A random mix from the whole library. Shuffle for a new set.
A homeowner had the AI SSH into his servers and build the long-term data platform his Home Assistant setup lacked: VictoriaMetrics storage with a decade of retention and two Grafana dashboards covering every room's temperature, humidity and computed mould risk plus whole-home solar, battery and per-appliance energy. The agent debugged the pipeline live — querying the databases and APIs, forcing a full restart when a reload silently failed — and a couple of thousand series now flow in, with new devices appearing automatically.
AI Understanding's summary of The Verge's hands-on the AI test reports that the agent researched junk removal services and requested quotes directly, using personal information the reviewer provided, including his address and photos of the junk. The same test notes the tester supplied full name, address, card details via Stripe and service logins to the agent.
His LLM agent reviews his robot vacuum's images and either sends the vacuum out or suggests moving things that would foul it up; works great.
The third case in the same comment: he had the AI call three local companies to get quotes for a fence at his property. Quote gathering for home work normally means three rounds of calls, messages and waiting; his agent made the calls itself. Prices are not stated in the comment.
He built an app with AI that reads his solar inverter and batteries, forecasts tomorrow's solar generation and household use, and emails him a report. It sets the battery charge level for the overnight cheap tariff based on the forecast.
A man doing a home renovation uses a discount monitor alongside shopping list alerts and 3D models of the project. He says the monitor on its own saved him about $2,000 on the renovation.
His 25 year old Intel Play QX3 microscope had no software that would run on a modern Mac, and he pulled it out for his grandkids. He worked with AI in stages in one morning to build a Mac app for it, and his grandkids were soon watching a seashell through it.
His home network had eight VLANs and no firewall rules between them, scoring 70 out of 100 on an audit with segmentation at 0 of 25. The AI, working through a UniFi MCP server, designed a default deny zone setup, previewed each rule, and wrote it only after he confirmed. Three audit runs took the score to 93, though one change briefly broke DNS on a live VLAN before it was rolled back.
He had the AI find a way into his ISP device and change its settings. The AI turned it into a wireless access point with 802.11r, added an access point section to the control panel, and turned off the old ISP's updates and telemetry.
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.