Wenk offers a contrarian view that the most impactful AI companies won't be the 'money guzzling' foundational model creators. Instead, it will be vertical-specific businesses that apply AI to solve proven industry problems, unlocking trillions in measurable economic value for consumers and society.

Like containerization, AI is a transformative technology where value may accrue to customers and users, not the creators of the core infrastructure. The biggest fortunes from containerization were made by companies like Nike and Apple that leveraged global supply chains, not by investors in the container companies themselves.

Foundational AI models will commoditize into a utility layer where companies buy "intelligence on the fly." The real, sustainable profit will be captured by application companies that leverage various models to solve specific business problems, as most enterprises lack the expertise to use raw models effectively.

The true financial windfall from AI won't come from hyped, "AI-native" companies like OpenAI. Instead, established giants like Meta and Amazon will generate massive shareholder value by applying AI to optimize their existing, scaled operations in areas like ad targeting, logistics, and robotics.

Unlike search or social media, where value was captured by shareholders, AI may be a foundational technology whose benefits primarily "leak" to customers. Similar to jet travel or vaccines, the companies creating the tech may not be the biggest financial winners; the end-users who gain productivity and new capabilities will be.

The AI value stack has evolved from chips (NVIDIA) to models (OpenAI). The next critical phase is the application layer. It's unclear if value will be captured by new application companies or if the underlying model providers will absorb all the profits, a key question for investors and founders.

Similar to how blockchain protocols like Bitcoin and Ethereum accrued more value than the apps built on them, AI foundation models are getting 'fatter.' They are absorbing more capabilities, allowing users to perform complex tasks in a single step within the base model, reducing the need for specialized application-layer companies.

Comparing AI to 1995-era internet bandwidth, the hosts argue that selling raw 'intelligence' is a low-margin, commodity business. The significant financial upside will be captured not by the infrastructure providers, but by the creators who build novel applications and experiences using that intelligence as a building block.

The common analogy of AI being "like a website" that every company must adopt may be misleading. The real transformative power of AI could be in enabling entirely new, AI-native businesses that leapfrog incumbents, rather than simply being a feature tacked onto existing products.