue a total of 1 billion plus 1 shares of stock.

Then, you sell 1 share to your mother for $1. Since the latest transaction price is $1, from a book value perspective, the additional 1 billion shares in your hands are now valued at $1 billion. Next, you take this "wealth" to the bank, hoping to borrow $100 million to buy a mansion, a Lamborghini, and all sorts of luxury goods. The bank will flat out tell you, "No way."

You would be puzzled. Because in your view, the loan-to-value (LTV) ratio of this loan is only 10%, so the risk is evidently low. But the bank's response is simple:

"If in the future you need to sell those shares to repay the loan, there's simply no liquidity in the market."

Apply this same logic to the AI SPV, and it's no different. If the SPV has become the largest single shareholder of an AI company, and other investors bought shares just because the government is involved, then once the government is ready to exit, there will be no genuine takers in the market. Moreover, when those politicians—such as Ro Khanna, Nancy Pelosi, and others—start selling their shares, all investors will rush to sell before the government, causing the gains on paper that were originally meant to "offset national debt" to instantly vanish. Not only will they turn into real losses, but they will also further increase government debt.

What's worse, the Treasury will still have to repay the money it initially borrowed from the Fed. Therefore, for this SPV, this is actually an investment that can only be bought and not sold. The Fed can only keep rolling over the SPV's loan, ensuring that no additional margin calls will ever be triggered.

Ultimately, to sustain the entire system, the expansion of the Fed's balance sheet will become permanent.

However, this is not a concern for Trump. Because politically, he has already profited from both ends—on one hand, the yet-to-be-profitable U.S. AI companies have received funding to continue competing with China; on the other hand, the paper "wealth" created by AI has boosted tax revenue growth and stimulated current economic activity.

Meanwhile, unrealized gains plus additional tax revenue combine to create an illusion that the "US debt-to-GDP ratio is decreasing." As a result, the market is willing to continue lending to the US government at lower rates.

The US government could act now to prevent the AI bubble from bursting. Of course, it could also wait until AI CAPEX growth slows down and the market begins a comprehensive selloff of AI stocks before intervening to support the market.

Since the US government has already started directly purchasing corporate equities, why not buy more? By combining "bank-guided lending" with "government direct purchase of AI stocks," it could theoretically ensure that an AI credit crisis never occurs. At least not before the 2028 US presidential election.

Someone might ask, after printing so much money from 2022 to now, why hasn't Bitcoin broken through $126,000? Don't worry, the next section will provide you with the answer.

When Will Bitcoin Bottom Out?

The bottom of the previous cycle occurred when the market discovered that white boy Sam Bankman-Fried stole FTX customer funds, with CZ helping and facilitating this discovery.

Meanwhile, ChatGPT was commercialized, and the AI wave began.

Starting in October 2023, the US liquidity environment changed. Due to continuous outflows of funds from overnight reverse repurchase agreements (RRP), US dollar liquidity began to increase. Subsequently, bank credit and government borrowing also began to grow. Bitcoin surged as a result and peaked in October 2025; however, Bitcoin did not continue to rise, only increasing by about 2x compared to its previous all-time high, as AI credit and AI stocks absorbed the new fiat liquidity.

With the acceleration of AI capital expenditure (CAPEX), consuming all available fiat liquidity, the subsequent 50% drop in Bitcoin seemed obvious in hindsight.

In mid-2026, the liquidity environment reversed. The announced growth rates of AI capital expenditure for the next 18 months are set to slow down, but banks and government credit channels have just begun creating dollars and channeling them to the AI industry.

If banks fail to fulfill their "patriotic duty" to continue providing credit, the government will strongly urge them to lend to AI. If that effort still falters, the government will step in by providing equity support to specific AI companies and making procurement commitments similar to Intel and IBM to mitigate the risk of lending to the AI industry.

Bitcoin is poised to bottom out in the early stages of this credit misallocation cycle, as the financialization of AI—where the dollar and renminbi amount chasing quality AI projects in the market far exceeds the scale of truly high-quality projects themselves—will eventually lead to capital misallocation.

As of late July 2026 when I am writing this article, I do not know at what price Bitcoin will ultimately bottom; perhaps the bottom has already occurred.

The market needs time to digest the concerns brought about by Strategy's sale of Bitcoin. At the same time, the market also needs to find a new narrative: if Strategy cannot continue issuing stock or find investors to buy its preferred shares to continue buying Bitcoin, how can Bitcoin rise?

Bitcoin may oscillate between $60,000 and $70,000 for a while and may even dip to $50,000. However, throughout all of this, AI capital waste will continue to accelerate, laying the foundation for Bitcoin to bottom out and slowly rise thereafter.

If my view is correct—that the scale of truly valuable AI capital expenditure projects is smaller than the flow of credit into "AI"—then the price of Bitcoin will eventually reflect this excess liquidity. This will help Bitcoin find a bottom, even if digital asset treasury companies like Strategy can no longer buy Bitcoin in a Bitcoin-per-share accretive manner through the stock and corporate bond markets.

I will continue to monitor several indicators to validate this logic:

· Whether AI capital expenditure growth is slowing down;

· Whether AI loan volumes are increasing;

· Whether hyperscalers are increasing their off-balance sheet commitments.

If we are in the capital waste phase of this AI credit boom, the next question is: what will regulators and governments do? Will they preemptively print money, or will they wait for the ultimate crisis to unfold due to a lack of political space before intervening with rescue packages?

Fortunately, as long as we hold Bitcoin in a non-leveraged manner, we are not concerned about when the bailout will arrive. Because we know that due to the distortions in government incentive mechanisms, they will eventually always choose to print to save the system. The AI capital expenditure credit frenzy is currently equivalent in scale to the portion of GDP occupied during the railway construction era. This means that the scale of capital misallocation has exceeded that of the U.S. subprime crisis.

Therefore, the scale of future bailouts will exceed the tens of trillions of dollars printed by the Federal Reserve and major central banks globally between 2009 and 2013. Bitcoin was born in response to the "irresponsible banker bailouts" during the subprime crisis. When you think about it carefully, this is a truly amazing thing. And this time, Bitcoin already exists, and it may fulfill the dreams of many - rising to $1 million or even higher.

Considering the current bleak state of the crypto capital markets, it is not easy to imagine such a future. However, in my opinion, this has created an interesting asymmetric opportunity. Maelstrom has long held a large amount of Bitcoin.

Aside from Bitcoin, what will be the new narrative that could drive a large-cap token's surge in the next six months? Ethereum is currently the most hated and forgotten large-cap "shitcoin" in the market. It has not even surpassed its 2021 all-time high of $5,000, while most of the top ten shitcoins have.

In my view, the next narrative is Real World Asset (RWA) chains of companies like Robinhood, which will use an Ethereum Layer 2 similar to Arbitrum. Ethereum will become the settlement layer for these chains. Therefore, even though the actual Gas income flowing to Ethereum is a small part of the system, ETH is still that shitcoin driving the "tokenization of everything".

I am a critic of RWAs. Maelstrom often receives numerous junk project funding pitches, with teams claiming to be boarding the asset tokenization wave, while on the other hand, traditional finance (TradFi) loves to discuss: "All assets will be tokenized in the future and will operate on some private or public chain."

I strongly believe that if this future indeed arrives, then these TradFi RWA projects must operate on a public blockchain. And Robinhood launching its own chain using Arbitrum will reduce the professional risk of TradFi practitioners - they can replicate the same pattern, ultimately building Ethereum-based solutions.

This narrative is very strong. And ETH, as a shitcoin, is the second-largest cryptocurrency by market cap, has been around since 2015, and therefore, it has a Lindy effect second only to Bitcoin (meaning the longer it has been in existence, the higher the probability of continued existence in the future). Additionally, Tom Lee from Bitmine has endorsed allocating ETH for institutional investors, allowing fund managers to bet on the capital market tokenization trend.

My rough target price for ETH by the end of 2026 is $5,000, which represents approximately a 2.6x increase from the current price. I like this trade because I can enter a sizable nominal position while being able to withstand the risk of ETH plummeting 75% one day due to some technical vulnerability, a risk that is very low.

Furthermore, ETH is highly liquid. Therefore, even though it represents a significant portion of the Maelstrom portfolio, I can still exit within minutes. Finally, I will also sell out-of-the-money puts to earn additional income, all while accepting the risk of buying ETH at a discount if it falls below the strike price.

The AI bubble once sucked liquidity out of the crypto market, but that situation has now ended. As the market narrative shifts from “invest in AI at any cost” to “what is my ROI” and eventually to “when do I get my money back,” governments that have staked their entire economic policy on AI will begin to worry — perhaps the bubble might actually burst.

To avoid admitting their mistake and prevent this outcome, they will engage in massive capital misallocation, a scale of misallocation that will ultimately create a cryptocurrency bull run unlike any we have seen since 2021.

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