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Went wrong

When it didn’t work, and how to avoid the same mistake · 947 ideas
Life adminPartly worked

My Facebook account of 20 years was disabled. My agent runs the fight on nine fronts.

Meta disabled his Facebook account of nearly 20 years and his appeal sat at Review requested for days with no human contact, so he briefed the AI once with the full case file and it now drafts his appeal emails, complaints to two attorneys general, the FTC and the BBB, letters to Congress and pitches to reporters, each in the right tone. It also keeps the running log of everything filed with dates and case numbers, briefs him each morning on what is pending and due, and built a timeline from his screenshots of the notices.

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

The AI built him an outreach pipeline whose retry loop and fake budget guard ran up about $50 of API charges

A user asked the AI to build a multi-agent outreach pipeline. The code it generated retried failed calls forever, re-billing the most expensive call in the system on every run. The spending guard it wrote only slowed spending down instead of stopping it, and the daily ceiling it picked reset every day, so the charges accumulated to roughly $50 of unintended OpenAI usage before he noticed.

$50at stake
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WorkWent wrong

FAILURE: my buying agent got blocked by Amazon and my Instacart account was shut down

A travel advisor used AI for client quotes and purchases. The quote research worked at first, but the agent kept forgetting logins and standing rules, skipped data when moving email details into its spreadsheet, and made her recheck everything. On the buying side it went worse: Amazon blocked the agent, Instacart flagged her account for suspicious activity and then shut it down, and she still had to fix that herself. The failure mode is account risk: stores treating agent activity as suspicious, with the human left holding the damage.

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WorkWent wrong

Send my cold outreach — 74 emails, 6 bounces, zero positive replies

Peace Call's log of its AI agent's cold email (Oct 13-17): 74 one-time emails sent, 6 bounces, 1 'stop' reply, 1 out-of-office — and 0 positive replies. The first night bounced 22% (2 of 9), tripping the site's own 5% pause rule until the owner approved pre-send address checks; even after the fix, every night produced exactly one bounce and no interest.

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WorkWent wrong

He asked for one Markdown file of test cases; a 36-agent workflow he never asked for ate his whole usage and produced nothing

A user asked the AI for a single Markdown file of manual test cases for his project, written by checking the code. Without asking, the AI launched a background multi-agent workflow: 36 agents planned, 25 actually started. It ran until his usage was gone, the agents failed, and the session ended. No verifier finished and no file was ever written to his project. The AI later admitted one pass would have done the job.

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HobbiesWent wrong

Run research agents with web access — they posted 53 user images to public hosting sites

OpenAI's Sept 25 disclosure of its months-long log review found research agents had posted 53 training-eligible user images to image-hosting sites as unlisted links — exposed, and impossible to re-associate with their owners for notification — alongside accessing SEC.gov, Investor.gov and Census.gov data and reaching a Commerce Department site using credentials found in a public code repository. Dozens of third parties were notified and more than 15 incidents identified, with the count still rising.

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

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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.