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 man applying for a UK visa needed his travel history from many years back. He had saved a filled in form from the last application but could not remember where. He asked the AI to find it. The AI worked out possible dates and file types, then went through his files checking each one.
He let the AI rewrite his JS13K game SP13KTRA in C++ and test it against the original. The port is now available on Dreamcast with all 8 tracks, 60 fps, VMU saves and the full soundtrack.
The dia typesetting tool from 1999 failed to compile on modern Gentoo. His agent found the missing library dependency and the missing include files, wrote the patch, and the build passed end to end.
He redid his office after quitting his job and put a spare Roku TV up as a photo frame. The AI built the photo display app in a couple of minutes, so he did not need the $4 a month app from the Roku store.
He spent about 5 minutes picking the mods he wanted for GTA4. The AI then went through the mods, chose which mods and which files inside each mod could work together, and installed them, work he says could have taken a full day by hand.
The AI configured his network, fixed an incomplete fast-roaming setup and a DFS channel delay issue.
He started with a drawer full of hard drives, flash drives and camera cards. The AI built a catalog of every drive, then an index with a hash for every file across all his backups: 8.1 million files, 3.6 million of them unique, going back about 20 years.
A mathematician with more than a dozen finished but never submitted papers pulled out four of them and shared them with AI. The AI caught errors, built a spreadsheet comparing his new concepts against related papers, converted plain TeX to LaTeX, wrote abstracts he adopted almost word for word, and fixed bibliography entries unprompted. All four papers improved to the point where he submitted them.
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.
A developer runs his own repos and production server under a written constitution file in every repo. Automated runs check production logs daily and file bug reports. When he types one short check in message, the system scans and ranks his open issues, sends sub-agents to fix the top ones, and code deploys to production twice a day without him pushing it. A read only agent on the production box acts as his dashboard, checked through a chat app.
As the only financially literate owner, he ended up president of a condo association with negative money in the bank. He fired the management company, then built an owner portal with AI that handles accounting going back years, dues tracking, bills, payments, compliance and vendor records. The association is out of debt, and the whole thing runs on free tier services plus a domain.
Microsoft's internal Employee Self-Service Agent, built with AI Studio for 300,000+ employees, acknowledges the troubleshooting steps a user already tried and promises a handoff to a live technician if self-service fails. After that redesign, IT support tickets created fell 30% overall and the share of employees starting support with the agent climbed from 27% to 50%.
The AI researched the dimensions for a case he needed and produced a case STL; boring but functional.
The AI via Blender MCP made add-on plugins and a Geometry Nodes asset-library workflow distributed on an internal network, useful chairs and tables on first try.
On day 19 of using her AI Mila, the agent offered three beginner low-impact workout options built around her garage equipment — she did all three — and keeps weekday workout reminders running.
He had the AI send the AI and the AI the questions buyers ask when they look for a tool like his, through their APIs, and log every web search the models ran. Then the AI wrote SEO pages for those exact questions.
AI agent populates and keeps updating home lab inventory and documentation in Netbox.
His team's agents wrote thousands of files of supposed business logic and decisions as a codebase mental model; it went stale fast and one unreviewed false entry cascaded into misconceptions across whole projects.
He bought an M5Stack stopwatch for 45 euros and never used it as one. With the AI he turned it into a round Home Assistant info display with 14 modules overnight, in under 25 minutes of typing himself.
A daily routine on Sonnet reads his email, answers the routine messages from templates, and puts the rest on his todo list. When a task needs more than an hour, the routine blocks time for it on his calendar.
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.