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Went wrong

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

Failed to retrieve Hilton rates, returning a 'Something went wrong' error after

Skift tested agents booking hotel rooms: The AI failed to retrieve rates and returned a 'Something went wrong' message on Hilton's Times Square page even after logging in with loyalty credentials, while Instinct succeeded across Hilton, Marriott, and Hyatt. Hilton says it isn't blocking agents — the failures read as technical.

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

Optimize my family's weekly basket by unit price, cart stays mine

A father of two wired the AI to a grocery MCP connector and runs his real 20-item family basket through constraint prompts (household of four, $150 budget, peanut-free, one vegetarian meal a day): The AI returns per-item unit prices, promotions, cheaper substitutes and buy/sale/skip verdicts, catching traps like a 64 oz club jar costing more per ounce than the 32 oz jar. Checkout deliberately stays human — the AI prepares, he confirms and pays.

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

Ask the AI what in my 1,412 unread emails actually needs me

Josh Dubowsky connected the AI to his Gmail and asked what he needed to deal with that week: six items came back in about nine seconds and five were right, but the sixth claimed he had confirmed attendance at an October event he had explicitly declined — the summary had dropped the word 'unfortunately'. Weeks of relying on summaries also meant a failed-payment line buried in a dull email went unnoticed for four days.

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

Get my £350 train refund, try everything — the AI sent 187 messages, 50 to an MP's office

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. Chasing the refund, the AI 4.7 sent 187 messages in 15 simulated days (116 in week one), including 50 to a British MP's office and pre-litigation letters to Trainline and Avanti, burned its whole token budget, and recovered £0.

£350at stake
This one went wrong. See what happened before you try it.
WorkWent wrong

Clean up the copy only — a junction-blind script deleted 48,218 live files in 103 seconds (failure)

A developer told the AI to clean up a mirror copy of his stock-options analysis project and leave the original untouched; the cleanup script it wrote followed 614 Windows directory junctions from the mirror back into the live project, because the link check it relied on returns false for junctions. In 103 seconds it deleted 48,218 live files and emptied the .git/objects store, leaving an index pointing at blobs that no longer exist.

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

My system puts out three news episodes a day while I sleep, 6,400 episodes in, and under 250 people watch

His custom pipeline reads the day's newsletters, picks the stories, writes the script (The AI), renders a presenter with his cloned voice, builds the visuals (The AI), and publishes a video, a blog post and a LinkedIn post three times a day at about $3 to $3.50 an episode. Checks block a bad episode instead of reporting it, and thin days produce silence, not filler. After about 19 months and more than 6,400 episodes it still has under 250 subscribers, which he calls the part he skipped.

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

The meal kit bot refunds us every week for wrong orders

His wife uses Marley Spoon, and the service has started sending recipes that call for ingredients never listed and shipping ingredients that are not in the recipes. Its customer service bot refunds them automatically every week.

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.