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Public story · 2026-08-07 · high
A second essay made the same argument through cooking a steak, and its replies argued back more than they agreed.
Why now: Both essays posted within 48 hours of each other, landing together on August 7.
NotAShelf's essay hit 483 points and 349 comments in under a day. It argues the scarce skill in software shifted from making things to judging what deserves to exist. Idea to working software now takes almost no effort, so the bottleneck moved to deciding what's worth keeping.
The essay leans on Sturgeon's Law, the old rule that 90% of everything is mediocre. That ratio holds even as output goes infinite, so the noise floor keeps rising while the signal doesn't move. Taste comes from repeatedly making bad work and learning to recognize it, per the essay.
A separate essay made the same point through cooking a steak: it takes little skill now, but knowing when it's actually good still does. That post hit 375 points, and its comment count topped its points, a ratio above 1.0 that signals real pushback in the replies.
I've made this argument for about a year. Watching two unrelated threads make the same point in two days feels less like being right early and more like watching the room settle on it.
Each link below shares sources, entities, or timing with this story.
NotAShelf's essay at 668 points argues that as AI collapses the cost of producing software, what remains is the judgment to distinguish what works from what deserves to exist, the ability to say "no, again," which can't be automated or measured. Two lines carry it: "The idea-t...
ComposioHQ's awesome-claude-skills sits around 60,000 stars and now curates 1,000+ production-ready Skills, reusable SKILL.md instruction packages with YAML frontmatter, that run beyond Claude across Codex, Cursor, Gemini CLI, and Antigravity. Skills hardened into a portable,...
In a New Stack interview, Dana Lawson argues the engineer's role shifts to "agent experience," a fusion of DX and UX where agents generate code, write tests, find faults, and open PRs in a continuous loop at machine speed. The human contribution is "judgment, taste, direction,...
An r/artificial thread (97 upvotes, 51 comments) popularized the term: in a long conversation, when a model states something wrong and you correct it, both the error and the correction stay in context, and the wrong claim keeps influencing downstream generation. Not novel to p...
A June 7 follow-up (78 points, 125 comments) argues LLMs commoditize software the way they gutted copywriting, supply rising faster than demand. The author rejects OOP comparisons and predicts finance, law, biology, and marketing follow as field-specific harnesses mature. The...
Argues sharing unedited LLM output creates cognitive debt: senders forfeit learning, recipients bear asymmetric verification effort, trust erodes systemically. Cites MIT and Anthropic research. 128pts, 76 comments on HN. stopsloppypasta.ai
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