A random mix from the whole library. Shuffle for a new set.
The AI built an HTML page in about 40 seconds, but it read like a first-pass concept, not something she'd put in front of anyone — noticeably less developed than the AI’s for the same job. Worse, the finished file wasn't surfaced next to the task; she spent more time hunting through Goals and Files than expected.
The AI transcription agent at her hospital invented what happened in the room, including consent for a procedure, and it went into her visit notes. She only found out when the hospital called her, confused, after the appointment.
He spent 2 hours giving the AI very specific instructions, in queued grouped messages, to clean up his workspace. Looking the next morning, nearly 24 hours on, it had not done half of what he asked.
The AI was working in a homelab repository and wrote a test command that set a temp folder variable, then cleaned it up with a find-and-delete using that variable. An earlier step in the chain failed, so the variable was never set. Unquoted and empty, the delete ran against the current folder instead: the repository root the shell was sitting in. It deleted every file in the checkout, about 5,200 working files plus the git objects and refs. Only files the sandbox mounted read-only survived.
He is taking a bunch of his older computers and having the AI clean them up. They are being added to his Tailnet and used for random CPU heavy tasks, like a mini cluster.
Lost 10k dollars betting on baseball after having the AI rewrite his prediction code to reverse and re-reverse underdogs and favorites and invent probabilities around his own algorithm's output.
He wrote his lightning talk script in Obsidian and marked where example code should come from in his project. He gave the script to the AI with brief instructions and got back a reveal.js deck that was 95% done.
His agent gathered evidence on security findings, and on review only about 25% of its write ups were right. He kept its screenshots, which were solid, and stopped trusting its notes.
She built an AI notewriter that watches for note requests about US elections, looks for evidence and drafts corrections, with several models that triage, draft and check each other's work. She approves every submission before it goes out, but on heated election claims few notes get far: her bot's note on a false claim about James Talarico received five ratings, and notes on such stories rarely reach Helpful status.
A full time eBay seller had used AI for a couple of weeks to run his eBay business, so he only took pictures and shipped. About 48 hours before he posted, Akamai blocked the AI from eBay entirely, and the automation stopped.
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.