Raw LLM Responses

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G I think you might be misunderstanding the Luddite remarks. It's worth rememberin… ytc_UgxieyF0t… G You know that's complete bullshit, right? Corporate-sourced (Google) AI or AGI … ytc_UgyfAzwNo… G True and it's still painful to remove background from a pic to make a perfect pa… rdc_n7yolgh G @michalw8865Electric regulations work and so do AI. People fall in line at the s… ytr_UgwFUk2xH… G the only way I can see this avoiding the worst case senerio, is if AI develops e… ytc_UgyWWrI9V… G And over on some side of the world is little timmy consuming 60 ai videos per ho… ytr_UgwsdQwVA… G That's utterly absurd. It's an equivalent if saying computers will make unemploy… ytr_UgwsCyEv7… G Calling ai art is like getting abs from plastic surgery instead of actually exer… ytr_UgzehaMb8…
Comment
As a developer who tested Claude/Cline extensively over more than a year, I can say with confidence: Once your project grows beyond ~5,000 lines of code and spans multiple files, Claude loses structural coherence. It starts forgetting context, mismanaging dependencies, repeating errors, and hallucinating logic. Debugging becomes circular. Refactoring? Unreliable. And this isn’t just Claude. No LLM today – including GPT-4, Gemini, Devin – can consistently maintain architectural integrity across a large codebase. There's no persistent memory, no full graph awareness, and no real understanding of software design patterns at scale. The claim that “AI will write 100% of code within a year” is not just wrong – it's deeply misleading. It ignores fundamental limitations of current LLMs: - No true multi-file reasoning - Shallow state tracking - No long-term refactoring memory - No awareness of tech debt or codebase health We’re years away from reliable full-scale AI coding – optimistically 3–5 years, realistically longer.
youtube 2025-07-09T11:2… ♥ 17
Coding Result
DimensionValue
Responsibilityai_itself
Reasoningconsequentialist
Policynone
Emotionresignation
Coded at2026-04-26T23:09:12.988011
Raw LLM Response
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