Don't Be Lazy: AI Won't Fix Your Bad Code

Oh, welcome to modern programming—where your IDE is just a browser with five AI tabs open. Remember when we used to debug our own code? Now we're just glorified AI wranglers, making the machines fight each other for the best solution. The truly painful part isn't even the AI dependency—it's the brutal self-awareness at the end. "It's me." Yeah buddy, it's all of us now. We've evolved from Stack Overflow copy-paste artists to AI response evaluators. Progress? Next week we'll just have AIs asking other AIs and cut out the middleman entirely. My job security is weeping in the corner.

Started coding a "simple hash function" and GitHub Copilot went full existential crisis mode. Started reasonable with "not cryptographically secure, but fast" then spiraled into "not guaranteed to be stable across different phases of the moon" and "different parallel universes." This is what happens when your AI assistant has seen one too many 3 AM debugging sessions. Somewhere in Silicon Valley, a neural network is clearly having PTSD flashbacks from training on StackOverflow comments.

Remember when we argued about text editors like they were sports teams? Now we're just watching AI companies slap version numbers on VS Code forks like they're NFTs. "My VS Code fork has more digits than yours" is the new "my dad can beat up your dad." Meanwhile, Emacs users are still configuring their first keystroke from 1976.

The great AI revolution has arrived... or has it? On the left, we have the muscular "Expectation" Doge representing those grandiose AI promises: code generators so powerful they'll make human developers obsolete! On the right, there's the pathetic "Reality" Doge – the actual AI that can't even handle a simple "Hello World" program without hallucinating semicolons. Meanwhile, executives who dumped "gazillion dollars" into AI development are frantically laying off actual programmers to cover their bad investment. Because nothing says "our AI strategy is working perfectly" like firing the people who could fix the AI's broken code. The corporate playbook never changes: overpromise, underdeliver, then blame the humans. At least the shareholders will feel better about those quarterly losses!

Ah yes, nothing says "efficient solution" like using a machete labeled "Deep learning" to slice through a tiny piece of bread labeled "Simple problem." The classic case of computational overkill. Why use a simple if-statement when you could train a 500-layer neural network that requires a small power plant to run? Next week: using quantum computing to calculate a 15% tip.

The eternal dance between developers and regex—a cryptic language that might as well be ancient runes. When ChatGPT spits out a working regex that looks like someone headbutted a keyboard, what do we do? Copy-paste that mystical incantation and back away slowly. It's the modern equivalent of summoning a demon—you don't need to understand the Latin, you just need the spell to work. And when it does? Pure dopamine. That smug satisfaction of solving a problem without actually understanding the solution is programming at its finest. Future you will hate present you when that regex breaks in six months. But that's a problem for future you, who is, quite frankly, a bit of a buzzkill anyway.