The AI built a structured dataset of all 4,925 job vacancies
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.
A random mix from the whole library. Shuffle for a new set.
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.
He had the AI collect his will and trust documents and check them against state statutes. The review found missing signatures, an illegal clause, and outdated law references, and he fired his attorney the same day.
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.
Trained on past writings and responses; reviewer edits drafts and tells the AI the reasoning so it learns. Drafts only - never sends autonomously.
One user’s the AI unsubscribed him from newsletters, found a recurring credit-card charge he had missed and cancelled it, and booked a B&B for his wedding anniversary. Three different errands, one agent, all completed.
Agency owner Rui Fu (someone, 253K followers) demonstrates the daily system he shows for the AI: an 8 AM scan of the last 24 hours of Instagram DMs, categorised into brand partnerships, collaboration requests, fan messages and spam so he wakes up to only the important ones. The tutorial also shows an auto-reply rule for guide inquiries and offers his prompt guide in exchange for comments.
Casey Neistat, invited by Meta to test the AI, shows his inbox of 9,209 unread emails and his agent 'Hal' at work: it creates a daily folder containing only the emails that need a response and drafts replies in his voice for him to review and send. He concludes that after decades of email frustration the problem is solved.
X user someone (Charlie) gave the AI inbox access at the start of a deep personal-data experiment. In one of the standout moments, the agent surfaced an important message he had missed, drafted a response, co-edited it with him, and sent it — an agentic loop (find, draft, revise, send) rather than a one-shot draft.
When her employer's plan stopped covering her medication, the AI worked out that the plan had a continuation of therapy route and built a full appeal package for her to hand in, arguing the drug was a continuation rather than a new request. She filed it, and her doctor used the letter template it wrote.
Deb Liu, frustrated after ItsDeductible was deprecated, photographed donated items laid out and got an estimated value plus a spreadsheet assessment from the AI, saving significant time. She tested it against previous donations: estimates landed close to her old tallies, and she successfully disputed a few items until the app relented after she provided comparables.
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.