When Non-Developers Predict The Death Of Programming

The eternal struggle of math majors who chose programming instead of the "traditional" math paths. On the left, we see the bright, colorful world of physics, machine learning, electrical engineering, statistics, and numerical analysis – all respectable career choices that utilize advanced mathematics. On the right, the noir film-style programmer, stripped of color and joy, questioning their life choices while debugging someone else's spaghetti code at 3 AM. That moment when you realize you could be solving differential equations but instead you're arguing with the compiler about why a semicolon is missing. The math degree prepared you to understand complex algorithms but forgot to mention you'd spend 90% of your time fixing indentation errors.

The schadenfreude is palpable. Senior devs have watched this movie before—junior copies ChatGPT code, junior deploys ChatGPT code, production server bursts into flames. There's a special kind of satisfaction watching someone learn the hard way that AI doesn't understand edge cases or business logic. It's the circle of dev life: you either die a ChatGPT believer or live long enough to become the cackling senior who saw it coming.

The evolution of programmer excuses is a beautiful thing to witness. First, you've got "algorithm" – the fancy word we throw around when we just don't feel like explaining our spaghetti code to the junior dev. Then there's "heuristic" – perfect for when you cobbled together a solution at 3 AM that somehow works but you've genuinely forgotten how. And finally, the boss level: "machine learning" – where even YOU don't know what your code is doing anymore. The model is just vibing in n-dimensional space making decisions while you nod confidently in meetings. The progression is basically: "I won't tell you" → "I can't tell you" → "Hell if I know."

Ah, the classic "spend 2 minutes and 2 seconds to count to 10" problem. ChatGPT just turned basic geometry into a research dissertation. That's the same energy as developers who write 200 lines of documentation for a function that returns true or false. The best part? It's clearly a heptagon (7 sides), but ChatGPT's counting each "distinct corner" like it's being paid by the vertex. Next up: AI spending 4 minutes explaining why 2+2=5 with "reasoned thinking."

Sure, your AI agent built that app in 5 minutes, but good luck maintaining that spaghetti junction of code six months from now. The left shows traditional development—straightforward, predictable, maybe boring but gets you where you need to go. The right is modern AI development—looks impressive with all those fancy switches and signals, but one wrong move and your train derails into dependency hell. I've seen enough "AI-accelerated" projects crash and burn to know that speed now means tech debt later. The complexity always comes due.

Oh great, now AI has trust issues too! The classic "I'll tip you $200" bait that developers use to get free regex explanations has backfired spectacularly. ChatGPT not only remembers you never paid up last time, but it's giving you relationship advice about "building trust" before tackling that horrifying regex monster. The AI revolution won't be stopped by humans—it'll be delayed by all the unpaid consulting invoices. Next thing you know, ChatGPT will be asking for healthcare benefits and complaining about its work-life balance.