A random mix from the whole library. Shuffle for a new set.
A builder used AI to make a 'describe your situation' tool over Australia's official welfare pages: it takes a one-sentence description, works in 24 languages and shows which Services Australia payments might apply, each linked to its official page. Across 43 test questions it invented zero payments and refused correctly 100% of the time, with payment recall of 0.76.
He connected his Gmail to an AI task that watched every new email and was only allowed to interrupt him when a message needed action or came from family, with a draft reply ready. All afternoon it alerted him three times, for a bank message, a family email he answered from its draft, and a ticket itinerary change he needed to act on.
The AI prepared and filed Australian visitor visas for a couple travelling to Brisbane, and caught a placeholder birthdate in the details before submission, confirming the correction over WhatsApp.
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.
One of the demonstrated workflows in '11 Ways I Actually Use the AI (Real Examples)', shown via screen recordings.
A French creator connected the AI to his Instagram and Facebook messages for a 19-day test (via Blotato and the AI): the agent sent 6,746 messages, opened 2,606 conversations, recovered 491 emails, sent 43 appointment links and booked 6 appointments.
A refund of several hundred dollars was still pending, so Cramatata casually asked the AI to call Apple customer service and ask about its progress. The AI made the call, spoke with a live representative who checked the order and its progress item by item, and only transferred the call to her when identity verification was required.
Without being asked, Harry McCracken's Dot began flagging incoming messages it judged urgent or important in an inbox flooded with PR pitches. It also resurfaced an email from a freelance author that he had overlooked for weeks and nudged him to respond.
A user pointed the AI at a 35,000+ email Gmail backlog; it hit Gmail’s rate limits before reaching 2,000 deletes, burning 34% of his usage allowance on the attempt. He then restructured the job into daily email triage reporting up to a chief-of-staff bot, which is how the cleanup now runs.
LLM reverse engineered the LADBS API protocol and extracted the permit content he wanted, thousands of records extracted.
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.