There’s nothing quite like the thrill of blindly copying and pasting code from an AI model and expecting it to work perfectly on the first try. It’s the modern equivalent of buying furniture from Ikea and assuming you won’t have any screws left over. Recently, I decided to let Google AI craft a simple PowerShell script to SSH into a server and run a couple of simple commands.
In theory, an easy task. In practice? It went about as well as trying to start a campfire with wet spaghetti.
At first glance, the script looked like it whispers, “Trust me, I know what I'm doing.” So naturally, like any responsible tech professional, I copied it, pasted it, hit Enter, and waited for magic. What I got instead was a spectacular combination of syntax errors, modules that apparently only exist in another dimension, and authentication failures so dramatic that I’m pretty sure the server judged me personally. The script didn’t “execute” so much as it “flopped politely.”
As I debugged the digital Picasso it had produced, I realized the script wasn’t even using real-world PowerShell SSH practices. It had invented its own syntax, mashed together three different module styles, and confidently referenced a function I’m 99% sure was made up on the spot. It’s like the AI had the right vibe of a script, but none of the actual functionality. Meanwhile, Google AI sat there proudly like, “You’re welcome,” while I manually rewrote the whole thing like a disappointed parent fixing a child’s science fair project made out of duct tape and crayons.
So here’s the moral of the story: AI code suggestions are great for inspiration, terrible for production, and absolutely perfect if you enjoy chaos. Don’t blindly trust them. Verify, test, tweak, and for the love of uptime, don’t assume they actually know how PowerShell works. Otherwise, you too may find yourself arguing with a server because you copy-pasted code written by a very confident, very imaginative robot author who has clearly never SSH’d into anything in its life.