What Debugging Is Really Like

Ah yes, the classic "let me solve this simple problem with the most unnecessarily complex solution possible" approach. Two mutually recursive functions to check if a number is even or odd? This has ChatGPT's fingerprints all over it. Meanwhile, every developer with more than 3 brain cells is screaming: return (n % 2 == 0); and calling it a day. This is what happens when you ask AI to "make it elegant" or "optimize this function." You get code that looks impressive in a technical interview but would get you publicly shamed in a code review.

Normal people sleep peacefully while programmers lie awake, staring into the void, haunted by that one bug they can't fix, the looming tech layoffs, existential AI career threats, and the crushing obligation to learn yet another JavaScript framework that'll be obsolete before they finish the tutorial. Sleep is just a luxury reserved for those who don't know what a dependency tree is.

The perfect metaphor for our relationship with legacy code! First, we acknowledge it feels abandoned and worthless after years of neglect. Then we realize we actually need it because the entire production system depends on it. We examine it closer, only to discover it's simultaneously a masterpiece of engineering and absolute garbage that nobody wants to refactor. The dung beetle whispering sweet nothings to literal crap is exactly how we justify maintaining that COBOL monstrosity from 1983 that somehow still processes all your financial transactions.

Ah, the family tree of dependency hell! Just like how you can't exist without Mom and Dad, and they somehow need you to function (especially when they need tech support), your code shouldn't form these ridiculous loops either. This is basically every developer justifying their spaghetti architecture with "but it works in real life!" Sure, and my code works on my machine too. Doesn't mean it's not a disaster waiting to happen when someone else tries to untangle your family issues—I mean, dependencies.

When your debugging session gets interrupted by a rubber duck that actually works. The developer starts explaining their CSS padding issue to ChatGPT, notices something's wrong, and suddenly the rubber duck falls out of nowhere—forcing them into accidental rubber duck debugging. The irony? The duck solved the problem before ChatGPT could even respond. Proof that sometimes the best debugging tool is just talking to an inanimate object that judges you silently from your desk drawer.

Content Me with Computer Science degree Relatives asking me to fix their printer