Using AI effectively isn't about cognitive offloading, which leads to mediocrity. It's about amplifying human thought. Humans must provide the 'why' (ambition) and the 'what' (taste) to bookend the technology, which only solves for the 'how'.

Just as the Industrial Revolution devalued physical strength, AI is devaluing raw intellectual output. As intelligence becomes abundant, value moves to uniquely human qualities like judgment, intuition, taste, and wisdom. AI can determine what is probable, but only humans can decide what is worth wanting.

AI excels at 'left-hemisphere' tasks—the 'what' and 'how-to' of logic. It is incapable of answering the 'right-hemisphere' 'why' questions that give life meaning. The strategic opportunity is to use AI to automate left-brain work, freeing human capacity for love, faith, and creativity.

Assuming AI's productivity gains create an economic safety net for displaced workers, the true challenge becomes existential. The most difficult problem to solve is how society helps individuals derive meaning and purpose when their traditional roles are automated.

Even if AIs can automate all technical aspects of research and engineering, humans will retain the crucial role of defining what the AI should actually do. Specifying goals, shaping behavior (like helpfulness), and setting constitutions will be the longest-lasting human contribution to AI development.

As AI handles analytical tasks, the most critical human skills are those it cannot replicate: setting aspirational goals, applying nuanced judgment, and demonstrating true orthogonal creativity. This shifts focus from credentials to raw intrinsic talent.

As AI agents increasingly automate tasks, the cost of 'doing' work plummets. Greg Brockman argues the most valuable and scarce resource becomes human attention for oversight, judgment, and ensuring AI actions align with high-level goals and values. The core of future work will be deciding 'what' and 'why', not 'how'.

As AI transforms intelligence into a cheap utility, the competitive advantage is no longer knowing the most. Instead, value lies in discernment: applying creativity, judgment, taste, and ethics. The critical skill becomes identifying what truly matters, making wisdom more valuable than raw information.

In a notable rhetorical shift, OpenAI now argues that as AI capability grows, the human role in setting direction, making trade-offs, and applying values becomes *more* critical, not less. This positions AI as a tool for augmentation rather than a vehicle for full automation.