AI, technology, education, and ideas about what comes next.
Ideas, frameworks, and systems for understanding how technology, society, human thinking, and complex forces interact to shape the world.
AI capability is advancing faster than institutions can absorb it. This episode connects the AI infrastructure problem, the Toolbox versus Idea Black Box question, and the emerging transfer of productive power toward individuals.
When AI enters mathematics, the challenge is not only whether machines can solve difficult problems, but what happens to discovery, attribution, provenance, and the human mathematical ecosystem.
When AI becomes a rented cognitive capability and commercial systems are built on humanity’s accumulated knowledge, who owns the work—and who owns the future?
AI does not need to replace teachers to disrupt teaching. What happens when scalable AI expertise enters a market built around selling instruction by the hour?
What happens if ASI succeeds? This thought experiment explores how abundance, automation and AI dependence could affect human agency, meaning and purpose.
A framework for separating AI capability, cognitive labor, work product, attribution, confidentiality, and rights—and understanding AI as a digital employee or agent.
AI may be weakening one of the traditional reasons companies needed to become large: the need to employ large numbers of specialists. As AI turns specialized capability into something that can be summoned on demand, a new organizational form may emerge—the lean micro-corporation, with a tiny human core commanding enormous productive capacity.
AI may create a new economic channel in which people contribute ideas, expertise, methods and cognitive systems to the development of machine intelligence—and potentially share in the value created.
AI can reason brilliantly inside the wrong frame. From the counterfeit-cap puzzle to the bat-and-ball problem, the deeper challenge is not merely solving a question but recognizing whether the question itself deserves to be solved.
Does an average IQ place a limit on what a person can understand? This article explores IQ, knowledge, abstraction, cognitive distance, teaching, and the role of mental models in understanding difficult ideas.
IQ matters, but it is not destiny. Research suggests that success emerges from the interaction of cognitive ability, execution, education, environment, opportunity, persistence, timing, luck, and compounding.
AI could shift education from a fixed four-year journey to a continuous, adaptive capability system in which people learn, demonstrate, work and keep learning.
AI companies are approaching a turning point: remain providers of powerful research tools, or become intellectual institutions that discover and commercialize ideas themselves. The difficult territory lies between the two.
The seed is not the beginning of life. A thought experiment about energy flow, information, propagation, artificial life and the possibility that life begins when a self-maintaining loop closes.