A random mix from the whole library. Shuffle for a new set.
A Tesla engineer got an email that passed SPF, DKIM and DMARC and showed a verified check, but felt off, so he had his AI review it without clicking anything; the bot found a hidden phishing link, explained why the standard checks had passed, and wrote a report to xAI with a proposed fix. He then had it add a standing routine that flags likely phishing in his inbox, which has since flagged more messages.
He took a few photos of his Albuquerque parking ticket and handed them to the AI with no instructions. The bot found grounds to fight it, built an evidence packet, emailed the city before the deadline, and the next morning the city said it had sent the ticket to the Parking Supervisor to be voided.
He got the AI to build out a structured dataset of all 4,925 vacancies, with job titles, organisation, salary and location. He shared it in a spreadsheet for other people to play with.
The AI called car dealerships and plumbers to collect quotes for the user and scheduled a dentist appointment, the calls and booking done in about five minutes of the user's time.
Lixka, an accelerated nursing student at Mercy University, uploaded all six syllabi to her AI 'Mila'. Mila identified that Monday, September 28th was a 'triple-header' — two quizzes and a Pharm lab she hadn't noticed — then built a sustainable weekly rhythm around fixed classes, clinicals, and workouts, and asked permission before creating three tracked goals: quiz prep, reflection paper, and workouts/downtime.
Peter Yang ran a learn how I write skill in an AI app Duet. It read 33 of his sent emails, 89 Slack messages, 47 DMs and 11 docs, then saved a writing guide as a skill that Duet now uses to draft his email replies in his own style for him to check before sending.
A team used an AI 2.5 tool to go through large sets of public comments. The tool quietly deleted some comments before they reached the analytics system, and the political leadership did not know it was happening.
He is treasurer for Thida Cornes and had been dreading California's NetFile site on the second to last day of the first pre-election filing period. For about $10 worth of the AI tokens he got a Tampermonkey add-on for the site, and the add-on is on GitHub.
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.
Jack created a recurring daily website-check goal by chat in about a minute, then deleted it by chat. The Goals tab itself was slow to load (once 25 seconds, once stuck on placeholders).
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.