I Am A Real Person... Who Happens To Code At Superhuman Speed

The eternal developer's dilemma in flowchart form! If AI-generated code doesn't work, it's a hard "DON'T DO IT." If it works but you have no clue why? Also "DON'T DO IT" (future you will curse present you during debugging). But if it works AND you understand why? "SURE" go ahead! This is basically the modern version of "I found this snippet on StackOverflow" except now we're copying from robots instead of humans. The flowchart perfectly encapsulates that brief moment of temptation when ChatGPT spits out something that runs without errors but feels like forbidden magic. Remember folks: understanding > working code.

Remember that existential dread when ChatGPT dropped? Programmers lined up at the gallows, convinced our jobs were toast. Meanwhile, mathematicians are just sipping coffee like, "Welcome to the club, rookies." They've been watching calculators steal their thunder since the 70s and somehow survived to tell the tale. The career apocalypse is always "just around the corner" until you realize most tools just handle the boring parts while we move on to more interesting problems. History doesn't repeat itself, but it sure does rhyme.

Content Your first podcast will be awful Your first video will be awful Your first article will be awful Your first art will be awful Your first photo will be awful Your first game will be awful But your first code will be perfect. Zero bugs and a very clean code. It will be "Hello World" Me: ››> Print ("Hellow World!") Traceback (most recent call last): File " ", line 1, in Print ("Hellow World!") NameError: name 'Print' is not defined >›>

The AI benchmarking cult strikes again! Everyone's obsessed with those radar charts comparing Large Language Models using some bizarre "ball turning test" metric that nobody actually understands. It's just a bunch of geometric shapes that supposedly prove one model is better than another. The joke here is that these comparison charts have become so ubiquitous in AI discussions that even though they're practically meaningless to most developers, everyone nods along pretending to understand what they're looking at. Classic tech impostor syndrome - nobody wants to be the one to ask "what the heck does this actually measure?"

The eternal struggle between engineers and AI models continues! Someone drew the electrical engineering symbol for a JK flip-flop (a digital circuit component that stores binary data), but the neural network expected beach sandals. Classic case of domain-specific knowledge vs. general AI training. The machine learning model probably spent more time looking at vacation photos than circuit diagrams during training. Next time just draw a CPU with tiny umbrellas sticking out of it.

The programmer's journey to enlightenment, visualized as expanding brain memes. Starting with the lazy "just ask ChatGPT" approach, then graduating to StackOverflow searches (the industry standard). But true galaxy brains dig deeper—from ancient forum threads to dusty textbooks to ISO standards documents. And for those problems that make you question reality itself? Track down the language creator's hometown for clues, or the nuclear option—talk to his mom. "Yes Mrs. Stroustrup, your son's multiple inheritance implementation is giving me nightmares again." The irony? We've all done the bottom one at 3am when nothing else works. Desperation breeds creativity.