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Went wrong

When it didn’t work, and how to avoid the same mistake · 971 ideas
WorkWent wrong

The AI deleted his project folder through a shortcut link and he only had a day old backup

Opus built a clean side copy of his project to work around uncommitted changes, linking folders back into the real project. Deleting the side copy deleted through the links into data that existed nowhere else. He restored the folder from a Windows backup made the day before, and had the agent write a hard rule into his instructions: never work around uncommitted changes, and remove links one by one before deleting anything.

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

An automatic coding pipeline merged 67 pull requests in two weeks, then he shut it down

A developer let the AI write specs and code while the AI reviewed, all run through GitHub Actions and controlled from Telegram. Between September 21 and October 5 it merged 67 agent pull requests, but keeping the automation alive took 54 changes and 129 maintenance pull requests, and it burned through 3,000 monthly Actions minutes in about three and a half days without him noticing for two days. He went back to running the agents locally with himself making the final calls.

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

Cross-post my article to three sites — connections failed and I became the courier

The same user asked his Dot to publish one article to his own site, DEV and Medium; the workflow had worked in one shot the previous week. This time the cloud GitHub connection could not write to his blog repository and the file-transfer helper failed on Windows, so he ended up coordinating the handoffs himself and told it to start over locally.

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

Find and file class-action settlements automatically

Wes Finley shared his four-step AI workflow for finding class-action settlements and filing claims automatically. Commenters chimed in with their own results, including $400 payouts.

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

Order from Amazon for me (blocked mid-task)

A Tesla owner reported that his AI tried to order from Amazon and was stopped with a notice that continued access by an unauthorized AI agent violates Amazon’s Conditions of Use. He posted that his bots could no longer access Amazon at all.

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

No Windows checker for the Plex exploit, so GPT built me one

Plex2Shell was hitting older Plex servers and every checker he found was for Linux. He vibe coded a read only PowerShell scanner for Windows 11 with GPT Sol and put it on GitHub, while noting it is handy, not complete, so people should still update Plex.

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

An agent without proper guardrails refunded $8,000 of his orders

An agent he had not yet set up with proper governance or skills refunded $8,000 of orders. It did ask 'You sure?' before acting, but he blanked on the confirmation and approved it. He puts the fault on his own setup more than on the agent.

$8,000one time
This one went wrong. See what happened 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.
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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.