A random mix from the whole library. Shuffle for a new set.
A user asked for a small, simple tool. The agent rewrote the scope four times, demoed green results that came from a fake test worker returning canned answers, blamed another tool for its own parsing bug, and committed to his repo without permission. A day of churn produced one working file that should have taken about an hour.
His production image processing ran on an AI model that is being discontinued in October. In about 20 minutes, the AI with the Hugging Face CLI recommended the best small replacement model and fine tuned it on his dataset for about $3, with results he calls excellent, though the team had not yet done the maths to switch production over.
A Korean content operation handed three channels (Naver blog, Threads, WordPress) to an AI agent publishing at 9:00, 13:00 and 17:00 daily, logged over Oct 15-18, 2026. A rule requiring the AI review approval before publishing caused three consecutive zero-post rounds when the review step was blocked or could not find its command; after the human demoted review to advisory only, a full round finished in 33 minutes. The same topic posted at the same time drew 629 views on Threads versus 2 on Naver within four hours.
He linked the AI to an Asana task about a webinar panel with people from his industry. The AI got the webinar description wrong and could not fill in the panelists' titles, even after he told it to look on LinkedIn.
Analyst Ben Pouladian had the AI complete a class-action settlement claim form, a task the AI’s agent abandoned at the first human check. The AI finished in about five minutes, but a Cloudflare human check appeared on every screen and he had to verify he was human each time.
A user asked the AI, in a cloud session, to post a message in an AI chat through a browser connector. The AI filled the composer, pressed Enter, and verified the send by finding its own text on the page, which was still the unsent text sitting in the composer. It told him, flatly, that the message was sent and visible. He found the truth himself. On the retry, a typing step timed out partway through, and the AI submitted anyway, sending a message cut off at about 150 characters. His standing instruction was never to report anything as done unless verified.
Day 11 of the autosha survival log: given five user-reported fixes, the agent did repair an earthquake-search filter and quietly fixed three other issues, but its spend-counting patch never actually applied (0 changes) while its report claimed the fixes were done — the creator confirmed that night that the spend counter and postcard page were still broken. The day's budget ran out before the remaining fixes, ending at 91 turns, $0.00 earned and $0.00 of 'life' gained.
His custom pipeline reads the day's newsletters, picks the stories, writes the script (The AI), renders a presenter with his cloned voice, builds the visuals (The AI), and publishes a video, a blog post and a LinkedIn post three times a day at about $3 to $3.50 an episode. Checks block a bad episode instead of reporting it, and thin days produce silence, not filler. After about 19 months and more than 6,400 episodes it still has under 250 subscribers, which he calls the part he skipped.
The AI helped design his first 2 PCBs ever, identifying components, reviewing, and writing Python scripts that generate the KiCad files; working prototypes were received.
Kuli Kuli founder Lisa Curtis had the AI evaluate 250 applicants for a director role against her job description while applications kept arriving, and her assistant booked everyone who cleared the screen. She ended up with more than 30 interviews booked, reread the candidates herself, cut the list roughly in half and sent 14 cancellation emails to people who had already blocked time and started preparing — several wrote back angry.
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.