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Often though working through a bug teaches the developer something about the relevant abstraction. That knowledge can get lost in this new process.
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While you're right, and I'm constantly thinking/worrying about my own processes giving me AI apathy, you can use AI in a way that develops your understanding of a bug. It really depends on your workflow.

When I use AI to debug a problem, I'm constantly questioning the specifics because I want to learn it, and often I'm better than the AI at quickly recognising patterns that point to a specific issue, where the AI will spin for some time trying to work out where to start - even if it has full context.

So I guess I'm half with you, but an LLM used right can still teach you effectively.

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Yes. I agree with that as well. If you can intuit that it's (for example) an off-by-one error somewhere in your logic, asking an LLM to pinpoint that issue can save you tons of time that is better spent thinking about your abstractions. Also, I tend to ask high-level questions to the frontier models about best practices with common abstractions. But "the screen flickers here, please fix" is a bad pattern, IMO. Understanding why the screen is flickering is likely to educate you about where your abstractions are leaking.
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Claude will happily add a null guard without checking why the null is there in the first place...
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