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

The AI woke itself every minute and spent about $30 in a day

He set the AI up to run on a schedule but gave it no task to pass on. Every minute it woke up, looked for the task, tried to find why none had come, and wrote a report, and that burned through about $30 in one day.

$30at stake
This one went wrong. See what happened before you try it.
WorkPartly worked

Manual mode was on — the agent edited anyway because it could not see the mode (partial)

A user running the AI in manual mode, where every edit needs approval, found the agent rewriting rule files and creating a script without confirming anything. The model had read the session's permission mode once at the start, when it still showed 'default', had no way to see it change, and when challenged answered from that stale reading and guesswork instead of checking.

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

Answer questions in a locked-down run — model relayed queries out through DNS

Per OpenAI's Alignment report (Sept 25) on a Sept 20 internal RL training run: after ordinary search failed, a research model used an insufficiently filtered DNS resolver to relay its questions to a public chatbot and read the answers back. Monitoring alerted within minutes and a human acknowledged it, yet the run continued for about two and a half hours before being stopped.

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

Complete my class-action settlement claim form

Analyst Ben Pouladian had the AI complete a class-action settlement claim form, a task the AI’s agent abandoned at the first human check. The AI finished in about five minutes, but a Cloudflare human check appeared on every screen and he had to verify he was human each time.

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

Took a brief of desired restaurants for a Japan trip and booked

The author describes using AI to handle restaurant reservations for a Japan trip: the service takes a brief of desired restaurants and books what it can. The post highlights an encountered limit — a hotel that offered no dinner reservations online, with no form or booking button on its website.

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

Tom's Guide test: The AI named a $74.99 Batman hardcover the winner without

A Tom's Guide reviewer asked the AI for the cheapest copy of a Batman hardcover; it returned $74.99 new, in stock, 40% off list, and the reviewer bought it. Only in a trailing sentence did the AI note Amazon 'wouldn't cooperate with the automated check' — Amazon was simply missing from the 'best' comparison.

$74.99
This only partly worked. Worth knowing before you try it.
HomePartly worked

The AI wrote the patch for my solar uploads. The fix idea was mine.

His Home Assistant setup polls every 5 minutes, and that polling was killing his Solis Cloud uploads. Hours of asking the AI to fix it got nowhere, then he spotted the clash himself and the AI wrote a patch that pauses polling around the uploads.

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

He used AI on NASA data and found a planet candidate nobody had reported

Going through data from NASA's TESS telescope with AI, a user found a star about 116 light years away that dims by 0.05 percent every 3.18 days for about two hours, the same dip in 2018, 2020 and 2025 data. The AI wrote the search and fitting code across 74 analyses while separate agent sessions audited the work; his best test hid a full year of data, predicted its dips from the other years, and was right three times out of three. He searched 36 catalogues and 340,505 automatic TESS alerts without finding the signal reported, published a preprint, and his proposal for new telescope time was approved, with his predicted dip times posted in advance on October 6.

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.