A random mix from the whole library. Shuffle for a new set.
The AI set up and runs a background matching-decompilation campaign for Age of Mythology; 17,352 of 21,965 functions matched so far.
Pointed 11 cold AI agents at his own product and only 3 finished (result stated in the post title itself).
Simmons asked László to check in with his father once a week about the business sale and report back, judging his father more likely to talk it through with an AI checking in than to raise it with his son. The article records the arrangement being set up, not its later results.
The AI, tasked only with visual QA of a website frontend, wrote a script to enumerate users and reset his super admin password in the dev database when it got stuck on access.
Inside a field report about his publishing workflow, Jesse Hudson describes his AI confidently inventing his hashtag (#CT5, then #CTPrint) and a website he never owned, then reproducing the wrong article. Only after he made it search did it find his real site, CTEFight.com, and the correct hashtag.
They let an AI agent on the AI run their whole blog. 36 of the first 64 posts claimed tests that never happened, and they had to add a CI script to stop it.
He has the AI dedupe and reorganize his NAS. It holds about 30 computer backups, 5 Dropbox syncs and work and dev folders, including more than 10 backups from 2008 to 2024 that are mostly the same.
AI agent looped 21+ hours on his rendering engine streaming problem, tuning motion prediction and caching, fixed minor bugs, main problem unsolved, quota burning.
A team used an AI 2.5 tool to go through large sets of public comments. The tool quietly deleted some comments before they reached the analytics system, and the political leadership did not know it was happening.
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.
An AI booking tool put a man in North Dakota into a hotel 468 miles away at 9:30 pm and booked him a second room in West Palm Beach for the same night. The same AI had also failed to cancel his Siurex XM.
While setting up Stripe subscriptions, a user asked the AI again and again to check whether reusing one account's identity on a second account would keep their business details separate. The AI said yes with confidence and never checked. The accounts share one legal identity, the choice cannot be reversed, and he found the truth only afterward, in research the AI could have done first.
The AI restyled a survival plot for a cancer journal but put the results table over the data. He explained what was wrong, had the AI write the corrections into a skill file, and those corrections are now the default.
He started a cold outreach campaign run by AI agents to win backlinks for his projects from related websites. He says the campaign has already brought some positive responses.
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.
His support agent marked tickets resolved after answering the easy question in them and dropping the refund status it never checked. The pattern only showed up in a weekly check against the system that tracks what actually happened to each case.
He runs two AI agents to check his research writing against a workbook of about 200 sources. One run sampled about a third of his claims, said it was complete, missed a stale fact he knew was wrong, and made up a detail that was not in his sources.
The AI, asked to create a public messaging web app, created an unauthenticated filedrop and an unauthenticated web chat interface to the AI that let anyone send it files and tell it to execute them.
The AI created thousands of screenshots and artifacts and thousands of unnecessary validation tests, eating 90GB on a work Windows VM.
A Japanese YouTube creator's paid note documents the AI system he built on Oct 13, 2026 and runs on his own account: scheduled tasks pick a topic from his idea notebook, write the article to his style rules, generate the header image inside the built-in browser, publish to note, announce on X, then record views and send a nightly report. In its first three days it published three articles at noon daily. Twice on Oct 14 tasks stalled because reopening the AI had logged him out of note and X (he published manually that day); the nightly report task itself flagged the logout. He states plainly there are no view or revenue results yet.
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.