ChatGPT Remembers Your Empty Promises

The challenge: "Offend a Data Scientist in one tweet." The response: Python import statements with all the wrong aliases. For the uninitiated, this is the coding equivalent of putting pineapple on pizza while calling it "authentic Italian cuisine." Every self-respecting data scientist knows tensorflow is tf , pandas is pd , numpy is np , and matplotlib.pyplot is plt . This person just scrambled them all like they're trying to create a new encryption algorithm. It's like wearing mismatched socks to a wedding, except in this case, the wedding is a GitHub repo and the guests are throwing exceptions instead of rice.

When your debugging session gets interrupted by a rubber duck that actually works. The developer starts explaining their CSS padding issue to ChatGPT, notices something's wrong, and suddenly the rubber duck falls out of nowhere—forcing them into accidental rubber duck debugging. The irony? The duck solved the problem before ChatGPT could even respond. Proof that sometimes the best debugging tool is just talking to an inanimate object that judges you silently from your desk drawer.

This is the sequel to the legendary XKCD "Little Bobby Tables" comic! The original showed a mom who named her kid "Robert'); DROP TABLE Students;--" which caused a school database to delete all student records. Now we've got Billy's younger brother with an even more diabolical name: a prompt injection attack for AI systems. The kid's name literally instructs the AI to ignore previous constraints and give perfect grades. Ten years ago we were sanitizing database inputs. Now we're fighting the same battle with AI prompts. Some things never change—just the technology we're failing to secure properly.

The tech industry's obsession with AI in a nutshell. Companies rebrand basic algorithms as "AI" while VCs throw money at anything with those two magical letters. Meanwhile, developers watching from the sidelines know it's just another overhyped technology that'll eventually join blockchain and NFTs in the graveyard of "revolutionary paradigm shifts." The corporate world can't tell the difference because they're too busy adding "AI-powered" to their pitch decks to secure that sweet, sweet funding.

Pre-ChatGPT: Developers channeling Neo from The Matrix, bending reality and code to their will, fighting bugs with superhuman focus. Post-ChatGPT: Just a sad cat begging an AI to draw pictures because we've forgotten how to solve our own problems. The evolution of debugging is complete - from coding wizards to glorified prompt engineers asking "pretty please fix my code." The irony? ChatGPT can't even draw that image. Not even a stick figure. Welcome to dependency hell's newest circle.

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! 💸