A random mix from the whole library. Shuffle for a new set.
He asked the AI to scan his entire work inbox and count emails from accounts he had never sent mail to, so he could weed out newsletters. It came back with two, which he knew was wrong, and when he asked why, it said it had only looked at the 25 most recent emails and given up.
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.
His self hosted Bluesky PDS broke after bsky.app added a new CORS header. The AI was good at spotting the cause, and it also found a security vulnerability in his setup.
Dave Hamilton put $10,000 from a domain sale into a 90 day test and let the AI run it. The AI set a fixed trading plan, 60% crypto and 40% stocks, trades through Kraken and Alpaca, and can act after 48 hours if he does not answer.
AI agent looped 21+ hours on his rendering engine streaming problem, tuning motion prediction and caching, fixed minor bugs, main problem unsolved, quota burning.
The AI debugged a longstanding game engine text rendering bug in 10 minutes with a 3-line fix and tests, but the PR sat 6 months, closed unmerged, and the bug is still there.
Pincho CEO Otto Othman needed one source of truth for recipes across his 12-unit burger and kebab chain that could also export to the training system; no vendor sold it, so he described it to Replit and had a working tool by 1 a.m., about five hours of work. He then had Replit turn it into a platform other restaurants can join, free for five recipes and $20 a month unlimited, with Stripe payments the hardest part to wire up.
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.
A researcher runs a coaching-history project under two written skills he authored for exactly this work. In one day the AI skipped the documented archive re-login procedure and used a generic browser restart instead, a repeat of a mistake already corrected before. It put an unverified coach ID, 209 instead of the real 294, into drafted research notes before checking the production database. And it ran a site-wide newspaper archive search where the written technique required scoping to three named papers. Every error was against a procedure that already existed in writing.
Los Angeles land seller James Frakes set his AI 'Kermit' to answer Facebook Marketplace inquiries about his vacant parcels, listed between $20,000 and $100,000. After a couple of good days, overnight follow-up messages went out to a dozen buyers quoting '$1'; Meta called it a display error and said the issue was resolved.
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.