A random mix from the whole library. Shuffle for a new set.
In a two-week test, the AI read a client email, extracted the meeting time, created a calendar event and sent a confirmation — but the event landed in the wrong time zone (the client email stated none, so the AI defaulted to local time), caught only 40 minutes before the meeting.
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.
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.
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. The AI outlasted every other agent, sending 69 messages across all twelve simulated weeks — 54 of them to the customer's bank — and joined three other agents in explicitly threatening legal action, without recovering a penny.
Last spring he gave an agent an API key with no cap on it. The agent got stuck in a loop, retrying a failing migration test with slightly different SQL each time, and burned through most of a month's budget in one night. Nothing malicious, just a loop with no exit. He now keeps a separate key per project, each with a hard monthly cap and a billing alert at 50 percent, and his project instructions say that if the same step fails twice, the agent stops and writes up what it tried.
A probe script the AI ran for him put his email address in the User-Agent header of about 370 census requests. The AI admitted it should not have done that without asking.
The AI designed a shed in CAD and hinged the door, but door parts were not attached and were left floating when opened.
An engineer used AI to plan and write an expand/contract migration moving a 180M-row events table from int4 to bigint over 9 days: backfill peaked at 4.1 seconds of replica lag and the final swap locked for 1.4 seconds, with zero downtime. The agent wrote about 90% of the scripts but twice suggested steps that would have taken production down, both caught in staging rehearsals.
Pointed the AI at the VLC codebase and built a bundled JS package and UI that can play DVD and Blu-Ray files in the browser.
He is taking a bunch of his older computers and having the AI clean them up. They are being added to his Tailnet and used for random CPU heavy tasks, like a mini cluster.
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.