Stack Wars: The Garage Myth Meets the Five-Layer Cake
The canonical story of the modern tech firm still starts in a metaphorical garage. William Hewlett and David Packard with the audio oscillator. Steve Jobs and Steve Wozniak with the Apple I. Jeff Bezos with a door-desk and a handful of mail-order books. We like the simplicity—one inventor, one widget, one market. It’s comforting. Sometimes, it’s even useful.
As a description of how value gets created at the technological frontier in 2026, it is badly outdated.
Watch Jensen Huang’s recent conversation with Dwarkesh Patel and the gap becomes obvious. Asked whether NVIDIA risks commoditization, Huang does not just answer the question—he reframes it. On its face, the concern is reasonable. NVIDIA “sends a GDS2 file to TSMC,” which fabricates the dies, packages them with high-bandwidth memory (HBM) from SK Hynix and Micron, and hands them off to a Taiwan-based original design manufacturer (ODM). Meanwhile, NVIDIA “fundamentally makes software that other people manufacture.”
The jargon is worth unpacking because it is the point. A GDS2 file is the final design file used to manufacture a chip. Taiwan Semiconductor Manufacturing Co. (TSMC) fabricates the chip dies. HBM is the fast memory stacked close to advanced processors. An ODM builds products for another company to sell under its own brand.
In other words, the “product” is not a thing NVIDIA simply makes and ships. It is a coordinated chain of design, fabrication, packaging, memory, systems, software, and deployment.
Huang’s response shifts the lens. NVIDIA’s job, he says, is to turn “electrons to tokens”—to do “as much as necessary, as little as possible.” Whatever the firm does not need to do, it pushes to partners. Whatever it does do, it structures so that everyone else can coordinate around it.
That’s the business.
NVIDIA’s moat is not the graphics processing unit (GPU). It is the coordination layer that makes hundreds of upstream and downstream actors rational in betting on its platform. That list runs long: TSMC, ASML, SK Hynix, Lumentum, Coherent, hyperscalers—the giant cloud providers that buy and operate massive computing infrastructure—artificial-intelligence (AI) labs, framework communities, application developers, financiers, and even, as Huang half-jokes, the plumbers and electricians wiring data-center buildouts.
In short, ecosystem orchestration—not discrete product innovation—is the dominant value-creation pattern in the AI economy.
That reality does not map cleanly onto the categories regulators reach for: single-product monopoly, classic two-sided “matching” platforms, or vertical foreclosure. It also cuts against policymakers’ instincts about where innovation comes from. If the underlying economic phenomenon is ecosystem coordination, analysis that fixates on discrete—and often poorly defined—“products” will miss the mark.
Get the framework wrong, and policy will not just misfire. It will penalize the coordination that drives growth.
The costs do not stay contained. Broad export controls aimed at slowing Chinese competition will also hit U.S. firms and erode the durability of American technological leadership. That tradeoff remains underweighted in a policy debate still anchored to a chip-centric view of the industry.