The 'Andy Warhol Coke' era, where everyone could access the best AI for a low price, is over. As inference costs for more powerful models rise, companies are introducing expensive tiered access. This will create significant inequality in who can use frontier AI, with implications for transparency and regulation.

Advanced technology used to be expensive, requiring permission from investors or governments. Now, cheap and accessible tools like AI and open-source platforms allow individuals anywhere to innovate disruptively without needing approval, as exemplified by Ethereum.

The most effective government role in innovation is to act as a catalyst for high-risk, foundational R&D (like DARPA creating the internet). Once a technology is viable, the government should step aside to allow private sector competition (like SpaceX) to drive down costs and accelerate progress.

The inability of the general public to invest in generational companies like OpenAI creates a societal risk. When a generation feels economically disconnected from major value creation and simultaneously threatened by that same technology, it fosters a negative future for everyone.

The primary barrier to realizing the benefits of new technologies like AI isn't the tech itself, but a societal structure Stripe calls the "Republic of Permissions." Non-market forces like regulators, committees, and courts create synthetic impediments that prevent economically superior solutions from being adopted.

Unlike private companies seeking product-market fit within a specific segment, designing digital public infrastructure (DPI) requires a different mindset. The goal is creating a level playing field that enables *everyone* to participate and allows markets to innovate on top.

Contrary to fears of a 'digital divide,' technology driven by free markets has become the great equalizer. Today, more people worldwide have access to smartphones and the internet than to basic utilities like electricity or running water, proving that market forces democratize access effectively.

Drawing a parallel to Intel's early strategy, the immense capital costs of AI development necessitate serving the largest possible market (consumers and businesses). This private, market-driven approach inherently conflicts with government expectations for control, as the government becomes just one of many customers for a globally-scaled technology.

The idea that AI owners will hoard wealth is a Marxist fallacy. True capitalist self-interest, demonstrated by Tesla's plan to create mass-market vehicles, incentivizes companies to make technology as cheap and broadly available as possible to capture the largest market.