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Spending 30 minutes writing a script to automate a 5-minute task is the hill I'll proudly die on. Sure, I could just do the damn thing, but where's the elegance in that? The cosmic irony of programming: we'd rather spend 6x longer building the automation than actually doing the work. It's not laziness—it's "future-proofing." And yes, I know I'll never run that script again. But what if I did ? Checkmate.

Content EXPECTATION REALITY A.l. will usher in a new age of prosperity. Your claim is denied. Go home and die.

For decades, error handling was that thing everyone nodded about in code reviews but secretly wrapped in a try-catch that just logged "oops" to console. Nobody wrote proper error messages, nobody validated inputs, and stack traces were treated like ancient hieroglyphics. Then AI showed up and suddenly everyone's an error handling expert. Why? Because when your LLM hallucinates or your API call to GPT-4 fails, you can't just shrug and refresh the page. Now you need graceful degradation, retry logic, fallback strategies, and detailed error context. The massive book represents all the error handling knowledge we should've been using all along. The tiny pamphlet is what we actually did before AI forced us to care. Nothing motivates proper engineering practices quite like burning through your OpenAI API credits because you didn't handle rate limits correctly.

Content 1st rule of Programming: If it works.... don't touch it!..

Content Interviewer: What's your biggest strength? Me: I'm an expert in machine learning. Inteviewer: What's 6 10? Me: Zero. Interviewer: Nowhere near, it's 16. Me: It's 16. Interviewer: Ok... What's 10 20? Me: It's 16.

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