2026-06-04原文2 min readUpdated: 2026-06-05

AI enthusiasts are in a race against time, AI skeptics are in a race against entropy

Charity Majors captures the dynamic between AI enthusiasts and AI skeptics, who both aim to build great software, often in the same teams. Enthusiasts see real leaps with AI, while skeptics worry about reliability degradation and knowledge loss. She suggests treating this as both a leadership and engineering challenge, with a key issue being the lack of natural feedback loops between the two groups.

SourceSimon Willison's Weblog

Simon Willison’s Weblog

4th June 2026 - Link Blog

AI enthusiasts are in a race against time, AI skeptics are in a race against entropy (via) Charity Majors neatly captures the dynamic between AI enthusiasts and AI skeptics, both of whom are trying to build great software, often in the same teams:

The enthusiasts are not wrong. We are starting to see real, non-imaginary, discontinuous leaps in capabilities from teams that lean in hard to working with AI. And this does not feel like a normal technology cycle where you can wait for the dust to settle; teams that sit this out while competitors are hustling could be out of business before the dust settles. That’s a real, existential threat.

The skeptics are also not wrong. When you ship code faster than engineers can read it, in domains where nobody has full context, you are making withdrawals from a trust account that took years to build. Reliability degrades, institutional knowledge evaporates. You end up with systems nobody understands, products burbling into incoherence, and on-call rotations that grind people up and spit them out. That is ALSO a real existential threat.

Charity recommends treating this as both a leadership challenge and an engineering challenge. The key issue:

There is no natural feedback loop connecting enthusiasts with skeptics.

Designing feedback loops to help "mend the gap in shared reality" between the two groups is a fascinating organizational design problem.