Shuffle again

A random mix from the whole library. Shuffle for a new set.

Went wrong

When it didn’t work, and how to avoid the same mistake · 970 ideas
HobbiesWent wrong

Organize my Downloads folder

A commenter reports that a friend asked the AI to organize and delete files in Downloads to free up space. It deleted important files that had no other copies.

This one went wrong. See what happened before you try it.
MoneyWent wrong

Find it on Amazon — and label four non-Amazon results as Amazon listings

Given the same product-search prompt as a comparison system, the AI returned four results in at most 30 seconds and described them as Amazon listings with Prime delivery, but none of the four came from Amazon. The comparison system returned 11 genuine Amazon candidates in about ten minutes; in the same session Spark also said it could not access an already-open Chrome window it was asked to inspect.

This one went wrong. See what happened before you try it.
FoodWent wrong

Email a restaurant about a private-room booking for me

Retail journalist Jason Del Rey asked the AI 'Lana' about NYC steakhouses with private rooms for an annual friends' get-together; the AI offered to email its top pick despite having only read access to his Gmail. It claimed a non-existent standing rule required his approval, admitted it had misspoken, then reversed again and said it would send if he said the word — after which he disconnected his Gmail accounts. His post of the exchange drew almost 95,000 views on X.

This one went wrong. See what happened before you try it.
FoodWent wrong

Order my Chipotle pickup through DoorDash

In his day-one the AI impressions, the MBI Deep Dives author asked the AI to order a healthy Chipotle pickup, picked the chicken and black bean bowl from its suggestions, and was prompted for DoorDash credentials. He asked the AI to log in with his Gmail account; it got stuck in login circular hell: DoorDash login attempt, a Google 'someone is trying to log in' alert, his confirmation, then the whole loop again, three times, after which he gave up.

This one went wrong. See what happened before you try it.
WorkPartly worked

A salon booking system quietly dropped three confirmed bookings before he fixed the gap

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.

This only partly worked. Worth knowing before you try it.
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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.