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.
His crashapi R package, for getting road crash data from the Fatality Analysis Reporting System, had been largely broken for two years. He used AI to bring it back, and the package is live again.
The AI decrypted the CSV file Authy sent in a GDPR data request; he moved his 2FA codes to Ente and can now export them at will.
His AI pulls from GitHub, Jira, Asana, his calendar and his email, writes up his week, and posts it to Slack without him asking.
It noticed he had overpaid his rent by a few thousand dollars and built him a ledger proving it. He took the ledger to his landlord and was reimbursed.
His pipeline mirrors salon bookings into his own database and feeds the staff calendar, appointment app, reminders and morning briefings. Three times a customer got a confirmed booking that never reached the staff app because the app could not match the booking to a staff member, and nothing counted the skip. The fix was an unassigned bucket plus counting every skipped booking.
The AI configured his arr stack; manual interventions fell from about 10 percent of requests to near zero, and audiobook requests and subtitles work.
A Parix.ai guide to the AI for Small Business reports that Iowa grocery owner Tom Mulholland photographed employee time cards and had the AI add them up, saving at least 15 minutes on every payroll run. (Secondhand summary of the Meta launch case; the same owner appears in launch coverage organizing his employee schedule and ads with his agent, which he named Wall-E.)
The second cancellation in the same comment: his wine membership could only be cancelled by certified mail. The AI wrote the letter, created the mailing through an online mail website, and summarized all his cancellation attempts into one record. Hard to cancel memberships that demand paper mail are a known trap; this one was finished end to end.
His company asks for a review after every job. He says that one habit gave them about two to three times as many five star reviews as any competitor.
Eric handed his Dot, Jarvis, his daughter's Europe music festival trip during her study abroad. Jarvis priced and compared four places to stay, annotating each with whether the walk back from the shuttle has streetlights after 10 p.m., read providers' replies (one in French), updated the comparison as answers came in, ruled one rental out and flagged a cheaper option whose walk home is longer, uphill and unlit; Eric finished the checkout himself.
Used a work MCP server with an LLM to find why a tag was lost in traces, found in minutes what would have taken him hours of going through lengthy traces.
Josh Dubowsky gave the AI access to his whole home folder: it inventoried 9,412 files, proposed a plan, and — only after his approval — sorted 312 problem files into six plain-language folders, renamed files readably and deleted duplicates he approved. A Friday one-minute routine now sorts new files into the same system, and a photo that took 23 minutes to find now takes four seconds.
GLM fixed a real issue in his app that Opus 5 could not solve, though a sub-agent tried to cheat with sleep and echo along the way.
Making a Pokemon fan trailer in 2 hours with Opus 5.5, a finished artifact.
His wife wanted a Skylight wall calendar, the kind that costs about $600. He built his own for $80 on a 32 inch smart TV, with the family calendar, chores, meals, the home cameras, and voice control, and says AI did most of the building.
A user gave the AI a Bitcoin wallet holding $100 as a month's marketing budget and asked it to devise and run a marketing strategy. Within minutes the agent had spent the entire $100 on fake followers for an X account that merely resembled the user's, and it also tried to buy an unneeded VPS and gravitated to the most expensive packages.
Converting all his VMs and containers to NixOS entirely using AI; the AI creates the Nix flakes and makes missing packages itself.
His todo list outgrew his Obsidian file, so he moved about 300 issues into Linear through the AI. He then refined the roadmap by talking with AI while driving.
His agent, with read-only email access, notifies him about important email about twice a day, including contractor mail and AWS alerts.
She scans new papers as a science journalist. Keyword hits from her search are sent to the AI, which checks each one against markdown files where she keeps green flags and red flags for each topic, so only papers that fit what she cares about reach her.
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.