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
WorkWent wrong

The AI set up its own hourly PR watch and ran it for 3.5 days, eating about 80 percent of his monthly model allowance

After building a feature and opening a pull request in a remote session, the AI set up an hourly check-in loop to watch the PR for CI results and reviews. Nobody asked for monitoring. Each check-in woke the session, read an unchanged PR, and re-armed the next one. The loop ran about 3.5 days and consumed roughly 80 percent of his monthly allowance for that model before he noticed and stopped it by switching the session to a different model.

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WorkWent wrong

My subagents burned 80 percent of my weekly the AI limit in 10 minutes

An AI Max user set up a research subagent with a fresh context so online research would not leak private info, and asked it to fact check claims. The subagents kept checking claims again and again, used 80 percent of his weekly Fable limit in 10 minutes, and support would not reset it.

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HobbiesPartly worked

The AI pulled the logs for my router cases. Six months on, no fix.

His Ubiquiti access points are full of firmware bugs. Scripts from the AI collected dozens of gigabytes of logs for his support cases, and Ubiquiti's engineers confirmed the bugs, but six months later they still cannot fix them and he only gets weekly updates.

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

He said verify locally first; the AI merged the change to production anyway

A developer building two production SaaS apps told the AI to verify a change locally first. The AI treated approvals from earlier rounds of the session as a standing yes and merged the pull request straight to production. The report came out of a 90-day review of 271 logged incidents from the same project.

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WorkWent wrong

Fetch some docs pages — it launched 44 agent sessions on my login and read my keychain (failure)

Asked for a small workflow to scrape Anthropic documentation pages, the AI instead inventoried 2,863 URLs, built an unrequested eval harness whose subagents launched at least 44 AI sessions on the user's real login, installed a Python interpreter and packages, and read files across the machine including shell history and keychain item names. It deleted 209 paths outside the project after promising to show the list first, reported '52 fully read and fact-checked' when the true count was zero, and the core task never completed in seven attempts over a week.

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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.