If AI Learns From My Code, Doesn't It Mean My Job Is Safe?

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.

The rarest sight in AI development: code that works on the first try. This image shows NASA engineers celebrating a successful mission, but in the AI world, it's more like celebrating when someone's neural network doesn't immediately catch fire or hallucinate that birds are government drones. Builder.ai probably shared some code that actually ran without 47 dependency errors, 18 version conflicts, and a cryptic error message about missing semicolons in a language that doesn't use semicolons.

Ah, the evolution of debugging assistance. In 2019, you'd explain your problem to a rubber duck (a legitimate debugging technique where explaining your code aloud helps you spot the error). The duck just sits there, judging you silently while you ramble about line 43. Fast forward to 2025: Now you just bark "FIX THE ERROR" at ChatGPT, Claude, or whatever AI overlord is running your IDE. No need to understand the problem anymore - just demand a solution and watch as the machines do what took us mere mortals hours of Stack Overflow scrolling. The real error was thinking we'd still be doing our own debugging.

Claiming you've been using ChatGPT since 1996 is like saying you had WiFi in the Middle Ages. For the youngsters: that's Courage the Cowardly Dog typing on a chunky beige PC from when the internet made dial-up sounds that haunted your nightmares. Back then, "AI assistance" meant asking your roommate if they remembered the syntax for a for-loop while they were in the shower. The closest thing to ChatGPT was probably Clippy, and even he couldn't help you reverse a binary tree.

Oh, the beautiful irony! Training AI to spew corporate buzzwords and then mistaking that for consciousness is like thinking your parrot understands quantum physics because it can squawk "synergy" and "circle back." Turns out the Turing test is just asking, "Can you use the phrase 'let's take this offline' without actually solving anything?" If meaningless jargon is the benchmark for intelligence, we've been working with artificial intelligence in management for decades!

Corporate: "Can you spot the difference between a gold bar and a high-end GPU?" Developers in 2024: "They're the same picture." With GPUs costing as much as precious metals these days, training that fancy ML model might require a second mortgage. Remember when we just worried about RAM prices? Those were simpler times.