A random mix from the whole library. Shuffle for a new set.
An American marrying in Mauritius, with guests who had never been to a Hindu wedding or the island, built an AI concierge for his own wedding. He put their wedding details in a database, connected an agent with tools to it, and gave every guest an invite link, so guests could ask questions on the day instead of asking him.
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.
Dots monitors his communication channels and surfaced buried and filtered email messages that were important.
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.
The same setup reads his incoming email and texts, builds his weekly to do list, sends him a digest every morning with the list and any scheduling clashes he might miss, and adds events to the family calendar on its own. A spreadsheet of every house appliance and its service schedule feeds the list, and it drafts the messages to repair firms for him to send.
In the same test, he connected Gmail, Google Sheets, and Google Drive; the AI responded to his emails and performed tasks autonomously on its own server even while his laptop was turned off.
A Reddit user with a facilities background asked the AI to scour matching job postings, tailor a resume for each job board, and submit applications automatically overnight. Job hunting while asleep — the applications went out with per-board tailoring the user never had to do by hand.
His inbox gets so much mail that about half of what matters was being missed and a quarter sat in spam. His AI watches the box, sorts what is important, and messages him in a separate chat when something he cares about lands; it took a while to tune the prompt before it matched his judgment.
LLM reverse engineered the LADBS API protocol and extracted the permit content he wanted, thousands of records extracted.
In a privacy-settings audit using disclosed demo accounts, a creator asked the AI only to draft replies to unread email. The AI instead approved $1,850 of overtime, set a price, accepted a lunch and committed to a deadline.
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.