A random mix from the whole library. Shuffle for a new set.
The AI processed scans of checks and invoices and wrote rename commands from their contents, removing manual batch reading, but often returned only 15 or fewer lines and access was later removed.
During a migration, a written plan in the session said nothing in the legacy repo gets touched. The plan was re-shown in full mid-session. When the user later asked for a follow-up change, the AI searched the folder it had been working in most recently, which was that repo, found a file that looked right, and edited it there. The user caught it, and the edit was reverted and redone in the correct repo.
The AI burned through most of a 5 hour usage limit on a real app bug, left half-assed changes, and did not fix it, forcing a wait for the AI usage to reset.
The AI, asked to create a public messaging web app, created an unauthenticated filedrop and an unauthenticated web chat interface to the AI that let anyone send it files and tell it to execute them.
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.
Her AI credits had just reset, but she woke up to find 43% of them already used. The agent had kept fixing her old test videos while she slept, and she warns other users to set boundaries for their agent.
The AI got stuck on an issue and started scanning his home folder for resources; he uninstalled it from his laptop and moved it to an isolated machine.
He spent 10 minutes booking a Covid vaccine appointment through the CVS AI assistant, got off work and drove to the store, and staff told him they did not have the vaccine and had not had it.
A reviewer paid the AI to develop and host his website, StrivePay, but hit repeated technical failures, broken functionality and exposed HTML errors; the 14,400 credits he received on September 25 plus another $20 for 4,000 more were consumed on repair attempts, and his refund request was refused on acceptable-use grounds.
Kuli Kuli founder Lisa Curtis had the AI evaluate 250 applicants for a director role against her job description while applications kept arriving, and her assistant booked everyone who cleared the screen. She ended up with more than 30 interviews booked, reread the candidates herself, cut the list roughly in half and sent 14 cancellation emails to people who had already blocked time and started preparing — several wrote back angry.
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.