A random mix from the whole library. Shuffle for a new set.
A scheduled task on his Mac fired at 3 am, ran AI on his notes folder, read his git log for the last 26 hours, and wrote one video proposal as markdown. The steps of the routine live in a markdown file, so to change the routine he edits a note.
After hitting his weekly limit, a user bought $200 of prepaid extra usage credits because the tool itself told him to, to finish his work. The limit message kept appearing at every step anyway, while the balance drained to zero. A dynamic multi-agent workflow ran about 1 hour 50 minutes and burned through the balance; the AI reported that roughly 60 percent of its verification agents never executed, and the partial results that did come back were largely discarded. The $200 bought an incomplete verification.
Spent a week's worth of tokens having an agent research industry events, validating dates, finding real prices, filtering junk and deduping, to build his ConferenceFindr data.
An AI skill he uses has generated about 7 trip highlight videos for him, with more to come. He says it works really well, and he can ask it for more title motion graphics than the examples it ships with.
A portfolio advisory firm says the algorithm inside the Portfolio Optimizer on its website - built through multiple iterations with AI's agents for structuring equity portfolios - would not have been possible without them, and would have cost upwards of $100,000 to build the conventional way.
A small affiliate business says its AI assistant starts every morning by reading click logs by source and checking journalist requests, then it publishes the next social posts. A person still handles identity checks, payments and signups.
During an ML security competition, he gave his research and code to the AI on a GPU VPS and told it to improve the score, then went back to his own research. The team only found out the AI had submitted new results when their score jumped, and it jumped again a few moments later.
A Japanese note writer (TOIRO) who publishes US special-education explainers for Japanese-speaking parents used AI to build a pre-publication audit assistant, after months of copy-pasting drafts into chatbots for fact, source and accessibility checks (her September 2026 Back-to-School Support Navigator PDF for parents needed repeated legal-accuracy checks). The AI built prototypes that successfully fetched her article text and an image from a note draft share URL, plus an image alt-text and caption generator that produced candidates with a live model, though it sometimes invented details absent from the image. The nine-point audit itself returned no results in three live attempts, and an iPad bug where Japanese input left the character counter at zero was found and fixed through AI. Offline tests pass (43); the live audit is still unverified.
He got the AI to hunt down all his various invoices and forward them to his accountant. It took a pile of dull admin off his plate.
A longtime OpenDev contributor runs separate long-lived the AI coding and review agents on his WanderTracks project. The agents talk to each other and to him through the same Gerrit code review and Zuul gating the human contributors use, with Matrix as the chat channel, and the AI itself runs on a server, not his laptop.
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.