AI has made knowledge—the ability to produce information—cheap and accessible. The new currency is wisdom: knowing what matters, where to focus, and how to find purpose. This shifts the focus of work and education from learning facts to developing critical thinking, empathy, and judgment.

As AI handles more routine tasks, uniquely human skills like creativity, strategic thinking, clear communication, and collaboration are becoming table stakes. These former "soft skills" are now mandatory for career growth and resilience.

As AI outsources thinking, specific job "skills" have a shorter shelf life. The new focus for education and corporate training must be on developing durable human "capabilities"—critical thinking, collaboration, and discerning truth from falsehood—that are necessary to effectively manage and leverage an AI superpower.

As AI handles technical tasks, the value of hard skills diminishes. The most crucial employee traits become "human" qualities: buying into the company vision, emotional intelligence, and self-awareness. These are the new competitive advantages in talent acquisition.

As AI automates technical and procedural tasks, professions requiring 'soft skills' like critical thinking, aesthetic judgment, and contextual understanding become more valuable. Fields like engineering may face more direct competition from AI, making a background in humanities a surprisingly strategic long-term career asset.

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.

The internet leveled the playing field by making information accessible. AI will do the same for intelligence, making expertise a commodity. The new human differentiator will be the creativity and ability to define and solve novel, previously un-articulable problems.

To stay relevant, humans shouldn't try to become more machine-like. Instead, they should focus on three categories of work AI struggles with: 'surprising' tasks involving chaos and uncertainty, 'social' work that makes people feel things, and 'scarce' work involving high-stakes, unique scenarios.

With AI handling execution, the differentiating skills for knowledge workers are no longer technical. Instead, value comes from having a distinct vision (taste), the initiative to pursue it (agency), and the ability to organize complex projects (structure).