AI makes 'yesterday's expert competence' cheap, leading to an abundance of decent but generic outputs (e.g., code, essays). This devalues standard work and increases demand for true experts who can add nuance, create systems, or produce something genuinely novel that stands out.

As AI commoditizes execution and intellectual labor, the only remaining scarce human skill will be judgment: the wisdom to know what to build, why, and for whom. This shifts economic value from effort and hard work to discernment and taste.

In fields like law and consulting, AI will automate the generation of work products (e.g., contract reviews). This commoditization will shift value upstream to uniquely human skills like providing strategic advice and experienced judgment based on the AI's output.

AI tools drastically reduce the time needed to complete complex tasks, breaking the traditional billable-hour model for consultants and agencies. The focus must shift to value-based pricing, where compensation is tied to the problem solved or the output created, not the hours worked.

As AI and technology automate repetitive, high-quantity tasks, the measure of human efficiency shifts. The new benchmark is not how much a person produces, but the quality of their ideas, insights, and complex problem-solving. Human value now lies in quality over quantity.

AI models are trained on past human work (code, articles, designs), making those skills cheap and accessible. This abundance creates homogenous, default outputs or "slop." Consequently, the market develops an urgent demand for human experts who can create something novel and differentiated, moving beyond the model's defaults.

If AI makes intelligence cheap and universally available, its economic value may collapse. This theory suggests that selling raw AI models could become a low-margin, utility-like business. Profitability will depend on building moats through specialized applications or regulatory capture, not on selling base intelligence.

AI accelerates capitalism's natural tendency to compress margins to zero. By automating tasks and replicating solutions cheaply, AI makes it difficult to sustain profits, benefiting only those who own scarce, non-digitizable assets like data, trust, or real estate.

Advanced AI tools have made writing software trivially easy, erasing the traditional moat of technical execution. The new differentiators for businesses are non-technical assets like brand trust, distribution networks, and community, as the software itself has become instantly replicable.