• john garrish
AI Doom or Boom
The 2028 Global Intelligence Crisis
A competent developer working with Claude Code or Codex could now replicate the core functionality of a mid-market SaaS product in weeks.
I particularly disagree with this idea.
Citrini Research and Alap Shah lay out a macro doom scenario.
It’s worth a read if for no other reason than it’s fodder for your weekend conversations. But I don’t subscribe.
Silicon Valley darlings like Stripe and Linear have built massive followings just by not being as insanely unusable and horrendous as their competitors. Ask tenured engineers “show me a piece of good software” and you’ll get long silences and blank stares.
This is John Loeber’s rebuttal. His core argument: everything is more complicated and takes longer than you think, and the apetitite for improvement is infinity.
I’m more in this camp. The reality of corporate technology improvement is all really damn slow. REALLY REALLY REALLY slow.
The Cyborg Era: What AI Means for Jobs
We’ve had millennia of things (and more humans!) replacing what humans do and yet humans do more than ever. If a million little tasks can be replaced and there is literally zero impact on total employment, why would we assume that wouldn’t hold up for a technology that replaces the next million tasks?
A guest essay by Sébastien Krier via Alex Imas. This is a more optimistic frame: comparative advantage, human preference for certain services, and economic frictions will keep humans in the game even as AI scales.
El Segundo started to produce more than just companies. It ended up producing a tight-knit community. Co-founders who were bonded by their belief that America needed a new model for progress.
If you want optimism, none of these are considering what is happening in the Gundo. Which I consider to the most optimistic of all futures.