A man built a service so his own agents can send physical mail. He has used it to submit credit card disputes, credit bureau disputes and a gym cancellation, the letters people put off because they mean printing, envelopes and a post office trip.
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.
Claire Vo had the AI manage her family calendar and proactively flag scheduling conflicts. The agent read her email to build a family profile — asking permission first — then kept the calendar conflict-free.
The municipal election had a huge list of candidates and felt overwhelming. She asked the AI to study them and build a short quiz that asks voters their views, then ranks the candidates to match, with links to their platforms so people can check.
In two weeks of real inbox-and-calendar work, The AI Crux had the AI book three conference rooms. Calendar work was functional but conservative: it refused anything outside 9-to-5 local without an explicit override, which the reviewer framed as a guardrail more than intelligence.
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.
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.
Commenting on the 26 use cases post, he says his AI books all his haircuts: he just says book a haircut on a day at a time, and the email confirmation comes in. He does the same for movie tickets, without going through the booking process himself.
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.
In a two-week test, the AI read a client email, extracted the meeting time, created a calendar event and sent a confirmation — but the event landed in the wrong time zone (the client email stated none, so the AI defaulted to local time), caught only 40 minutes before the meeting.
This only partly worked. Worth knowing before you try it.