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.
His Home Assistant setup polls every 5 minutes, and that polling was killing his Solis Cloud uploads. Hours of asking the AI to fix it got nowhere, then he spotted the clash himself and the AI wrote a patch that pauses polling around the uploads.
This only partly worked. Worth knowing before you try it.
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 had the AI add all the special days from the Pittsburgh Public Schools calendar into the family calendar. It was a win, but the school calendar itself had errors, and he spent 30 minutes working out which day was wrong.
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.
Got the AI to implement TPAP compatibility in Swift purely by interacting with his local plugs and response shapes plus RFC 9383, figuring out it was SPAKE2+ and the password hashing steps.
After the AI started managing his home systems, he gave it control of Home Assistant too. It proved good at writing automations and doing the setup, and he later moved Home Assistant into a Docker image.
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.
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.