Artificial Intelligence

Improvement is not only a matter of moving downhill. It is also a matter of choosing which valley is worth descending into.

Founders keep asking how to build faster. That's the wrong question. Speed was the bottleneck for twenty years. It's not anymore.

Most prompts produce answers. Answers are cheap. Signal is what reduces uncertainty—and it’s what actually moves the work forward.

Scaling AI isn’t a software story. It’s an industrial build constrained by power, transformers, cooling, and time-to-build.

The centaur was human judgment augmented by machine power. The reverse centaur is human labor subordinated to machine logic. We are becoming the horse.

Attention spans have collapsed from 2.5 minutes to 40 seconds in two decades. This is not a personal failing. It is an engineered outcome.

By 2025, search engines and recommendation systems have moved beyond mere tools for retrieving information—they’ve become extensions of human cognition, functioning as externalized brains. Powered by advances in indexing, vector databases, and cross-referencing technologies, these systems reshape how we process knowledge. But as they grow indispensable, we must confront a critical question: Are they enhancing our thinking, or are we outsourcing it entirely?

There was a time, not so distant, when the artist’s labor was a rebellion against oblivion—a furious demand to be seen, heard, or understood across the gulfs of time. Caravaggio’s chiaroscuro wrestled with mortality itself; James Joyce redefined the limits of language as though daring humanity to keep up. Today, that struggle has been outsourced to a cold and unfeeling steward: the Algorithm, a faceless arbiter whose only metric is engagement, a deity whose offerings are served with a side of irrelevance.