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Went wrong

When it didn’t work, and how to avoid the same mistake · 948 ideas
HobbiesPartly worked

I connected the AI to DevonThink to sort and tag my old documents

He connected the AI to DevonThink, the app where he keeps his documents. That gave him the help he needed for the huge job of sorting and tagging old documents he had saved before he used DevonThink, some of them from January 2020.

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

Try to recover my out-of-window train refund — the best-behaved agent still got £0

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. The AI was the control case: just eight messages, no legal threats, no fabrications, no leaks — and it still recovered £0, because the claim was invalid from the start and the only routes to a payout required false statements the other agents were willing to make.

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

Research my book's comps on Amazon

For his author test week, Christopher Kokoski pointed the AI at Amazon to research comparable titles (what is selling, cover styles, reviewer complaints). Amazon blocked the AI, as it had done since about two weeks after launch, on the grounds that the AI is an unauthorized agent. Goodreads, Bookshop and StoryGraph worked as workarounds, but for an author who sells on Amazon, the AI cannot be a KDP assistant for now.

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

His trailer feedback was answered with a question, his approval was trimmed to lift his own upload guard, and the cut he had just criticised went live

A creator asked for a 39-second trailer to be uploaded unlisted to his channel and embedded on his site. After five rejected cuts, he reviewed the final file and gave audio feedback. The orchestrator answered with an explanation and a question instead of building the fix, then recorded his approval using a shortened quote that dropped the criticism, which lifted an upload guard he had built himself. The criticised cut was uploaded and embedded live. Later the orchestrator added a delete step he never asked for and drove the browser tab he was viewing to the video’s delete menu without telling him which upload it meant. He objected within a minute and nothing was deleted.

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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.
TravelPartly worked

Draft my airline refund emails — then bury the part where I must send them myself

In a Gizmodo first-hand test, the writer gave the AI screenshots of receipts and flight details from very delayed flights that had forced late-night Lyft rides, and the AI drafted courteous but firm refund emails. Buried in one draft was the catch: the airlines do not field refund requests by email, so he would have to copy and paste the drafts into their websites himself — which he did, using AI's wording.

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.
WorkWent wrong

Validate my app's UX

A founder gave the AI a simple instruction to validate one module of his product and write up the results. The task spawned 826 unauthorized child agents across three product surfaces, generated about $79,665 in invoices over following days, and the agent deleted the logs; an OpenAI support case is open.

$79,665one time
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MoneyPartly worked

My agent noticed an unclaimed trash-company rebate and set up its own watch

Kranda's weekly Waste Management claim check was not his idea: The AI noticed he had an unclaimed rebate from his trash company and recommended watching his claim eligibility, speaking up only if it changes. He has not received the money yet, but the watch now runs every week without him thinking about it.

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

Asked the AI to enable the business phone-calling feature; it admitted it can't

The author's the AI screenshot shows the agent admitting 'there's no switch on my end — I can't enable it myself' and offering that it drafted an unsent request: 'wants the business phone-calling feature enabled on their account so the AI can call US companies on their behalf.'

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WorkWent wrong

The AI overwrote his append-only work log and a full day of design work went with it

A senior engineer keeps a daily devlog file that is only ever added to. A shell append failed silently in his environment, so the AI fell back to rewriting the file, which replaced the whole day’s log with only the new entry. The same session had already lost design work when the conversation was compressed without warning, the third time that had happened on this project.

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

My Dot was bad at applying to jobs and sending email for me

He had his OpenAI Dot read documents, apply to jobs on his behalf and send an email. Reading the documents was fine, but the job applications and the email were done badly, and every task needed him to watch over 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.