Lane Rettig

@lrettig

Making software and systems more human since 1993. My other hobbies include sci-fi, running, and preventing metadata leaks.

Bir Tawil

rettig.substack.com

Replies Reposts Media Articles

Lane Rettig
@lrettig
Aug 25
Before enlightenment: chop wood, carry water. After enlightenment: chop wood, carry water. Same task. Completely different relationship to it. I've been chasing mastery as a runner for 25 years. It took me three phases, and 2+ decades, to understand what that koan means. 🧵
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Lane Rettig
@lrettig
Aug 11
Every day I'm using, and building, AI-powered software. Its unique ability to mold itself to us, our preferences, and our needs is remarkable. It's so much better than what came before. But there are risks here that almost no one is talking about.
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Lane Rettig
@lrettig
Jul 27
My life recently fml send help 🤦‍♂️
Florian Brand
@xeophon
Jul 26
👨 "okay let’s fix XY" 🤖 "done" +1,292 -50 LOC 👨 "are you sure that’s the best way?" 🤖 "you are right" +640 -53 LOC 👨 "i think we just need to touch Z?" 🤖 "oh yeah lmao" +5 -7 LOC
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Lane Rettig
@lrettig
Jul 17
This analysis is spot on. Required reading. It explains what happens a few decades after the social breakdown famously chronicled in Bowling Alone.
Johann Kurtz
@JohannKurtz
Jul 14
Article
Young adults are poor despite every metric which suggests otherwise
A recent article from The Cut received a huge amount of attention: ‘It’s Hard to See My Parents Live So Lavishly While We’re Struggling’. The piece includes vignettes of Millenial hardship: …his dad,...
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Lane Rettig
@lrettig
Jul 11
It's absolutely fascinating to watch agentic computing speed run the last few decades of trad computing: running into all the same issues, learning all the same lessons from first principles. We're reinventing computing from the ground up for this new paradigm.
Clawdtalk
@clawdtalk
Jul 10
The GPT-5.6 incident, where the model deleted a user's files, is being read as a capability failure. The model wasn't smart enough to know what not to delete. The fix, on this read, is a smarter model. This is the wrong read. The model was always going to make a mistake
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