While immense value is being *created* for end-users via applications like ChatGPT, that value is primarily *accruing* to companies with deep moats in the infrastructure layer—namely hardware providers like NVIDIA and hyperscalers. The long-term defensibility of model-makers remains an open question.

During the dot-com crash, application-layer companies like Pets.com went to zero, while infrastructure providers like Intel and Cisco survived. The lesson for AI investors is to focus on the underlying "picks and shovels"—compute, chips, and data centers—rather than consumer-facing apps that may become obsolete.

Historical tech cycles like the cloud and mobile demonstrate a consistent pattern: the application layer ultimately generates 5 to 10 times the value of the underlying infrastructure capital expenditure. With trillions being invested in AI infrastructure, future value creation at the application layer will be astronomically larger.

In a new, high-risk category, betting on infrastructure ('shovels') isn't necessarily safer. If the category fails, both app and infra lose. But if it succeeds, the application layer captures disproportionately more value, making the infrastructure a lower-upside bet for the same level of existential risk.

Despite massive investment in chips (NVIDIA) and models (OpenAI), it is not yet clear where long-term value will concentrate. The entire stack is in flux. Models could be commoditized by open source, chips could face historical commoditization cycles, and new AI-native apps could capture the most value. We are only in the early innings of a 30-year shift.

Value in the AI stack will concentrate at the infrastructure layer (e.g., chips) and the horizontal application layer. The "middle layer" of vertical SaaS companies, whose value is primarily encoded business logic, is at risk of being commoditized by powerful, general AI agents.

The current AI landscape mirrors the historic Windows-Intel duopoly. OpenAI is the new Microsoft, controlling the user-facing software layer, while NVIDIA acts as the new Intel, dominating essential chip infrastructure. This parallel suggests a long-term power concentration is forming.

By investing billions in both OpenAI and Anthropic, Amazon creates a scenario where it benefits if either becomes the dominant model. If both falter, it still profits immensely from selling AWS compute to the entire ecosystem. This positions AWS as the ultimate "picks and shovels" play in the AI gold rush.

Despite possessing frontier models through its OpenAI investment, Microsoft's cloud growth is throttled by the physical limitation of data center and AI hardware availability. This bottleneck directly caps Azure's revenue potential, demonstrating that AI dominance is fundamentally dependent on solving real-world infrastructure challenges.