A random mix from the whole library. Shuffle for a new set.
XAI says Starlink call centers run on the AI Voice, handling about 20,000 customer calls a day across multiple languages, with roughly 70% resolved without a human and one in four sales calls ending in a purchase. A single agent verifies customers, troubleshoots hardware, issues credits and ships replacement equipment.
The AI found a Reolink init tool and took care of enabling and configuring his newly bought RLC-810A cameras that required an app to set up RTSP.
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.
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.
His local LLM runs permanently as a Home Assistant agent with agentic access to his sensors, answering voice queries about his solar and battery data and creating automations.
Home Assistant sends a bin camera image to the Anthropic API, gets JSON for which bins are visible, notifies him which bins to put out or return, and lights a color LED Bindicator; the AI configured the automations via MCP.
A parent of three was copying school, cram school and nursery dates from paper prints, LINE and email into Google Calendar by hand, and nearly missed a field trip lunch. He built Hanamaru: the family posts a photo of a print in Slack, the AI pulls out the dates, and it registers them on the right child's calendar, asking in the thread first when it is not sure.
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.
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.
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.
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.