Before replacing human workers, AI expands the total addressable market by making services economically viable for previously unserved segments. For instance, Intercom customers now offer AI support to their free users, something they could never afford with human agents.

Counterintuitively, making a task cheaper and easier with AI doesn't just eliminate jobs; it drastically increases the overall demand for that task. Just as Excel created more accountants, AI's efficiencies will lead to an explosion in the volume of work, creating new roles and opportunities.

Counter-intuitively, as AI models become more efficient, the total consumption of compute resources will rise. This economic principle, Jevons Paradox, states that increased efficiency lowers costs, which in turn unlocks more applications and drives greater overall demand.

The Jevons Paradox, an 1865 economic principle, states that efficiency gains increase total consumption, not decrease it. Applied to AI, as coding becomes cheaper and more efficient, the total demand for software will explode into new applications, ultimately creating a net positive number of jobs.

AI makes tasks cheaper and faster. This increased efficiency doesn't reduce the need for workers; instead, it increases the demand for their work, as companies can now afford to do more of it. This creates a positive feedback loop that may lead to more hiring, not less.

Economists see no AI job loss in data because, like cheaper coal in the 1860s, cheaper intelligence via AI doesn't shrink demand. Instead, it explodes it, creating new roles and applications that offset initial displacement.

Contrary to fears that efficient models will curb computing needs, lower costs will attract more users and enable complex applications, leading to higher overall consumption. This is a classic example of Jevon's paradox, where increased efficiency drives greater demand for a resource.

Counterintuitively, Anthropic lowered the price of its premium Opus model because it was underutilized. This move triggered the Jevons paradox: the lower price made Opus more accessible, and consumption increased by a far greater multiple than the price decrease, unlocking significant value for customers.

The host experienced Jevons paradox firsthand: after switching from a barely-used enterprise ChatGPT to the more efficient OpenClaw, usage exploded. Costs trended towards exceeding the company's payroll, highlighting how efficiency gains in AI can lead to unsustainable consumption increases.