Veblen & Jevon Walk Into a Data Center

Jevon & Veblen walk into a data center.

The dominant motif around AI has been Jevon’s Paradox¹ : the cheaper a product becomes, the more it is consumed.

Token prices dropped 10-20x over the past 18 months & demand exploded in response.

Anthropic surged past $19 billion in run-rate last month, up from $9 billion at the end of 2025.² OpenAI topped $25 billion in annualized revenue in February, a 17% increase in two months.³

We know GPUs, CPUs, & memory are already in short supply.⁴ Rumors of next-generation models, including Claude Mythos, suggest pricing that moves in the opposite direction.

This weekend, an accidental data leak revealed Anthropic’s secretive Mythos model.⁵ A leaked blog post described it as :

“A step change” in capability, “dramatically higher scores on tests of software coding, academic reasoning, and cybersecurity.”⁶

Anthropic stated the model is “very expensive to serve & will be very expensive for customers.”⁷ Some have speculated on inference pricing 5-6x more than existing models.

If these rumors hold, the most powerful intelligence would trade at a stiff premium. Jevon’s Paradox would give way to Veblen goods.⁸

Veblen goods are those whose demand increases with price : front-row concert tickets that cost 10x more despite worse acoustics. Nike Jordans that retail for $110 and resell for $500+. Ivy League tuition where selectivity is the value proposition.

Could AI follow this dynamic for competitive advantage? The company with capital to access the most powerful model wins. How much is that worth?

Consider a Series A founder building an AI coding assistant. Today, she pays $25 per million output tokens for Opus 4.6. Her burn rate assumes that price. If Mythos launches at $150 per million tokens, 6x more, she faces a choice : raise prices, raise capital, or watch her AI-native competitor ship features she can’t match.

The token-maxxing era ends. Companies will stop optimizing for cheap inference. They’ll deploy capital aggressively, both GPUs & dollars, to maximize capability rather than minimize cost.

Balance sheets become a moat. The most profitable companies or those who can raise capital cheaply will have the biggest advantage in their industries.

For companies that cannot respond quickly enough or afford the most sophisticated AI, the gap widens. If AI-native companies can build 10x faster with Mythos-class models while competitors are stuck on Opus 4.6, valuations will diverge further.

Jevon & Veblen walked into a data center. We don’t yet know who walks out.