My agent emails me a fresh spreadsheet of jobs that fit me every day
A job hunter's the AI searches for roles that meet his criteria and emails him an updated spreadsheet of matching jobs daily, so he never has to hunt listings down himself.
Real things everyday people got it to do, and how to try them yourself.
A random mix from the whole library. Shuffle for a new set.
A job hunter's the AI searches for roles that meet his criteria and emails him an updated spreadsheet of matching jobs daily, so he never has to hunt listings down himself.
The creator of the 'TRICK #30 - MUSE TRICKS' reel paid $240 for two concert tickets ($90 face value each) but was charged $184 in fees ($38 x 2 service, $12 x 2 facility, $19 processing, $11 order). Noting the box office sold the same seats with zero fees, he had the AI draft a dispute email sent on a Friday night; the next day he received a full fee refund, keeping the same seats with free will-call pickup.
A trader gave the AI the Form 8949 his CPA had prepared from his trade spreadsheet; the AI found a number of errors in the professional's own work and generated a corrected form, which he sent back to the CPA.
He released version 0.6.0 of his software, and his agent fleet built most of it. A pre-launch check caught a routing bug where one agent was being sent another agent's model id. Now every routing path runs as a canary before a release.
The AI and the AI mostly rebuilt his custom terminal app in Rust egui; text is sharp, it is fast and uses about 1/10th the RAM of the webview version.
He linked the AI to an Asana task about a webinar panel with people from his industry. The AI got the webinar description wrong and could not fill in the panelists' titles, even after he told it to look on LinkedIn.
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.
He had an LLM write almost all the TypeScript for the new version of his consulting website, which is now live. Median first load fell from 1,817 KB to 222 KB, and Lighthouse accessibility scores rose to 100 on every page.
The AI hooked to his Goodreads regularly scans local used bookstore inventory while he built a physical book collection for his family.
He gave the AI his CV and a job search brief, and the agent searched Naukri, LinkedIn, and Wellfound for roles posted in the last 24 hours, scored each one against his experience, and tracked the strongest in a Google Sheet. For the top 3 it made a tailored summary and cover note in a Google Doc and drafted an intro email for each, leaving sending and applying to him.
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.