Chat GPT Writing Code Comments Like

Nothing says "we love our users" like dropping a free AI feature that immediately sets fire to your data center. Those poor GPUs, running at 110°C, fans screaming like they're auditioning for a metal band. Meanwhile, DevOps is frantically calculating the electricity bill while the marketing team high-fives over user engagement metrics. The best part? The feature probably could've been implemented with a simple if-statement, but hey—gotta justify those VC millions somehow!

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!

The initial joy of getting 10,000 lines of AI-generated code in minutes quickly transforms into the crushing reality of what comes next. That smiling face knows what's coming - endless refactoring sessions, security vulnerability patches, and explaining to management why that "instant solution" needs two years of cleanup. It's the coding equivalent of ordering fast food and then dealing with indigestion for days. The technical debt interest rate is brutal, and Hide-the-Pain Harold knows it!

That's not machine learning. That's just a terminal spewing errors while someone went to lunch. Classic misdirection to keep management from asking why your project is six weeks behind. The screen full of red text means either your code is spectacularly broken or you're training the next ChatGPT. Either way, nobody's touching that keyboard until the "learning" is complete.

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.

Putting on glasses to transform from "LLM Engineer" to "Knows about openai, anthropic and google-genai package" is peak tech industry smoke and mirrors. It's like calling yourself a "Cloud Architect" because you once deployed a WordPress site to AWS. The glasses don't add intelligence—they just help you see through the BS of your own job title. Next time someone introduces themselves as an "LLM Engineer," ask them if they can actually explain a transformer architecture or if they just know how to copy-paste API keys.