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Joined 8 months ago
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Cake day: March 24th, 2026

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  • It makes sense that if you can’t be bothered to write it, then I can’t be bothered to read it.

    Also, the term “AI slop” puts the blame on a machine instead of the lazy human who doesn’t give a shit and can’t be bothered to so much as proofread a machine’s output based on their half-assed input before subjecting other humans to it and wasting their time.






  • The emergent behavior in huge models where it can “reason” instead of simply predicting the next token is fascinating. Artificial “neurons” built on statistics and linear algebra emerge to create something that legitimately has artificial intelligence. ANNs were conceived in the 1940s, building on centuries of development in statistical modeling and only now do we have the compute power to make this vision a reality.

    Yes, the “intelligence” has significant limitations and won’t be replacing human intelligence anytime soon, but it can actually be a useful tool if its limitations are kept in mind.

    The problem is of course the tech bros turning centuries of innovation they had no part in developing into a massive Ponzi scheme for their own profit.





  • Repo level markdown files with architectural guidance not working for example… I’ve found that works quite well.

    Same. AGENTS.md files and the like are quite effective. Especially if you’re reviewing the code and making the LLM help you update the markdown files when it makes a mistake to prevent the same type of mistake in the future. Having concrete examples of “good” vs. “bad” to illustrate each architectural rule goes a long way.

    For any feature or bug fix that is “painting with the colors already in the tray”, it makes sense to let a LLM write the code. Humans will introduce new tech and new patterns out of boredom and turn the codebase into a big Frankenstein, but the LLM will just follow the architectural guidelines indefinitely.