Biggest Self Report

Ah yes, the classic tech startup delusion in its natural habitat! Nothing says "I'm qualified to be CTO" like casually proposing to replicate a $500 billion AI company with a budget that wouldn't even cover their coffee expenses. It's the tech equivalent of saying "I could totally beat Usain Bolt if I just had some new sneakers." Sure buddy, OpenAI only has thousands of PhDs, supercomputers, and decades of research—but you've got a MacBook Pro and an energy drink. Your investors will definitely be impressed when you deliver ChatGPT at home: "Hello wrold, how can I halp you toady?"

Content Me, trying to write code while sales is hyping up their latest deal

The modern developer's version control system: ChatGPT. Sure, we've evolved from USB sticks to Google Drive, but some of us have ascended to a higher plane of chaotic development—keeping our precious code snippets in chat history with an AI. Nothing says "senior developer with impeccable practices" quite like frantically scrolling through your conversation history at 2 PM during a production outage trying to find that one clever function you wrote last month. Git who? Never heard of her.

Remember when we thought we'd train AI to help us write code? Top panel: cute little AI cub learning from the wise software engineer master. Bottom panel: six months later, that same AI has evolved into a towering beast while we're still sitting there with our legacy code knowledge from 2019. The career progression timeline has been dramatically compressed. Took me 15 years to become a tech lead. Took AI about 15 minutes to make half my StackOverflow contributions irrelevant. But hey, at least I still know how to exit Vim. For now.

Asking how to check LLM code quality without being an expert is like asking how to check if your parachute works without jumping out of a plane. The irony is delicious - you're using an LLM to ask how to evaluate LLM-generated code. It's the digital equivalent of asking a toddler if they think they should have more candy. The answer is always "yes" and always suspiciously in their favor.

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!