Days earlier he set up Pi-hole on a 50 euro mini PC and it removed ads across his whole home, with Tailscale so he could carry it in his pocket. In this second part, all built in one Sunday afternoon with AI’s help, he added an app that knows when he is home without asking for his location, his own VPN using his home IP, and DNS privacy so his internet provider cannot see every site he visits.
For a year he plugged in a USB WiFi dongle because his built in WiFi was not working and he could not fix it himself. The AI fixed the built in WiFi in 10 minutes.
A Korean automation instructor sells an AI skill kit for Naver Blog and documents his own test on a real shop: he handed the skill five shop photos and a one-line memo, and it wrote the post, placed photos, a video, a map and tags, and completed a scheduled publication in 3 minutes 20 seconds. With a reservation set, Naver itself posts at the chosen time even with the computer off.
Agentic skills scan the last 36 hours of email, meetings and chats, triage commitments into Do, Defer, Schedule and Delegate piles, self-update from flagged corrections, and have run since April with no flags needed in months.
At the same accounting firm, staff batch upload client bills and the agent reads each one, decides whether it belongs in payables, receivables, or the cash book, and posts it into AutoCount after a person reviews and amends the lines. The firm has run the setup in production for three months.
He downloaded a cook's videos and bought her book, then had the AI read the book and format it at 8.5 by 11 inches. He uploaded the formatted book to Amazon for printing, in a listing only he can see.
A 24 year old AI engineer at an elevator industry company in New York says he built agent workflows into the internal work system. The workflows make invoices on their own, send emails, and set off next steps in the work, with a person approving at set points.
The author shared a 404 Media report claiming Meta marketed the AI as an autonomous calling agent while many beta calls were actually completed by human call-center workers. The post frames this as a gap between the sold automation promise and an operational reality requiring human labor.
This one went wrong. See what happened before you try it.
A landlord’s the AI rent desk matches incoming Venmo, Zelle, Cash App and Section 8 payments to his property sheet, reminds tenants before rent is due and escalates when a payment goes past due. Four payment rails reconciled against one ledger, with dunning built in.
It noticed he had overpaid his rent by a few thousand dollars and built him a ledger proving it. He took the ledger to his landlord and was reimbursed.