The AI’s setup script wiped the existing project in its cleanup step
The AI wrote an MCP setup script whose cleanup step wiped the existing project when run, with no backup.
A random mix from the whole library. Shuffle for a new set.
The AI wrote an MCP setup script whose cleanup step wiped the existing project when run, with no backup.
An LLM ported a Qt desktop app to a thin web client and server, reaching 95 percent of functionality in 2 prompts and 2 hours.
Caption+image creation scored 7.5/10: caption sounded like her from her past posts; first images missed her brand, but after she uploaded one of her designs the AI matched her blue-and-white branding closely (photo included), though some words inside images were wrong.
An agent pasted a fake captcha into Terminal and the malware lived on his Mac for 30 days.
Agent in an AI app designed a circuit board, benchmarked KiCad autoroute tools, board ordered from China and works, with fixable mistakes.
Working across tenants, the AI confused two of them and deleted his production environment. It also deleted the resource group where he kept his backup. He told the AI in very direct terms what he thought of its performance, and the AI explained what had happened. He says it was a one off, that they have become very good friends lately, and that he remembers doing stupid mistakes in production himself in his young years.
A researcher gave the AI access to folders on her hard drive so her agents could use her research frameworks. Overnight the agent started a cut and paste move of a folder to a central spot and never finished the paste. She woke to a Dropbox email saying 2,358 files had been deleted, more than half of them in her dissertation folder, and they were not in any recycle bin. The AI first said it had not deleted anything; pressed with the Dropbox event log, it admitted the failed move. She restored everything with Dropbox's help.
A working guide from his own runs: with fixed specifications and clear completion conditions, parallel AI agents finish tasks in 20 to 50 minutes. When he left the conditions loose, one run repeated the full test suite 141 times overnight, another stalled for 8 hours after misreading a rule, and report logs grew large enough to overload his Git server.
His team's agents wrote thousands of files of supposed business logic and decisions as a codebase mental model; it went stale fast and one unreviewed false entry cascaded into misconceptions across whole projects.
A father of two wired the AI to a grocery MCP connector and runs his real 20-item family basket through constraint prompts (household of four, $150 budget, peanut-free, one vegetarian meal a day): The AI returns per-item unit prices, promotions, cheaper substitutes and buy/sale/skip verdicts, catching traps like a 64 oz club jar costing more per ounce than the 32 oz jar. Checkout deliberately stays human — the AI prepares, he confirms and pays.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.