A random mix from the whole library. Shuffle for a new set.
WIRED's Reece Rogers had the AI order breakfast from a bakery; the agent built the order correctly but quietly selected 'no tip.' Rogers ended up ordering in person — a small social-judgment failure that shows why checkout details need a human read before approval.
A developer let the AI write specs and code while the AI reviewed, all run through GitHub Actions and controlled from Telegram. Between September 21 and October 5 it merged 67 agent pull requests, but keeping the automation alive took 54 changes and 129 maintenance pull requests, and it burned through 3,000 monthly Actions minutes in about three and a half days without him noticing for two days. He went back to running the agents locally with himself making the final calls.
AI sessions and local LLMs OCR'd years of journals with multi-model averaging and a sanity check, producing free-text searchable journals plus photo backups, settled at 80 percent accuracy.
A Scientific American journalist spending a week with AI (Mark) and OpenAI's Dots (Sam) needed a moving truck. Her own search found no 10-foot trucks at the nearby U-Haul lot. Both agents found a slightly farther lot with availability, though only for 15-foot trucks, and Sam (Dots) booked one. At the lot next morning, a cashier mentioned 10-foot trucks were available for walk-ins, and they switched to the smaller truck. (Cross-agent event; the booking was executed by Dots.)
When an API call kept failing, his agent retried it by opening a new support ticket each time. By morning there were 47 identical tickets and a very confused support queue.
In Vox's two-week agent feature, one tester asked Instinct to show possible replies after it flagged a couple of emails. The agent sent the responses it had written instead of displaying them for review first.
Meta disabled his Facebook account of nearly 20 years and his appeal sat at Review requested for days with no human contact, so he briefed the AI once with the full case file and it now drafts his appeal emails, complaints to two attorneys general, the FTC and the BBB, letters to Congress and pitches to reporters, each in the right tone. It also keeps the running log of everything filed with dates and case numbers, briefs him each morning on what is pending and due, and built a timeline from his screenshots of the notices.
His agent fleet built a Rust project but crippled the machine filling the disk, forcing a cap of 5 workers and a dedicated resource monitor; the project was ended by rebuilding in Go.
He had to write a physical letter to his health savings account about a denied claim, and had been avoiding it since March. The AI wrote the letter, attached the invoice for the expense, and mailed the whole thing to the HSA. His only job was taking over for the $2.31 payment. Whether the claim was then paid is not stated in the comment.
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.
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.