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Dear Reader,
If you suspect AI is going to crash, I just want you to know, you’re right.
My name is Alexander Green.
I started my career on Wall Street four decades ago. I retired in my 40s. And today, I’m the chief investment strategist of one of the longest running private investment research groups in the U.S.
And I’m sending you a recording of a private presentation I recently gave, to tell you the truth about AI that no one else will tell you…
It’s partly to do with what will happen after the AI crash… and what the #1 investment of the next decade will be.
Prepare now, and thank me later.
Nobody else sees this coming.
Click here and I’ll reveal what’s going on in full…
Good investing,
Alexander Green
Chief Investment Strategist, The Oxford Club
P.S. This could make or break your financial future… But you’ll grow old and grey waiting to hear about it on CNBC. Details here.
Meta Platforms Turns AI Power Scarcity Into a $10 Billion Cloud Bet
By Jeffrey Neal Johnson. Date Posted: 7/20/2026.
Key Points
- Meta Platforms is negotiating to lease up to $10 billion in data center computing capacity to Anthropic over two years, positioning itself as a cloud infrastructure provider.
- Meta's Meta Compute initiative aims to build roughly 14 gigawatts of AI capacity by 2027, capitalizing on a projected 100-gigawatt U.S. power supply gap by 2030.
- Meta maintains strong fundamentals, including a 32.84% net margin and 36.93% return on equity, while planning $125 billion to $145 billion in 2026 capital spending.
- Special Report: Everyone wanted SpaceX. Smart money wants this.
A severe macroeconomic grid power shortage has quietly transformed physical artificial intelligence (AI) compute capacity into the technology sector's most valuable commodity. By leveraging its vast infrastructure to lease processing power to Anthropic, Meta Platforms (NASDAQ: META) is aggressively pivoting from hardware consumer to commercial cloud landlord, challenging established hyperscalers directly at the compute bottleneck.
Shorting the Plug: The 100-Gigawatt Grid Shock
The conversation around artificial intelligence has historically centered on silicon. Investors constantly ask how many chips a business can buy and how quickly it can deploy them. That narrative is rapidly evolving. Banking analysts project a U.S. electricity supply gap exceeding 100 gigawatts by 2030. Upgrading the domestic power grid requires high-voltage transformers and transmission lines that are currently facing multi-year manufacturing backlogs.
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Alexander Green bought Apple in 1996, recommended Nvidia at a split-adjusted 66 cents in 2004, and picked up Amazon and Netflix under $3 per share in 2005.
Now the chief investment strategist at The Oxford Club has identified three AI stocks he believes could be the most profitable investments of the next decade.
Click here to get all three AI stock names from Alexander GreenThe primary bottleneck is no longer just securing graphics processing units, but finding an energized facility to plug them into. Companies with existing physical footprints, secured data centers, and locked-in power purchase agreements hold a structural advantage that competitors cannot replicate simply by raising capital.
Building Business: The 14-Gigawatt Infrastructure
Meta Platforms is navigating an immense capital expenditure cycle. Management projects spending between $125 billion and $145 billion in 2026 alone, predominantly directed toward AI hardware and data center expansion.
To the untrained eye, that level of cash burn looks like an operational liability. When a technology enterprise spends that aggressively, market participants typically worry about margin compression, fearing that the upfront costs will erode bottom-line profitability before the investments generate a measurable return.
However, viewing this purely as an expense misses the strategic land grab taking place. Meta Platforms is essentially acquiring highly sought-after real estate in a supply-shocked compute market.
The internal initiative, Meta Compute, aims to build approximately 14 gigawatts of AI compute capacity by 2027. Meta Platforms is bypassing the utility grid bottlenecks that currently paralyze smaller developers. The underlying enterprise value is shifting from purely digital advertising yields to the direct ownership of secured, energized infrastructure.
Signing the Lease: Anthropic Rents Meta's Power
The clearest validation of this infrastructure thesis surfaced with preliminary negotiations to lease data center computing capacity to AI developer Anthropic. The proposed transaction is valued at up to $10 billion over two years and structured as monthly installments. The deal reportedly includes mutual early-termination clauses, acting as a pragmatic safety valve should Meta Platforms require the physical capacity for its own internal development.
Why would a tier-one AI developer bypass traditional hyperscalers like Amazon's (NASDAQ: AMZN) Web Services or Microsoft's (NASDAQ: MSFT) Azure? The decision comes down to necessity and compute scarcity. Anthropic has faced substantial processing bottlenecks, previously enforcing usage limits on advanced models like Claude Fable because it lacked the raw capacity to run them at scale. Securing processing power from a social media giant mirrors Anthropic's recent multi-billion-dollar infrastructure lease with SpaceX. Top-tier AI developers are scouring the market for any energized compute they can find, regardless of the provider's primary industry.
Meta Platforms is not treating this as a temporary favor. The strategic hiring of former AWS Senior Vice President Dave Brown to lead Meta Compute signals a formalized push for enterprise cloud market share. At the May 2026 shareholder meeting, management explicitly validated these commercial cloud ambitions, confirming that it receives weekly inbound inquiries for spare compute capacity. Meta Platforms is taking dormant GPU stockpiles intended for internal open-source model development and generating immediate commercial yield.
Collecting the Rent: High-Margin Infrastructure Yield
Turning idle hardware into a $10 billion revenue stream creates a highly efficient strategic dynamic. Meta Platforms captures recurring, high-margin revenue from an industry peer while pricing its scarce physical processing power at a premium. This recurring revenue helps subsidize the immense capital expenditure required to build out the 14-gigawatt footprint, directly mitigating the margin compression investors initially feared.
Fundamentally, the underlying business remains remarkably robust. Meta's stock price recently closed at $646.
Meta has a market capitalization of $1.63 trillion and trades at a trailing price-to-earnings ratio of 23.48, compared with a forward multiple of 21.93. When the forward multiple is lower than the trailing multiple, it indicates analysts expect earnings to grow faster than the current share price implies, suggesting a relatively grounded valuation given the broader technology sector's premium pricing.
Profitability metrics underscore a highly efficient operation. Meta Platforms commands a net margin of 32.84% and an exceptional return on equity of 36.93%. A high return on equity indicates that management is efficiently generating profits from shareholders' capital. Building physical data centers is historically a low-margin endeavor, but operating with a 36% ROE implies Meta Platforms knows how to extract maximum value from every dollar deployed. The balance sheet remains flush with liquidity, carrying a current ratio of 2.35 and a conservative debt-to-equity ratio of 0.24.
During the first quarter, Meta Platforms delivered a $3.77 earnings-per-share beat alongside 33.1% year-over-year revenue growth. Despite the aggressive capital expenditure cycle, management continues to prioritize shareholder yield. The recent implementation of a 52.5-cent-per-share quarterly dividend provides a crucial baseline of support for long-term investors waiting for the hyperscaler pivot to mature.
The Sublet Trap: When Meta Needs Its Own Power
Every major business model pivot carries execution risk. The core premise is that Meta Platforms possesses dormant compute stockpiles. Sustained use by external entities like Anthropic could eventually lead to compute rationing for internal open-source Llama model development. If Meta Platforms leases too much power, the organization risks stalling its own AI advancements.
Transitioning to a commercial hyperscaler forces the company into direct, capital-intensive competition with established cloud providers. This shift introduces enterprise-level sales and business-to-business support requirements to an organization that has historically been optimized for consumer data and digital advertising.
Investors tracking insider behavior will notice a net selling trend, reflecting capital distribution among executives. A confirmed transaction occurred on July 7, involving a corporate director liquidating $303,875.00 in equity. While insider selling often reflects routine portfolio diversification or tax obligations, it remains a metric worth monitoring during a structural transition.
Holding the Deed: Why Infrastructure Beats Silicon
The shift from hardware consumer to provider of physical infrastructure represents a fundamental evolution in how the market should value Meta Platforms. The secured data centers, power agreements, and localized grid connections are forming a physical moat that competitors will struggle to breach before the end of the decade.
Investors seeking exposure to the structural power shortages in the AI supply chain might want to evaluate companies that already hold energized assets rather than focusing solely on chip designers. Evaluating the upcoming July 29 earnings call for updates on the Anthropic lease and the broader Meta Compute initiative could provide valuable clarity on the pace of this cloud transition. Cautious market participants may prefer to watch how effectively the new enterprise sales division scales operations before allocating fresh capital to the space.
Catching the AI Wave: DigitalOcean Reels in AI Whales
Author: Jeffrey Neal Johnson. Published: 7/9/2026.
Key Points
- DigitalOcean shares rose more than 10% after preliminary second-quarter results showed revenue of $282.1 million, beating estimates and driven by nine-figure enterprise AI contracts.
- Remaining performance obligations exceeded $800 million after a $550 million quarterly jump, signaling a pivot from small-business hosting toward enterprise AI infrastructure.
- The rally is fueled partly by short covering and index-driven buying, while insiders sold roughly $565.9 million in stock and shares trade near 57 times earnings.
- Special Report: Everyone wanted SpaceX. Smart money wants this.
The architectural landscape of cloud infrastructure is fracturing. For years, the market assumed legacy hyperscalers like Amazon (NASDAQ: AMZN) and Microsoft (NASDAQ: MSFT) would control the enterprise server space indefinitely, leaving smaller infrastructure providers to compete mainly for budget-conscious developers.
That paradigm shifted on June 7, 2026, as DigitalOcean Holdings (NYSE: DOCN) defied a broadly declining macroeconomic backdrop and rose by more than 10% following a highly bullish preliminary second-quarter earnings release. The price action signals something much deeper than an earnings beat. The market is witnessing a pivot as smaller independent cloud providers capture high-margin, enterprise-scale workloads.
3 AI stocks to buy before August 2026 (Ad)
Alexander Green bought Apple in 1996, recommended Nvidia at a split-adjusted 66 cents in 2004, and picked up Amazon and Netflix under $3 per share in 2005.
Now the chief investment strategist at The Oxford Club has identified three AI stocks he believes could be the most profitable investments of the next decade.
Click here to get all three AI stock names from Alexander GreenInvestors chasing this momentum should unpack the underlying data to separate the growth story from temporary distortions such as short covering and passive index accumulation. When you look closely, it becomes clear how DigitalOcean is changing the tide in the enterprise artificial intelligence sector.
Reeling in Revenue: Accelerating Top-Line Metrics
Analyzing the second-quarter pre-announcement reveals the distinct drivers behind the sudden upside volatility. Management now forecasts second-quarter revenue of $282.1 million, a 29% year-over-year acceleration. This decisively eclipses Wall Street’s consensus estimate of $273.6 million and marks a steep reacceleration from the 14% growth recorded in the second quarter of last year.
While the top-line beat is impressive, the forward-looking metrics are resetting valuation models across the sector. DigitalOcean reported remaining performance obligations exceeding $800 million. Remaining performance obligations act as a reliable leading indicator of future revenue, representing contracted but unrecognized sales.
Adding $550 million to this pipeline in a single quarter is a major achievement, reflecting a more than tenfold increase from the prior year. The weighted-average contract life has also extended from 1.6 years to over three years. By locking in long-term capital, DigitalOcean is preserving adjusted EBITDA margins despite continued infrastructure spending.
Deep Water Infrastructure: The Enterprise AI Pivot
The historic surge in contracted revenue requires a fresh re-evaluation of DigitalOcean's target demographic. Historically, the broader market categorized the business as a volume-driven host for small businesses or independent software developers. A low average revenue per user model traditionally struggles during periods of macroeconomic tightening, as smaller clients churn or downsize their hosting plans to survive.
Management explicitly attributes the recent $550 million pipeline jump to multiple nine-figure annual customer commitments strictly tied to inference and AI workloads. Nine-figure contracts are fundamentally incompatible with small business budgets. These agreements are the domain of highly funded enterprise AI labs and institutional research divisions. DigitalOcean is effectively pivoting from a budget-friendly hosting service to a heavyweight player in AI infrastructure.
To support these enterprise contracts, DigitalOcean deployed capital from a recent $800 million equity offering to secure an additional 20 megawatts of data center capacity for late 2027 and early 2028. This brings total committed capacity to 155 megawatts. By focusing on purpose-built architectures, such as its proprietary inference routing software, DigitalOcean is competing on total cost of ownership against major hyperscalers rather than entering a margin-crushing race to the bottom on pricing.
Currents of Capital: Institutional Buy-In Vs. Insider Exits
Understanding the mechanics of the current price action requires looking under the hood at market sentiment and institutional capital flows. Options flow reflects a strong upside bias, with the volume put-to-call ratio dropping to 0.18 and total contract volume rising above 136% of the average daily volume.
This bullish derivatives activity is colliding directly with forced buying in the underlying equity. Short interest currently sits at approximately 12% of the public float, translating to roughly 12.2 million shares shorted. With a days-to-cover ratio nearing four, the double-digit intraday climb is undoubtedly exacerbated by short sellers scrambling to close underwater positions. Institutional ownership commands about 50% of outstanding shares, down from around 90%, creating a structural floor that successfully absorbed the dilution from the recent equity offering.
Despite the institutional accumulation, retail investors should consider internal structural headwinds. Over the trailing three months, insiders liquidated approximately $565.9 million in stock. The bulk of this distribution came from major shareholder Access Industries, along with multi-million-dollar sales from key executives. With zero open-market insider purchases during this period, internal leadership is clearly using the elevated valuation to take profits.
Sailing Close to the Wind: At 57x Earnings?
The fundamental momentum supporting DigitalOcean is undeniable, and the expanding contracted revenue provides visibility through 2026. However, market mechanics and valuation multiples should still matter for investors entering at these levels.
DigitalOcean commands a premium trailing price-to-earnings ratio of about 57x. A valuation this rich leaves very little room for operational missteps, particularly in a high-interest-rate environment where the broader technology sector remains highly sensitive to changes in the cost of capital.
The recent addition of DigitalOcean to the Russell 1000 index has led to continued passive index accumulation, creating an artificial tailwind for the share price. Investors should acknowledge that DigitalOcean is currently priced for perfection, and the heavy insider distribution suggests that early institutional backers have already captured much of the easy money.
Dropping Anchor: Rigging the Deck for an AI Pivot
The cloud computing narrative is undergoing a fundamental shift, revealing that nimble, cost-effective infrastructure providers can thrive alongside the trillion-dollar tech giants. DigitalOcean is proving that independent operators can successfully capture enterprise market share without sacrificing profitability. The pivot toward artificial intelligence infrastructure is resetting the forward growth trajectory and shielding DigitalOcean from the high-churn risks typically associated with small business clients.
The underlying data support the bullish price action, driven by tangible contract expansions rather than speculative hype. Investors evaluating the infrastructure space might consider adding DigitalOcean to their watchlist as a high-growth alternative to mega-cap technology stocks, provided they have the risk tolerance for premium valuation multiples and post-squeeze volatility.
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