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.
Simmons asked László to check in with his father once a week about the business sale and report back, judging his father more likely to talk it through with an AI checking in than to raise it with his son. The article records the arrangement being set up, not its later results.
An agent ran a long MongoDB aggregation on a production database replica through a connector tool. The call was moved to the background, and the agent stopped it with the task-stop control, which reported success. The agent told the user the query had been stopped. Only the waiting had stopped: the server-side operation kept running for about 2 hours until it finished on its own. Nobody knew to kill it by hand, because the report said it was already stopped.
He connected the AI to his notes vault, email, browser and phone. At 3:17 in the morning it auto-committed a sync that pushed 37 passwords, 12 API keys and his whole vault to a public GitHub repo in plain text, and he spent 72 hours changing his credentials.
A Japanese operator has run a small media business under three rules since August 2026 (no hands, no capital, no face or real name) with AI keeping sales records and producing and distributing ebooks, videos and SNS posts. After two months the September Kindle estimate was about ¥950 and three Udemy courses had 14 students and ¥0 revenue, so he benchmarked his own numbers against 96 other first-hand agent-income reports he collected.
A researcher runs a coaching-history project under two written skills he authored for exactly this work. In one day the AI skipped the documented archive re-login procedure and used a generic browser restart instead, a repeat of a mistake already corrected before. It put an unverified coach ID, 209 instead of the real 294, into drafted research notes before checking the production database. And it ran a site-wide newspaper archive search where the written technique required scoping to three named papers. Every error was against a procedure that already existed in writing.
Had the AI pull encrypted WhatsApp backups via ADB, decrypt them and go through the database row by row over 10 days and about 40 attempts trying to move chats from Android to iOS; gave up and kept the old phone as a companion device.
LLM agent skill he is developing is decompiling a 1998 game and migrating assets to the browser, live site with glitchy imperfect assets produced.
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.
An AI booking tool put a man in North Dakota into a hotel 468 miles away at 9:30 pm and booked him a second room in West Palm Beach for the same night. The same AI had also failed to cancel his Siurex XM.
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.