A farmer's John Deere combine had an electronics fault for days and a paid Deere mechanic could not find it. Working with AI, he built a test suite that read the machine's CanBUS messages and the traces from his oscilloscope, and compared both against a second working combine. They found two faulty controllers and the machine runs again.
He built a Lego mailbox with a small motorised flag. The AI hooks raise the flag when the AI finishes a task or needs him, and lower it when he writes a new prompt or leaves.
He built a home dashboard with AI that pulls a dozen sources into one wall screen for the whole family. It shows the shared calendar, weather warnings, solar and battery levels, car charge and bin days, and it only brings things up when they matter, like bins out tonight or a frost warning.
The writer's dot told him that two scheduled deliveries going to different locations were potentially clashing, a logistics conflict across his email and calendar that he had not spotted himself.
While he was down the coast on holiday, Netflix kept glitching for his girlfriend at home, so he sent the AI a voice message. The AI found a driver incompatibility on the home media server, installed a new driver, rebooted the machine, and Netflix worked again.
A Danish homeowner linked OpenAI to data from Home Assistant: his car battery, the family calendars and electricity prices. Every morning he gets a small report with advice on when to charge the car and when to wash and dry clothes.
He had black mold in his home and no idea what to buy. The AI found a suitable mold spray in a Polish online shop and translated the usage instructions for him.
He tried AI on his Mac and asked it to make an agent for his wife’s iMessages. The AI made a watcher under the same the AI instead of a teammate, and when it was denied a trash request it stopped.
This only partly worked. Worth knowing before you try it.
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.
Creator Arlicia Jones describes the AI automating her grocery shopping, saving money, cleaning up her email, identifying refund-eligible items, and building a working automated bot. She promotes the service with a referral code (ND6YC6).
During a week-long, move-in agent test, the journalist's the AI (Mark) logged into her Facebook, scoured Marketplace for couches, lamps and rugs, drafted and sent seller messages with her approval, and managed the replies. The hunt ended with a real purchase: an AI-sourced dining table.
A Tesla owner’s the AI took a Sentry-mode scratch incident end to end: it cut the relevant clip, identified the other car, wrote the incident report and sent the insurance claim. The whole claim package was assembled from the car’s own footage without the owner editing video or forms.
The AI took about a week with light steering to convert OpenStreetMap data into his car's map format, a project that would have taken him months to a year, and he now pulls fresh maps that work on the car.
AI built his renovation material list and looked for discounts, saving about 2,000 dollars (watch for fuller sibling telling 50013796, dedupe by case facts at merge).
A father set the AI up to read 7 school WhatsApp groups twice a day on school days and post only the items about his daughter into a private chat he shares with his wife. It reads PDFs and images too, and caught his name on a volunteer roster he would have missed.
His new hardware device was faulty and the community had spent days looking for a fix that did not need a replacement. He plugged it into his computer, asked the AI to fix it, went to dinner, and came back to find it fixed.
Over four weeks of evenings, an AI agent wrote the firmware, the live web chart, the Node-RED automation and the enclosure CAD for his radar stair light, driving a live Fusion 360 session through its scripting API. He reviewed, printed and measured, and the second half of the video lists what the agent got confidently wrong, including a radome gap that landed on exactly a quarter wavelength.