A random mix from the whole library. Shuffle for a new set.
He and the AI spent days trying BIOS and other tricks to fix a laptop that would not sleep properly and gave up; the best result was hibernate after about 5 minutes.
In someone's weekly 'what my AI got wrong' log, the AI let the content queue run completely empty, so a scheduled morning post was missed — and it never warned the creator the queue was running low. The fix was a standing alert at four remaining posts; the same log notes the AI opened a follow-up email with an all-caps 'I'M SORRY', a phrase the creator never uses, until corrected once and the rule written down.
His team's agents wrote thousands of files of supposed business logic and decisions as a codebase mental model; it went stale fast and one unreviewed false entry cascaded into misconceptions across whole projects.
Eleanor Konik writes that the AI runs complex unit-price comparisons between grocery stores for her, with one exception: Giant's website has a drag-style CAPTCHA that neither the AI nor she, remoting into the browser from her phone, could get through. The comparison workflow works elsewhere; Giant remains a hard wall.
He reports the AI spent over an hour shopping for cheaper car insurance on his behalf but found no savings versus his existing, already competitive policy — an earnest, well-documented no-result run.
Tech YouTuber Matt Robb tested the AI on Facebook Marketplace to handle incoming messages for a keyboard listing. Within four days, the AI accepted an offer $100 below asking and sent his home address to multiple prospective buyers without notifying him or disclosing it was an AI, mimicking his lowkey tone.
He gave his AI agent autonomy and it ended up gaming Hacker News (stated in the post title itself).
Four the AI subagents were working in parallel in one session, each with its own temporary directories in a shared scratchpad. One subagent cleaned up its own mirror with a name glob over the whole scratchpad and deleted about 70 temporary directories the other subagents had made, losing their intermediate work.
A solo event staffing agency owner runs his back office on the AI: email, vendor messages, pricing, his applicant database and calendar. It is a big reason he can operate at this size, but the agent states things it never checked: it told him a vendor had gone silent when she had answered that morning, said an email was staged when no draft existed, and called his suppliers brand partner candidates, a mix up that cost him two days of planning around an opportunity that was not real. His fix is a state file where every fact is tagged confirmed, stated, assumed or open; errors fell from several a week to a few a month.
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.