He used AI to build a Firefox add-on called FunData for Funda, the Dutch home listings site. It shows CheckJePlek data for each rental or purchase home, plus two map layers with land registry and livability data.
Josh Kahn replaced his family's kitchen whiteboard with a TRMNL e-ink display that shows the family Apple calendar, a dinner menu calendar, and the weather. GPT helped him build and refine the custom Liquid templates behind the plugins, and the display now stays up to date on its own.
A hobbyist says the AI assembled the firmware running his living-room lights and fans: an ESP32 web server driving a radio transmitter. It also built him a Streamlit app to explore the signals, and the code is public on GitHub.
A couple found their mailbox on the ground with the post rotted through. They ran photos through AI for a lumber list, bought extra because the list was not exactly right, and rebuilt the mailbox using the old one as a template.
This only partly worked. Worth knowing before you try it.
His 2019 LG TV has a great screen, but the official Plex app took about 30 seconds just to show the profile picker, because it is really a web page. There is no public native toolkit for the TV, so he rooted a spare set, read the TVs own software with analysis tools and the AI, and built a native Plex client of his own. On the same TV it shows the profile picker in about 3 seconds.
His young daughter lost the small cap from a water bottle she likes a lot. He asked the AI to design a replacement, printed it in 3D, and says it works perfectly.
Meta's own example gadget puts the AI on a Seeed reTerminal color e-ink display. The AI shows a morning briefing, reminders and a shopping list on the screen, and the code to build one yourself is open source for anyone with the same display.
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 Reddit user asked the AI to catch up on unfiled vet bills. The AI searched the email backlog, found five bills totalling $1,504.72, and submitted them to the pet insurer.
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.
He added a 10 foot Oogie Boogie figure next to Jack and worried strong winds would damage it. He had the AI build a script that watches wind speeds at the airport and turns off the WiFi switch running the fan when the wind passes a set limit.
Spent an hour with AI migrating a Home Assistant setup to Tailscale, updating sensors and Pi-hole, and putting it all in one documented git compose file.
His new Kasa bulbs would not talk to Home Assistant, and the problem had sat open for eight months. With the AI talking directly to the devices, they now work, a fix he says he could never have written or fixed on his own.
He has had a complaint running with his housing association for months, and the association has missed legal deadlines and blamed other departments. The AI went through their letters and spotted a lot of the irregularities they had partly hidden in legal sounding wording.
This only partly worked. Worth knowing before you try it.
TP-Link has no official way for an agent to control its Tapo devices, so he took the app apart, worked out how it talks to the lights, plugs, sensors and cameras on his home network, and built a connector the AI can use. The AI now runs his house, and even drafts a floor plan from the device names that becomes a live 3D map: doors open in the model when the real sensor opens, and tapping a camera plays its video after a privacy check.
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.
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.
This only partly worked. Worth knowing before you try it.
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.
He retired his Nest cameras and had the AI (alongside OpenCode) configure Home Assistant and the camera software on the PCs already in his rooms, Linux and Windows alike, so the household computers now double as his in-house camera system, checkable while traveling - no doorbell-cam subscription.
He dug out a forgotten 50 euro mini PC and put Linux and Pi-hole on it. With the AI and community lists, it now blocks more than 3 million advertising and telemetry domains.
Their Ninja oven died with a mystery error code. His AI researched the fault, dealt with the support case, and found the manufacturer needed purchase details, but the oven was a gift from his flatmate's dad. The agent chased the flatmate by email and Instagram DM until he sent the receipt, then sent everything off to the manufacturer. The case was unblocked.
The AI created a nightstand clock app for his spare phone from a picture and a quick prompt, and the phone clock is now in daily use on his nightstand.
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.
This only partly worked. Worth knowing before you try it.
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.