Massive AI Crackdown Is Coming (It’s Simply Too Good) | David Woo
David Woo argues that AI has become too powerful and will face significant regulatory crackdowns, presenting the primary downside risk to AI stocks. He contends that real capex growth is slowing despite nominal earnings appearing strong, driven by input cost inflation rather than increased output, while accessible AI capabilities are plateauing despite claims of breakthroughs.
Summary
David Woo, an independent economist, presents a bearish case on AI stocks based on three primary arguments: regulatory risk, commoditization of AI models, and accounting illusions masking weak underlying fundamentals. On the capex question, Woo reveals that the combined spending of the five major hyperscalers (Microsoft, Google, Amazon, Oracle, Facebook) declined quarter-over-quarter in Q1, marking the first drop in three years. Despite this, earnings growth appears strong at 25%, which Woo attributes to rising input costs rather than increased output. He illustrates this with an example: if Microsoft pays $100 more per chip to Micron but only expenses 10% of that increase through depreciation, the company books $90 in earnings growth from what is essentially just an income transfer from hyperscaler to chip maker.
Woo emphasizes that the slowdown in real capex is masked by inflation and token maxing—artificial consumption of AI tokens by companies like Amazon to drive usage metrics. He predicts Q2 earnings will show deceleration as this token maxing phenomenon subsides, citing Uber's COO statement that the company exhausted its annual token budget in just four months with little to show for it. The capex-to-operating-income ratio for the five hyperscalers now sits at 135%, forcing companies like Google to raise $80-85 billion in equity and companies like Facebook to rely on debt issuance to finance capex—a shift from their historical position as cash-rich firms.
On the regulatory front, Woo's core thesis is that AI has become too good for its own good. Claude 3.5 Sonnet (released April 7) is so capable at multi-stage autonomous tasks that it essentially functions as a perfect cyber hacking tool. Woo notes that despite the model's release and the NASDAQ's subsequent $5 trillion addition in market cap, anthropic has distributed Claude 3.5 Sonnet to only 150 users after two months, indicating de facto government control. He argues this regulatory constraint is inevitable because distributing such capabilities beyond a select group creates unacceptable national security risks. Germany alone reported €300 billion in cyber attack costs last year, and models like Claude Sonnet with recursive learning capabilities make government-imposed restrictions politically necessary.
Woo also addresses the commoditization thesis, arguing that while Nvidia maintains monopolistic pricing power in learning chips (Blackwell and Reuben), competition is intensifying in inference chips, where Intel, AMD, and Broadcom compete. Memory chip makers (Micron, Samsung, SK Hynix) face particular vulnerability to commoditization despite current pricing power. Woo notes these companies have historically experienced extreme boom-bust cycles and that Chinese competitors are rapidly moving into DRAM and NAND flash, where they will likely achieve parity within two to three years, even if they cannot compete with Nvidia on cutting-edge learning chips.
Regarding AI's impact on employment, Woo distinguishes between capabilities: he believes AI can replace the bottom 90% of workers engaged in repetitive, copy-paste work, but struggles with the top 10% who require creative, original thinking. He predicts 50% of software engineers will be displaced within three to four years, but sees potential positive applications in democratizing tool-building and empowering small teams. Paradoxically, while AI threatens jobs, it may also address emerging labor shortages in the US, where birth rates are collapsing and net immigration has stopped.
Woo concludes by addressing the Iran-Israel conflict and oil markets, arguing that Trump's repeated claims of an imminent deal signal desperation to the Iranians, hardening their negotiating position. He maintains a bullish oil stance based on the probability that most scenarios lead to higher oil prices, regardless of the specific endgame.
About this episode
Sponsor: Teucrium Corn Fund (NYSE Arca: CORN): https://teucrium.com/corn In this episode of Monetary Matters, host Jack Farley sits down with independent economist and strategist David Woo to break down the hidden realities behind global tech markets and macroeconomics. Woo reveals how component inflation and artificial "token maxing" have created an optical illusion of accelerating corporate earnings, obscuring a real-term slowdown in tech hyperscaler CapEx. Rather than arguing that artificial intelligence lacks power, Woo presents a stark AI bear case rooted in imminent global regulatory crackdowns as advanced frontier models like Claude Mythos introduce severe cybersecurity and national security risks. He predicts that the broader AI industry is rapidly heading toward intense competition and commoditization, which will ultimately turn current hardware shortages into a massive compute glut. Turning to geopolitics, Woo details why he remains heavily bullish on oil as active military conflicts between Iran and Israel continue to jeopardize the blockaded Strait of Hormuz. Applying game theory to President Trump's ongoing ceasefire negotiations, he asserts that Iran is exploiting Washington's public push for a deal to extract tougher terms that will inevitably drive energy prices even higher. Recorded June 10, 2026. ____ Jack Farley on X https://x.com/JackFarley96 David Woo on X https://x.com/Davidwoounbound?lang=en David Woo website https://www.davidwoounbound.com/ David Woo's book, "Merry-Go-Round Broke Down: A Novel of Guilt, Greed & Globalization," https://www.amazon.com/Merry-Go-Round-Broke-Down-Novel-Globalization/dp/B0GCX8Y6KT Follow Monetary Matters on: Apple Podcasts https://rb.gy/s5qfyh Spotify https://rb.gy/x56dx5 YouTube https://rb.gy/dpwxez __ This episode is sponsored by the Teucrium Corn Fund (CORN). Download our free eBook, "Why Investors Are Increasingly Turning to Commodity ETFs," to explore the macro forces shaping commodity markets today. Download the eBook: insights.teucrium.com/why-investors-turning-to-commodity-etfs CORN Fund Page & Prospectus: www.teucrium.com/corn This material must be preceded or accompanied by a prospectus. The prospectus is available at https://teucrium.com/corn. Investing involves risk, including the possible loss of principal. Commodities and futures generally are volatile, and instruments whose underlying investments include commodities and futures are not suitable for all investors. Past performance does not guarantee future results. For further discussion of these and additional risks associated with an investment in the Funds please read the respective Fund Prospectus before investing. CORN, CANE, SOYB, and WEAT are commodity pools regulated by the Commodity Futures Trading Commission (CFTC). The Funds do not track the spot price of corn, sugar, soybeans or wheat. These Funds, which are ETPs, are not a mutual fund or any other type of Investment Company within the meaning of the Investment Company Act of 1940, as amended, and are not subject to regulation thereunder. Teucrium Trading, LLC is the Sponsor for CORN, CANE, SOYB, and WEAT. PINE Distributors LLC is the Marketing Agent for CORN, CANE, SOYB, and WEAT and is not affiliated with Teucrium Investment Advisors, LLC and Teucrium Trading, LLC. Timestamps 00:00 Intro 00:26 Teucrium $CORN Pre-roll 01:30 Data Center CapEx 08:02 AI Profits Inflated by Supply-Chain Inflation 16:05 Regulation Risk for AI 20:38 Teucrium $CORN Mid-roll 22:20 "Harbinger to Come": Regulation from Trump Administration 28:20 "Crackdown on AI": What Would That Look Like? 33:47 "AI Is Very Productive" For Many Tasks 46:27 "Is It A Bubble"? 53:42 Bearish View on Nasdaq 56:00 Oil and Iran 1:07:30 Teucrium $CORN End-roll
Key Insights
- Combined capex of five hyperscalers declined quarter-over-quarter in Q1 for the first time in three years, yet nominal earnings grew 25% due to rising input costs being expensed at depreciation rates rather than full cost recognition
- Woo argues that 'token maxing' by companies like Amazon, where employees artificially inflated AI consumption to meet performance metrics, created a temporary revenue surge for AI companies that will reverse in Q2
- The capex-to-operating-income ratio for the five hyperscalers reached 135%, forcing companies historically known for cash generation to raise new equity and debt, signaling a shift in financial sustainability
- Claude 3.5 Sonnet has been distributed to only 150 users after two months since its April 7 release, representing de facto government control through capability constraint rather than explicit regulation
- Claude 3.5 Sonnet's recursive learning capability—where version one can create version two without human intervention—makes government regulation of model distribution politically inevitable and technically necessary
- Memory chip makers face severe commoditization risk within two to three years as Chinese competitors achieve parity in DRAM and NAND flash, despite near-monopolistic pricing power today
- AI can replace the bottom 90% of workers performing repetitive, copy-paste functions but struggles with the top 10% who require creative, original thinking and novel problem-solving
- Woo predicts approximately 50% of software engineers will be displaced within three to four years due to AI's superior code generation and completion capabilities relative to other professions
- Large language model competition follows a predictable pattern where one model achieves a breakthrough, achieves rapid revenue acceleration, then loses ground within three to four months as competitors catch up to the same public training data
- Anthropic's claimed increase in annual recurring revenue from $9 billion in December to $42-44 billion is substantially inflated by token maxing and the temporary success of Claude Code before competitive offerings emerged
- Regulatory risk, not technical limitations or business model constraints, represents the primary downside risk to AI stocks and the AI trade over the next 6-12 months
- Trump's repeated public claims that a deal with Iran is imminent signal desperation to the Iranian negotiating team, likely hardening their resolve rather than encouraging compromise
Topics
Transcript
[0:00] My big issue with the whole entire AI thing is that AI has gotten too good for his own good. I may be the first one talking about the downside risk to AI now is regulatory risk, but there is no doubt in my mind that more and more people are going to talk like me and think like me in the coming months because it's inevitable. >> So the bare case for AI is not that it's not powerful, but that it's too powerful and is going to be reigned in by governments worldwide, including the US government. >> Absolutely. Today's episode is brought to you by the Tukrium Corn Fund, ticker CO RN. Let's get into it.…
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