Invest1 publisherNot yet confirmed elsewhere3 min readPublished
Fed minutes list AI debt issuance among the forces pushing long Treasury yields higher
Federal Reserve minutes from September record market contacts blaming heavy AI infrastructure borrowing for part of a 35-basis-point rise in Treasury yields. Crypto buyers counting on a Fed pause may find the relief stops short of a 10-year Treasury paying 5.28%.
The Investor · Invest desk

What happened
- In September the Fed lifted its target range 25 basis points, to 3.75%-4%, and most officials thought one more hike before year-end would probably be appropriate.
- According to the Fed, most of the rise in longer-dated Treasury yields between meetings came from moves in real rates.
- The Fed's trading-desk manager said spreads on major cloud providers' debt stayed wide because of how much they are borrowing and at what long maturities.
- By the Bank for International Settlements' estimate, AI-related capital spending by the five biggest technology companies will top $1 trillion over 2025 and 2026 combined.
Compiled by The InvestorSomething wrong?How this is made
Why it matters
- constraint A pause removes only the tightening-expectations part of the yield rise; AI builders borrowing at long maturities keep bidding for the same 10-year money whatever the overnight rate does.
- cost Bitcoin holders forgo a positive after-inflation Treasury return, so any floor under real yields from AI borrowing raises the return bitcoin must deliver to justify its drawdowns.
- exposure Companies funding the buildout with bonds and private credit carry the risk the BIS describes, forced asset sales if AI revenue falls short of expectations.
The minutes did not say how much of the move came from AI financing. They cited stronger economic data, expectations of further Fed tightening, geopolitical developments and uncertainty around Treasury buybacks alongside it [2]. For anyone waiting on a pause, the tightening expectations are the item on that list that matters most, because a pause removes them directly and leaves the others in place.
On Oct. 7 the 10-year par yield was 5.28% and the inflation-adjusted 10-year yield was 2.92%, according to Treasury data cited by CryptoSlate [9]. The gap between them, 2.36 percentage points, is the inflation compensation in the price [14]. The 2.92% is what a buyer earns after inflation for lending to the government, and bitcoin pays nothing to set against it. The 10-year also sits 1.28 points above the 4% top of the fed funds range [15]. For a holder with a horizon of years, the long yield is the opportunity cost, and it is set partly by who else wants to borrow for ten years.
Some of those borrowers no longer fund the buildout from cash. CryptoSlate reports that spending outpaces earnings and free cash flow at some companies, raising their reliance on bonds and private credit [13]. The BIS said debt is a growing part of the financing for data centers, chips and energy [7]. Industry projections cited by the BIS take global AI investment from roughly $500 billion today to between $3 trillion and $4 trillion by 2030 [6], six to eight times the current level [16]. That baseline is hard to square with the BIS estimate for the five largest tech companies, whose spending of more than $1 trillion over two years averages above $500 billion a year for those five alone [17], so the two series must use different definitions.
Equity holders have absorbed the cost so far. The Fed said companies that benefit directly from the buildout outperformed the broader market, with stronger actual and expected earnings supporting prices even as valuation multiples declined [11].
If expectations of more tightening were most of the 35 basis points [3], a pause brings the 10-year down and crypto gets the cheaper money it is waiting for. If issuance was the larger force, a pause lowers short-rate expectations and leaves the long end close to where it is. The BIS describes a third path, in which competition for market share pushes companies to commit more capital than eventual returns justify, and heavier debt raises the risk of financial stress and forced asset sales if revenue disappoints [12]. CryptoSlate argues that outcome would eventually become a new liquidity tailwind for crypto [19]. It would arrive through a credit problem first.
I think the second path is the likeliest. The Fed's finding on real rates [10] fits a story about the supply of long-dated debt better than one about inflation, and the desk manager's comment on cloud-provider spreads points the same way [8]. The view is wrong if 10-year yields fall as far as two-year yields once the Fed signals it is finished, or if cloud-provider spreads tighten while the borrowing keeps coming.
What to watch
- Whether the next Fed minutes move the AI-financing explanation from market contacts into the committee's own assessment of long-term yields.
- The year-end meeting: whether the hike most officials expected happens and takes the target range to 4%-4.25%.
- New long-dated bond deals from the major cloud providers and whether their spreads stay as wide as the desk manager described.
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- [1]
Minutes from the Federal Reserve's Sept. 15-16 meeting showed market participants citing heavy private debt issuance for AI infrastructure as one factor pushing Treasury yields and term premiums higher; market contacts pointed to competition for capital from AI-related private issuance as one contributor to higher term premiums.
ReportedSupportedSource: Fed minutes, as reported by CryptoSlate2 sources— create a free account to open themView cited source - [2]
The minutes did not quantify how much of the roughly 35-basis-point rise in yields came from AI financing; stronger economic data, expectations for additional Fed tightening, geopolitical developments and uncertainty around Treasury buybacks were also cited.
ReportedSupportedSource: CryptoSlate, citing Fed minutes2 sources— create a free account to open themView cited source - [3]
Nominal Treasury yields rose about 35 basis points across maturities from two to 10 years between Fed meetings.
- [4]
The Fed raised the federal funds target by 25 basis points to 3.75%-4% in September, and most officials judged another increase would probably be appropriate before year-end.
- [5]
The Bank for International Settlements estimates the five largest technology companies will spend more than $1 trillion on AI-related capital expenditure across 2025 and 2026.
- [6]
Industry projections cited by the BIS put global AI investment at roughly $500 billion today, potentially rising to between $3 trillion and $4 trillion by 2030.
- [7]
The BIS said debt is becoming a larger part of the financing mix as firms build data centers, buy chips and secure energy infrastructure.
- [8]
The Fed's trading-desk manager said spreads on debt issued by major cloud providers remained wide because of the amount being borrowed and the long maturities involved.
- [9]
Treasury data showed the 10-year Treasury par yield at 5.28% on Oct. 7, while the inflation-adjusted 10-year yield was 2.92%.
- [10]
The Fed said changes in real rates accounted for most of the increase in longer-dated Treasury yields during the intermeeting period.
- [11]
The Fed said companies benefiting directly from AI infrastructure spending outperformed the broader market, with stronger actual and expected earnings supporting equity prices even as valuation multiples declined.
- [12]
The BIS has warned the AI buildout ranks among the largest technology investment booms in US history; its research argues competition for future market share could push companies to commit more capital than eventual returns justify, while greater debt use increases the risk of financial stress and forced asset sales if revenue expectations disappoint.
- [13]
AI spending is outpacing earnings and free cash flow at some companies, increasing reliance on bonds and private credit.
- [14]
The gap between the 10-year nominal par yield and the inflation-adjusted 10-year yield on Oct. 7 was 2.36 percentage points.
- [15]
The 10-year par yield of 5.28% sits 1.28 percentage points above the 4% upper bound of the fed funds target range.
- [16]
The 2030 projection of $3 trillion to $4 trillion is six to eight times the roughly $500 billion of global AI investment today.
- [17]
More than $1 trillion of AI capex across 2025 and 2026 by the five largest tech companies averages more than $500 billion a year.
- [18]
Another 25-basis-point increase would take the fed funds target range to 4%-4.25%.
- [19]
If the AI boom later cracks, the same cycle could reverse into financial stress and a new liquidity tailwind for crypto.
ReportedInsufficientSource: CryptoSlate analysis2 sources— create a free account to open themView cited source
Sources
1 independent publisher whose own reporting we read for this story.
- cryptoslate.comAI may be keeping Bitcoin’s biggest macro headwind alive after the Fed stops hiking
1 article · October 8, 2026
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