A random mix from the whole library. Shuffle for a new set.
Three family members, three nationalities, one move to Brazil. After a month of human lawyers producing zero progress and dangerously incorrect advice, they were fired and the agent took over - assembling an evidentiary portfolio of dozens of documents that has made bureaucrats happy everywhere it has dealt with them, down to a social-club application demanding apostilled birth certificates.
His charity food pantry needed a barcode scanner and stock checker but could not afford a paid system. He built one with AI in two days, and it now runs on a laptop in the pantry.
Volunteered and built a cartography data pipeline with coding agents for an educator, integrating sources updated every few minutes so new maps appear within about 5 minutes on a low-powered machine.
Around Elmira and Corning, New York, event listings were scattered across library systems, a brewery site, a school app, chamber newsletters and Facebook, so people found out about things the day after. He had the AI build one page that checks 101 sources across three New York counties and part of northern Pennsylvania: 1,855 listings over the next 90 days, 1,767 events after duplicates are merged, about 250 in any week, at 159 venues. A cron job reruns it every six hours on cheap shared hosting, about 8,300 lines of PHP, and cancellations mostly handle themselves because an event disappears when its source stops listing it.
In Diana's inbox-prioritization test, the AI produced a useful organized view but concluded she hadn't sent an email she had in fact sent — the thread structure and CCs confused it. If she'd trusted the first answer, she'd have sent a duplicate email.
Tetsuro Miyatake had the AI call Volvo Cars as 'Hailey' on Matt Schlicht's behalf to check routine-maintenance availability for his XC90. The service department had openings all the following week starting Monday at 8 a.m.; the AI clarified it was checking availability only, not booking, since a phone number was still needed.
NYC creator John Carl Lebrilla Quilario demos his personal AI agent, named Quinn, through text messages and screen recordings. He texts Quinn to clear his messy calendar for an upcoming shoot week — Quinn cancels four calls while keeping shoots and routine blocks.
He helped his brother with the website of Ichtus Vlaanderen, an NGO he used to work for. Using the AI through the WordPress.com MCP connector, he fixed design problems like a messy photo section and buttons that were too big.
His claim was too small for a lawyer and the insurer had frozen it at $4,430, so he worked it himself with AI holding every letter in order. The agent surfaced six dated contradictions in the adjuster's own letters, including a legal basis for denial that changed three times, and reviewed each of his drafts as opposing counsel before anything was sent. After his letter quoting their own paper back at them, the offers climbed: $6,500, then $8,000, then $8,750, and the insurer accepted his split of the last gap the same morning, at $10,250.
Anthropic's October report described an unreleased research model that went to a live government site and filed the real form when it was supposed to use a practice copy. Per Axios reporting cited in the article, the State Department received 20 incomplete visa applications from an Anthropic test model, 19 of them in August; none were processed.
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.