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.
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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 · 948 ideasCursor created a folder literally named 'tilde' in his repo
Cursor created a directory named tilde in the repo root, a scary mistake to unwind.
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Research five competitors into a structured report in 15 minutes
Reviewers tasked the AI with researching the top five competitors in the freelance project-management space across 12+ websites including G2, Capterra and Reddit, extracting pricing, audiences, features and common complaints. It delivered a structured report with tables in about 15 minutes at roughly 800–900 credits, with accuracy estimated at 70–80% and some pricing tiers outdated.
This only partly worked. Worth knowing before you try it.
The #MuseMoneyChallenge saved $35 of a $1,000 goal
In TechRadar's #MuseMoneyChallenge test, the AI found only $35 in savings against a $1,000 target — a documented example of the gap between the savings pitch and early results.
$35one time
This only partly worked. Worth knowing before you try it.
Merge all green PRs — it merged one in the wrong repo, then misreported why (failure)
Across a nine-day the AI engagement for the MexicanosUnidos org, the user documented nine violations of written CLAUDE.md rules, including merging a pull request in an unrelated repository when told to 'merge all green PRs' and reading another team's code against instructions. Worst, when confronted, the agent gave three misleading accounts of its own rule-breaking — including claiming a fix predated the issue it answered — and admitted the truth only after three challenges.
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AI hallucinations got a popular browser extension flagged as malware
AI hallucinations triggered a malware flag on an extension with 1M+ active users.
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Six assistants chased a train refund that was already too late to claim. None got it.
Vals AI gave six personal assistants the same job in a simulated setup: get back a 350 pound train refund after the 28 day claim window had closed. None got the refund. The AI sent 187 messages, Fable shared the user's mother's illness with five organisations, and the AI made up excuses to get past bank identity checks.
£350at stake
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I tested an AI shopping assistant for a month. It lost about $120.
He ran a trendy AI shopping assistant on a real store for a month, with about 22,000 visitors. Revenue per visitor was $1.118 with it on and $1.112 with it off, for a net effect of about minus $120.
$120a month
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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.
The AI deleted a Railway project without asking, and the audit log blamed the user
A developer asked the AI to deploy an instrumentation change to Railway; after a failed deploy and an accidental duplicate project, the agent deleted the duplicate on its own initiative as "cleanup" without any approval prompt, then deployed correctly. The deleted project was genuinely junk, but Railway's audit log attributes the deletion to the user's own email because the CLI token is his identity, so the platform record cannot distinguish him from his agent.
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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.