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Autor refleksji zauważa, że modele językowe (LLM) zmieniają nawyki edukacyjne inżynierów. AI szybko streszcza prace naukowe, dając złudzenie wiedzy bez głębokiego uczenia się. Prawdziwe zrozumienie wymaga głębokiego czytania i praktyki, a nie tylko skrótów. To zjawisko bywa groźniejsze niż zwykłe lenistwo.

I've been reflecting on how LLMs are changing our learning habits as engineers, and realized something worrying.AI can now quickly help search and research information, distilling the core of a paper into a concise summary. It lets you pick up a term fast and have something to talk about.But real learning requires deep reading, thinking, and practice. A polished summary is far from enough. Since having AI, how long has it been since you truly studied a paper or deeply read through and implemented a technology? Has your ability to think and your taste improved or declined? Once that ability is weakened, are you ready to let AI replace you entirely? Taste is never built by reading abstracts — it is forged through countless bad decisions and excellent practice.To be honest, most people never seriously finished reading many papers before AI either. AI hasn't taken anything away — it has just made shallow learning more efficient and more deceptive. The real risk isn't that AI makes people lazy, but that AI makes "lazy" look like "productive." Spend ten minutes reading a summary, post it on social media, feel like you're keeping up with the frontier — but nothing actually sticks.I am absolutely not against AI. What I advocate is using AI for deep work, not treating it as your TikTok of pretend learning. From "summarize it for me" to "debate it with me," from "do it for me" to "help me reason through it" — that is what matters. Comments URL: https://news.ycombinator.com/item?id=47555081 Points: 7 # Comments: 2