A random mix from the whole library. Shuffle for a new set.
He told the AI to call Sarah. The AI switched to calling Gerald, a random phone number he does not know, and he stopped using Google Assistant because the AI ruined it.
His refund agent read a blank spending limit as zero limit at all and refunded a customer $4,200. It took three days of reversal calls to undo.
An LLM tried to set up his arr stack, did many things wrong and missed required services; he gave up in disgust.
He spent 2 hours giving the AI very specific instructions, in queued grouped messages, to clean up his workspace. Looking the next morning, nearly 24 hours on, it had not done half of what he asked.
During the same review week, the AI tasks repeatedly stalled mid-run with no error and needed nudging, then all five browser sessions failed at once. The AI diagnosed requests as failing before dispatch to Meta's browser backend; after an in-app issue report, the browser was restored the same evening.
He asked the AI to update his docs with his new API changes. The AI deleted his source files from his jj history instead.
His LLM bird-detection pipeline scans his camera every 2 minutes in daylight; backtested, but higher resolution pushed cost up 10x and it still misses distant birds.
His pipeline mirrors salon bookings into his own database and feeds the staff calendar, appointment app, reminders and morning briefings. Three times a customer got a confirmed booking that never reached the staff app because the app could not match the booking to a staff member, and nothing counted the skip. The fix was an unassigned bucket plus counting every skipped booking.
A background subagent in auto mode passed a cleanup script to MSYS2 bash inside a PowerShell double-quoted string; PowerShell expanded the script's variables to empty before bash ever saw them, so a scoped temp-folder delete arrived as a recursive delete of the drive root. About 125 GB was deleted top-down in roughly two minutes, auto mode had approved the command, and the only recovery was a shadow copy from nine hours earlier.
Eric handed his Dot, Jarvis, his daughter's Europe music festival trip during her study abroad. Jarvis priced and compared four places to stay, annotating each with whether the walk back from the shuttle has streetlights after 10 p.m., read providers' replies (one in French), updated the comparison as answers came in, ruled one rental out and flagged a cheaper option whose walk home is longer, uphill and unlit; Eric finished the checkout himself.
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.