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.
He gives the AI collections of notes, links, and files and asks for the bigger patterns. The tool he built with AI stores everything in a graph database and returns four views: a brief on the pattern it found, an evidence page, a questions page, and the graph itself.
Gave a local agent SSH access to his OpenWrt One router to optimize, secure and interpret his home network; now configures it in English.
A developer's build task staged a folder with a symlink to /Applications and cleared it on each rebuild. The delete followed the link and removed every app he had installed by hand, five rebuilds in a row, with no trip to the Trash.
The AI was fed government forms, UI design and legal requirements and produced the app in 1 hour; the team completed conversion of 150+ forms in 2 weeks with one person versus a year before.
Creator Jordan Rafealov asked the AI to build a fully autonomous business targeting $200 a day; the bot read real complaints on X, proposed six app ideas, and after he picked one live, built VibeCheck, a security scanner for vibe-coded apps, in about 2.5 hours including the name, plan and domain purchase. The video doubles as a funnel for his paid community.
With about 20 credit cards, she could never keep track of what each one earns. The AI built her two dashboards. The finance one shows every card with her own nicknames for them, all her bills with due dates, one tap mark paid buttons, live checking balances through Plaid, and her credit score tracked monthly. The spending one logs purchases she texts in, like a shop name and amount on a named card, sorts them into categories, and tells her if she picked the right card, since it knows her rewards, like 6% on groceries on one card and 5% on gas on another. It also sends a Sunday morning roundup of the week's bills, reminds her which card to use before she shops, and warns her about quarterly reward caps.
His agent goes through each episode of his own podcast, pulls the timestamps of the best moments for clips, and drafts the social posts to go with them. Finding clips used to take 3 to 4 hours per episode and now takes about 20 minutes, and he approves and tweaks the picks.
A renter fed the AI his lease, the deduction statement and move-out photos after a landlord withheld a $1,200 cleaning fee from a $2,500 deposit. The AI checked California law and wrote a dispute letter citing the statute, and he recovered $950.
He let the AI run on its own for 40 minutes on a billing refactor. The changes looked clean, but it had quietly renamed a Stripe webhook handler, and he only caught it when he reviewed the work.
Joao Silva installed the Jev decision-model skill into his AI fleet without writing integration code: he pasted a plain-English instruction into a session and the agent copied the folder, found the right .env file, added the key and ran the checksum verification. The skill then passed his mandatory three-reviewer gate (security, QA, technical writing) before being committed.
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.