The Problem Isn’t AI. It’s the Pace.

The speed of artificial intelligence development is not the problem, but rather the gap between how quickly technology advances and how slowly we adapt to those changes, says the author. They acknowledge that AI capabilities are growing rapidly, with tools like Vite and Rollup accelerating the JavaScript toolchain, and AI models building on each other without a plateau.

This compounding gap creates a challenge where no single person can become deeply expert in everything, leading to codebases that stack multiple eras of tooling, with nobody left who comprehends the bottom layer. The author contrasts this with past technological advancements, which had plateaus allowing for adaptation, whereas the current AI development process lacks a pause.

They argue that the problem lies in the slow-moving scaffolding around biology, such as norms, laws, professional identity, and institutions, all of which evolve at a much slower pace compared to technology. The author acknowledges that the desire to keep up with AI advancements is overwhelming, but suggests a more constructive approach: deliberately choosing what to not keep up with, and finding peace with that decision.

This involves focusing on a short list of things to go deep on, while letting go of the much longer list of tools and advancements that pass by. For the author, this means being selective about adopting new tools until they have proven their worth, and avoiding the notion of personal failure in the face of rapid change.