An essay published on OpenAI's platform, written by Hemanth Asirvatham and Elliott Mokski, argues that the greatest value of AI may lie in handling mundane execution rather than delivering genius-level insight. The authors point to a widening gap between what minds can imagine and what institutions can actually build. Galileo needed only a few dozen hands for his telescope, while the James Webb Space Telescope required a global army of organizations and billions of dollars—progress, they argue, is increasingly limited by execution capacity, not ideas.
The essay cites research showing that sustaining Moore's law now takes over eighteen times more researchers than in the early 1970s, and that economy-wide research productivity has fallen sharply despite a massive increase in effort. The authors frame this through the economic concept of complements: a brilliant hypothesis is more valuable when the machinery and support staff exist to test it, and better instruments make good questions more valuable. They call the unglamorous work of institutions—laws, supply chains, funding mechanisms—"institutional intelligence," and say it is just as crucial as genius.
AI, they argue, is already making execution less scarce by writing code, searching unfamiliar literature, and turning sketches into prototypes. That means ideas that once required a whole organization can increasingly be pursued by one ambitious person. The authors' note clarifies that the views are their own and not those of OpenAI or their colleagues, but the essay offers a concrete case for why the "intelligence age" may begin by complementing human effort rather than replacing it.