Contessaria's strategy prioritizes businesses with predictable 10-year outlooks and low capital intensity. He avoids tech giants like Meta and Alphabet, which require massive, ongoing reinvestment in R&D and infrastructure, making their long-term free cash flow less durable and predictable than Visa's.

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The tech business model has fundamentally changed. It has moved from the early Google model—a high-margin, low-CapEx "infinite money glitch"—to the current AI paradigm, which requires a capital-intensive, debt-financed infrastructure buildout resembling heavy industries like oil and gas.

While high capex is often seen as a negative, for giants like Alphabet and Microsoft, it functions as a powerful moat in the AI race. The sheer scale of spending—tens of billions annually—is something most companies cannot afford, effectively limiting the field of viable competitors.

Rick Reeder explains that the immense free cash flow of large companies is a self-fulfilling prophecy. It allows them to fund R&D and CapEx at a scale that smaller competitors cannot match, continuously widening their competitive advantage and ensuring their market dominance.

Tech giants are shifting from asset-light models to massive capital expenditures, resembling utility companies. This is a red flag, as historical data shows that heavy investment in physical assets—unlike intangible assets—tends to predict future stock underperformance.

Major tech and fintech players, including Apple, Google, and Stripe, have opted to integrate with Visa's network rather than build a competing one from scratch. This dynamic turns potential disruptors into partners, reinforcing Visa's deep moat and demonstrating the prohibitively high cost of replicating its global infrastructure.

While many investors hunt for pure monopolies, most tech markets naturally support a handful of large players in an oligopoly structure. Markets like payments (Stripe, Adyen, PayPal) demonstrate that multiple large, successful companies can coexist, a crucial distinction for market analysis and investment strategy.

Valuing companies like Meta based on past P/E multiples is flawed because their business model is changing. The shift from a capital-light, high-margin software firm to a leveraged, hardware-heavy business means it should command a much lower valuation multiple.

The AI buildout is forcing mega-cap tech companies to abandon their high-margin, asset-light models for a CapEx-heavy approach. This transition is increasingly funded by debt, not cash flow, which fundamentally alters their risk profile and valuation logic, as seen in Meta's stock drop after raising CapEx guidance.

The huge CapEx required for GPUs is fundamentally changing the business model of tech hyperscalers like Google and Meta. For the first time, they are becoming capital-intensive businesses, with spending that can outstrip operating cash flow. This shifts their financial profile from high-margin software to one more closely resembling industrial manufacturing.

Companies like Meta are ceasing buybacks to fund existential AI CapEx, transforming them from high-margin, capital-light software businesses into leveraged, capital-intensive infrastructure players. This fundamental shift invalidates past valuation models based on free cash flow.