A random mix from the whole library. Shuffle for a new set.
He had been designing wooden bookshelves and cutlery cabinets in FreeCAD and finding it hard work. He used AI to make the designs and send the results to FreeCAD, and got fully parametric designs and cutting lists in minutes rather than days.
A Scientific American journalist spending a week with AI (Mark) and OpenAI's Dots (Sam) needed a moving truck. Her own search found no 10-foot trucks at the nearby U-Haul lot. Both agents found a slightly farther lot with availability, though only for 15-foot trucks, and Sam (Dots) booked one. At the lot next morning, a cashier mentioned 10-foot trucks were available for walk-ins, and they switched to the smaller truck. (Cross-agent event; the booking was executed by Dots.)
He put a camera on his rental property boiler and uses AI to read the screen and zone lights, texting him when anything goes outside normal operating parameters.
He needed his designs as 3D files he could print. The AI created the renders in Blender via MCP, then optimized the files for his printer.
The AI listed the user's house on Facebook Marketplace, answered renter inquiries, scheduled viewings, and the home rented in 14 days at the full asking rent.
A mother built a morning checklist app with AI over about two weeks, running on a server at home. Her daughter checks it on a tablet each morning, and the usual items open on their own from her timetable, so she is less unsure about what to bring.
He set up saved searches on Cars.com, Carvana and CarMax with his makes, models, price, year and features, and favorited cars on each. The AI merged them into one list, checked price guidance, mileage, consumer reports, recalls and reliability, named his ten best and ten worst, and removed the bottom ten from his favorites. They repeated the rounds until the list was tight, then refined by color and features. He test drove two cars from the list. While he was out, the AI checked the stock of two dealerships he drove past, just from him naming the brands nearby, and found one more match. Every morning it reruns the searches, removing cars that sold and adding new ones.
A rural homeowner had the AI mine months of his circuit-level power-monitor readings against his bills and assemble a packet documenting brownouts down to 95V, then help fill out the Board of Public Utilities complaint - JCP&L called back within two days.
His family of three uses a local assistant called Sadie, built on a home server so their calendar, photos and messages stay off cloud services. Sadie runs their shared calendar, sends location based reminders, answers texts and emails, searches family photos, and sorts household mail, flagging bills and school deadlines.
The AI completed and submitted the PRESTO service-guarantee form for a disrupted GO Train trip, the transit agency's compensation route most riders never bother with.
His 15 year old dryer broke on Saturday. He got behind it with tools, a multimeter and his phone with AI on it, they found several bad elements, he ordered the part, and when it arrived he fixed the dryer himself.
The author lost house keys and asked the AI to find locksmiths. One responded with a cal.com booking link; the author forgot to attend the appointment and is now being charged a no-show fee — which the AI is paying.
The AI and the AI re-created a Tesla data tool in Go from an existing codebase at his request; he has used the new tool for 5 months and it works well.
He had a PDF of scanned letters from his dad's Navy years, the paper letters long misplaced, and had put the project off for decades. He asked the AI to turn the PDF into an interactive timeline, and after about 10 minutes of prompting it was live online.
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.
A ready made dashboard only shows what the maker thinks matters. His own status monitor, built with AI on a 10.3 inch second screen, shows him when an n8n workflow, a hoster or his lawn mower socket fails, with 53 tests included.
He needed quotes for a seasonal tire swap, with the winter set already on rims, and did not want a day of phone tag. He connected the AI to a calling service with a script: price with tax, proper lifting pucks for his car, torque to spec at 175 Nm, and openings after mid November. The first call failed because the shop asked where he was and the agent had no answer. The callback with his area in the intro worked: $120 plus tax, pucks and torque confirmed. Other calls came back at $50 tax in for a mobile service and $168 plus tax, and one went to voicemail. Every call produced a full transcript. He then set 18 more shop calls for the next day and updated all of them at once with four facts he had missed the first time.
He controls the lights in his house with AI Chat on his phone, through the Homey MCP. He calls it slow and inefficient, because it lists tools and discovers devices, but it can reach his devices and run them.
He needed his address history for a co-op application and had struggled to dig out leases from a decade or more back. The AI searched more than 20 years of his Gmail and built a spreadsheet listing his addresses back to 2006, with links to the emails behind each date and a flag on the dates that were only a guess.
The open-source 'burner' project gives the AI a real spare Android phone (Android 11+). The agent uses the phone's apps exactly like a human would — opening them, tapping, typing, scrolling — and sends the user screenshots, extending its reach to marketplaces and shopping apps with no website or API.
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.