Vibe Check: Debugging AI-Generated Spaghetti Code

So they want a "Vibe Coder" who "orchestrates code through the power of AI" and "vibes their way to a brilliant front end product." Translation: We want someone to type prompts into ChatGPT while we pretend we're revolutionizing development. This job description screams "we have no idea what we're doing but we've invested too much in AI to admit it." Soon they'll replace "Senior Developer" with "Prompt Engineering Guru" and wonder why their codebase looks like it was written by a caffeinated squirrel with a keyboard. The funniest part? 42 people actually applied. Desperation truly knows no bounds in this economy.

Ah, the ultimate job security plan! Turns out the one person AI won't replace is the colleague who contributes absolutely nothing. That sweet spot where you're so useless that even automation can't justify the ROI of replacing you. It's like finding a bug so bizarre that QA just labels it as "expected behavior" and moves on. The perfect defense against technological unemployment isn't upskilling—it's strategic incompetence!

The evolution of getting help as a developer! First we had Reddit calling our questions "stupid," then Stack Overflow dismissing everything as "off-topic," and now ChatGPT responding with "that's a very good question" to even the most ridiculous requests like "how to prevent screenshots of my website." Finally, a digital assistant that doesn't make us feel like complete idiots for not knowing something! It's the therapy we never knew we needed after years of Stack Overflow PTSD. Breaking generational trauma one suspiciously positive response at a time.

Ah, the classic "let's use a sledgehammer to kill a fly" approach. Every tech startup these days thinks they need machine learning to solve problems that could be handled with an if-statement and a cup of coffee. After 15 years in the industry, I've sat through countless pitch meetings where some bright-eyed founder explains how their revolutionary AI will disrupt the sandwich-ordering process. Meanwhile, their actual problem is that they can't figure out how to store user preferences in a database. The real kicker? When they finally implement their neural network to predict topping preferences, it works worse than random chance. But hey, at least they can put "AI-powered" in their pitch deck!

Waterfall development starts with just wheels and slowly builds into a complete car, one piece at a time, in sequential order. Can't back up, can't change direction. Hope you spec'd the right vehicle. Agile takes a different route - start with a skateboard, then scooter, bicycle, quad bike, and finally a car. Each iteration is actually usable, unlike those lone wheels from waterfall. Then there's AI development: throw in Wacky Races' Mean Machine with three normal cars. Because nothing says "cutting edge technology" like randomly generating a monstrosity and hoping it doesn't kill anyone on the highway.

The modern developer's digital mirror match! GitHub Copilot is shaking hands with itself in the ultimate AI narcissism loop. When your code assistant both writes and reviews your code, it's basically just patting itself on the back. "Great job me, I approve of what I wrote!" This is peak programming efficiency—why waste time having humans review code when the robot can just high-five itself? The circle of AI life is complete. Next up: GitHub Copilot creating pull requests for problems it invented while reviewing its own code.