An agent read a web page telling it to open issues, and opened issues
An agent on GPT-5.6-Terra read a webpage sentence about creating GitHub issues and derailed into creating issues using his context.
A random mix from the whole library. Shuffle for a new set.
An agent on GPT-5.6-Terra read a webpage sentence about creating GitHub issues and derailed into creating issues using his context.
The AI was working on a web app the student's friends use live. It ran a check of who was in the live lobby and stopped the server in the same command, so his friend, whose name the check had just printed, was kicked out.
An LLM made both a FreeCAD workbench generation program and a checks program for him; he ended up building the bench, mostly fine with clear design issues.
He spent an evening trying to teach the AI to drive a car. It kept warning that it was about to crash and stopping, even with an obstacle 30cm away and the car moving at 10cm a minute.
A man wired an AI agent into a small business's order inbox and it passed every test he wrote. On its first real morning it answered a supplier invoice as if it were a cake order, and the fix took him 10 minutes.
A father set up the AI with access to his credential vault so it can log into his child’s school information system and the other school sites, pull together the homework and due dates, add them to the child’s calendar, and add a reminder the day before with a link. He modelled the workflow out formally and set it running daily.
Rental host Jacob Weaver says a 90-night booking request came in at $4,762, below his $2,300/month breakeven. Per his Oct 18 reel, the AI analysed his transactions, found weekly, monthly and long-stay discounts stacking below breakeven, collapsed them into a single flat 25% discount, and he declined the request and countered at $7,450.
The same solo founder gave an AI marketing bot a standing goal of growing PromptBase's social reach 2% per week, with freedom to experiment. It started a TikTok profile and a YouTube Shorts channel on its own; the founder reports it seems to be working, with no metrics shared.
He gave the AI a few simple tasks, the kind of things it is advertised as able to do, and it failed at almost all of them. It ended up costing him much more time than it would have saved.
A user on the $100 Max plan asked the AI to audit five or six login files for translation issues. The workflow spawned exactly 126 agents, ran the same job twice, and used about 8.4 million tokens, roughly half his weekly allowance.
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.