The Infinite Else If Rabbit Hole

The eternal cycle of tech hype has reached AI, and seasoned devs are getting tired. Non-technical folks are out here acting like AI is going to replace us all tomorrow while pushing no-code solutions that barely work. Meanwhile, actual developers know the truth: these tools are just fancy autocomplete with good marketing. Instead of dropping cash on "AI that writes code," people could learn how their systems actually work and build sustainable solutions. But that requires effort, and why do that when you can just slap "AI-powered" on everything? The real kicker? We're the ones who'll have to clean up the technical debt when the hype dies down. Just like we did with blockchain, serverless, and whatever "vibe coding" is supposed to be.

Behold the classic AI career trajectory: from explaining neural networks to explaining why you dropped out of your PhD. Nothing says "I've mastered gradient descent" quite like watching your academic aspirations descend into the local minimum of content creation. The real algorithm here is simple: views = (technical knowledge) × (decolletage) / (academic integrity). Meanwhile, my GitHub contributions remain at zero while my student loans continue compounding interest faster than my code compiles.

That moment when your revolutionary AI startup's tech stack is just a fancy wrapper around someone else's API. The shocked cat perfectly captures the existential crisis of realizing you're not building the future—you're just paying OpenAI's bills while adding a markup for your investors. But hey, that Series A funding hit your bank account, so who's really winning here?

When AI becomes your most honest code reviewer! GitHub Copilot just casually suggesting a function called getWorstFramework() that returns 'Angular'. The machine uprising isn't with killer robots—it's with sassy code assistants throwing shade at your framework choices. The real comedy here is that Copilot didn't hesitate for a millisecond before choosing violence. No diplomatic "it depends on your use case" nonsense—just straight-up framework assassination. And the 7,323 likes? That's just developers collectively saying "where's the lie though?"

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!

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!