Quicker, But What Do We Sacrifice?

Forget complex algorithms! This Python developer decided to outsource the "is odd number" check to ChatGPT. Just casually burning through API credits to determine if a number has a remainder when divided by 2. The function makes a full API call, parses the response, and checks if the answer contains "yes" - all to replace a simple return number % 2 != 0 . Peak computational efficiency! 💸

Oh snap! The AI bubble just got popped harder than my dreams of writing bug-free code on the first try! 🎯 After years of hype cycles and buzzword bingo, we've reached that beautiful moment of clarity where someone finally said the quiet part out loud. All those fancy "AI solutions" your boss keeps pushing? Just regular algorithms wearing expensive suits and practicing elevator pitches! It's like when you rename your "if-else" function to "DecisionIntelligenceEngine™" and suddenly your startup is worth $10 million. Pure magic! ✨

Ah yes, the mythical 10,000-lines-of-code-per-day developer. Next, he'll tell us his code compiles on the first try and his documentation is always up to date. Anyone who's spent more than a week coding knows that quantity and quality have an inverse relationship that not even AI can fix. The real achievement isn't writing 10k lines - it's deleting 9,950 unnecessary ones and still having working software.

When your neural network sees a GPU and a 3D loss function plot trying to solve what your brain does naturally: "Look what they need to mimic a fraction of our power." Hardware engineers sweating as they build increasingly monstrous GPUs just to calculate gradients, while the human brain sitting there using 20 watts and somehow understanding why that cat meme is funny. The ultimate flex of biological computing.

Ah yes, the pinnacle of modern debugging: when your code fails, just ask ChatGPT to fix it. Who needs Stack Overflow anymore when you can just wrap your entire codebase in a try-catch and let AI handle the rest? Next step: AI that writes the bugs for you so the other AI can fix them. The circle of life in silicon.

When your resume is just a list of tech companies that imploded right after you left. Nothing suspicious here, folks. Just a trail of digital catastrophes following this person like a shadow. Netflix sports streaming that doesn't exist yet, CrowdStrike's Windows update disaster, Google's Gemini historical figure fiasco, Silicon Valley Bank collapse, and FTX's crypto meltdown. Hiring managers will definitely not notice this pattern of working at companies right before they face existential crises. Solid career strategy - join, collect paycheck, abandon ship, repeat.