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's Bluetooth keyboard and trackpad can only pair with one computer, and the switching tools he found needed both machines awake to work. He used AI to help build his own tool, which moves the pairings to whichever computer is active based on sleep, wake and display events, and he put it on GitHub for anyone to use.
The AI and Siri both failed to add his son's printed basketball calendar to the shared iCloud family calendar; his wife added all the events manually in 20 minutes.
The AI phoned the hospital to confirm insurance coverage for the user's X-ray and escalated past the hospital's own automated system to reach a human who could answer.
He had the AI configure his smart TV through its debug connection to use a filtered DNS service. Ads on the TV stopped, which he jokes is either a great morning or the start of a robot uprising.
Harry McCracken's Dot, Chip, cross-checked his calendar against his email and spotted that a speaking engagement he had entered on one date had been rescheduled by the organizers to a different day, which the confirmation email showed. He says he would otherwise have shown up to an empty room.
He had wanted an automatic provisioner for his boards for a long time but it was a whole project on its own, so he told the AI to write it. Some physical steps still need him, but each board now takes 2 to 3 minutes instead of a few stressful hours.
Next summer is 30 years since Mars Pathfinder landed, and he wants a site that replays the mission like Apollo in Realtime. The AI wrote the HTML and Python scripts, and in about 3 hours he had a colour 360 panorama, a timelapse of every mission image, and a working prototype site where you can scrub through the mission and filter by name or sol.
Agent integrated libgit into his IDE project to add source control, work that would have taken months by hand, done in about 2 weeks of calendar time.
Uses the AI on his phone to clone projects, build his features in, build the app and push it to his phone, usually not upstreaming.
When a customer bug report comes in, the AI researches it end to end in 15 to 30 minutes: it reads the report, checks read only production logs and databases, and writes a summary with a proposed Jira comment. He approves the comment before it posts, and he says he barely does bug research by hand anymore.
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.