You Are The Bug

Congratulations, you've just reinvented rubber duck debugging but with extra steps. Turns out, articulating your problem clearly enough for an AI is the same mental process that makes you realize the solution yourself. The real ChatGPT was the brain cells we activated along the way. The irony is delicious - AI researchers discovering that humans think better when forced to explain things clearly. Next breakthrough: water is wet.

Content MACHINE LEARNING inglip.com

Ah, the classic corporate brainstorming session where everyone's looking for shortcuts except the one person suggesting the obvious solution. Low-code, AI, buzzwords galore—but nobody wants to hear "just hire someone who knows what they're doing." That dev getting thrown out the window represents every competent engineer watching their company chase shiny tech instead of proper staffing. The real punchline? Six months later they'll hire three devs anyway, but only after burning through the budget on half-baked AI solutions that generated more bugs than features.

The quill pen of yesterday becomes the AI assistant of today. In the original scene, Harry writes "My name is Harry Potter" and Tom Riddle's diary responds. Now it's ChatGPT introducing itself instead - completing the perfect metaphor for modern programming. Ten years ago we'd spend hours debugging regex. Now we just ask an AI to write it. Magic? Maybe. But like Tom Riddle's diary, I can't help wondering what part of our soul we're trading for this convenience. Remember when we had to actually understand how things worked? Those were dark times. Terrible, yes... but great.

Google's AI Overview just confidently explained that matrix multiplication "is not a problem in P" (polynomial time), which is... hilariously wrong. Matrix multiplication is literally IN the P complexity class because it can be solved in polynomial time. The AI confused "not being in P" with "not being solvable in optimal polynomial time for all cases" or something equally nonsensical. This is like saying "driving to work is not a problem you can solve by driving" – technically uses the right words, but the logic is completely backwards. The AI hallucinated its way through computational complexity theory and served it up with the confidence of a junior dev who just discovered Big O notation yesterday. And this, folks, is why you don't trust AI to teach you computer science fundamentals. It'll gaslight you into thinking basic polynomial-time operations are unsolvable mysteries while sounding incredibly authoritative about it.

Content Programmers in the past Writes code without StackOverflow and AI Creates a whole game on Assembly Fixes memory leaks using pointers Programmers now Writes code for the Moon landing BY HAND Googles "how to center div 2025* ChatGPT please fix the syntax error Can't exit Vim Fixes one bug, creates 3 new ones