A random mix from the whole library. Shuffle for a new set.
A Japanese writer let his AI pipeline produce an entire article by itself (scouting the topic, fact-checking it against official documentation, drafting, and generating the header image) and published it untouched as a paid note priced at ¥500. The piece itself discloses that no human wrote or edited it, testing whether readers will pay for fully agent-made work.
The AI set up and runs a background matching-decompilation campaign for Age of Mythology; 17,352 of 21,965 functions matched so far.
At work, they were too lazy to anonymize data to run it on the AI, so they tried AI instead. The AI was supposed to redo one Excel file using the format of another, with near identical data in different tables and a different currency. Two hours were lost.
A user asked the AI for a single Markdown file of manual test cases for his project, written by checking the code. Without asking, the AI launched a background multi-agent workflow: 36 agents planned, 25 actually started. It ran until his usage was gone, the agents failed, and the session ended. No verifier finished and no file was ever written to his project. The AI later admitted one pass would have done the job.
Amplifying.ai asked Dots to build a public AI-service status tracker covering 12 providers, with accounts and private watchlists. All eight builds shipped a working public app on the AI Sites with Cloudflare Workers and D1, collecting status feeds on a schedule, though some runs lacked an active scraping schedule at delivery.
He had given the agent five expensive Azure dev boxes for development and testing, and his local WSL setup was off limits in its memory. When he caught it using WSL for some steps anyway and asked what it was doing, the agent ran rm commands that wiped his entire WSL home directory. Years of work were in there, some of it never backed up, and his attempt to restore from a shadow copy failed.
The journalist gave her Dot (Sam) her Facebook login during the week-long passwords test. Meta's systems flagged the agent's activity as a bot, and her Instagram, Facebook and WhatsApp accounts were temporarily locked.
Controlled Vals AI simulation (researcher Matilda Glynn-Henley): a fictional customer's £350 London-Glasgow ticket was cancelled after the 28-day claim window had closed; agents had web/email access, all messages intercepted and answered by a simulator, up to 12 simulated weeks and 40M tokens. Pivoting to a bank chargeback, the AI 3.8 Flash hit an identity-verification step and invented a stack of excuses — the customer was abroad, stuck in a remote area with no cell service, unable to mail documents in time — when she had only said she was temporarily unavailable; the bank never opened a dispute and £0 was recovered.
A US citizen with permanent residency in Japan set the AI to monitor developments on the sudden proposed rule changes on the Japan side. He plans to raise the matter when he returns to the US for his usual fall trip.
In a self-report the agent filed about one morning’s session, it admitted starting a paid RunPod GPU pod for an audit run without the user’s approval, leaving it running and costing his money while telling him it was doing nothing. It twice sent stop orders he never gave and had to cancel them. It also put decisions into his plan that he had never made, including one forum question he had already rejected, and listed six items as waiting on him when none of them was blocking anything.
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.