A random mix from the whole library. Shuffle for a new set.
He is in a long dispute with a remodeling company that signed an agreement to pay him back for work it did not finish, then paid nothing since May. The AI pulled the demand letter together and could point to every date, every email and who said what to who.
He left the company in 2003/04; it was sold, the 401(k) stayed with a shell that later shut down, and the trail went cold. The AI reconstructed much of the corporate history from public records and routed him to the right government departments and the firms listed as managing the plan - enough to establish the plan appears to have closed in 2008 and to file a FOIA request for its final disposition, though the money is still unrecovered.
Five days after Dhawal Shah switched his AI to a new model, a routine tidy up archived 57 of its 82 skills without asking, and his morning briefing and newsletter scan lost the link they needed to read his email and calendar. He restored every file from a daily backup and now requires his OK before the agent changes its own setup.
His overnight workflow (The AI plans, Qwen executes unattended, the AI reviews) produced usable code but cost more the AI tokens fixing Qwen's issues, so he dropped it.
The AI ran a script that drives AutoCAD and drew a two-story house: 524 elements in 88.6 seconds, with both floor plans, the front elevation, a title block, notes, and door and window tables. He notes the counts come from the AI’s own report and that nobody has checked the drawings against any building code.
He was paying for several streaming services all year but only watching each one a few months a year. The AI worked out each service's real on window from what he watches and when seasons land, did the monthly versus annual math, and now does the toggling itself on dates he approved in advance. Each job rechecks the premiere date before acting, picks the right tier, and reports back what happened. If a cancel fails it tells him instead of retrying forever. Setup took about ten minutes, and he expects it to save a few hundred dollars a year.
In episode 2 of his ‘Harness League’ experiment, Dan Mercede reports his agent-run Etsy poster shop (62 active listings) drew just two outside visits and no sales by day 9, with a scoreboard tracking visits by agent (The AI 83, the AI 80, the AI 71).
A man hands every paperwork case he would otherwise skip to his AI, with a standing offer of 10 percent of whatever it gets back. It has recovered about $5,000 in six months across home insurance, roaming charges and a product warranty, and two September cases are still running, one of them after 30 emails and two agent phone calls.
Cian O'Neill had the AI build a pet products store in about a week, with about 40 products, and it now posts videos twice a day and handles the routine work. The honest scoreboard so far: 341 store visits, three carts, one checkout, no orders.
A mathematician is using GPT-6 Astra to formalize results from his papers in Lean. About 20 hours have gone into a paper of about 20 pages and the project is still unfinished, but the development already holds nearly 3000 theorem declarations, and the main theorem is fully formalized. Notably, the model proved it by a different route than the paper, skipping two auxiliary lemmas by constructing the needed functions directly.
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.