He now uses AI for design work and for putting print plans together. It fixes the biggest problem in his work, clients sending poor quality files, and gives everything back neat and ready to print.
The AI was working in a homelab repository and wrote a test command that set a temp folder variable, then cleaned it up with a find-and-delete using that variable. An earlier step in the chain failed, so the variable was never set. Unquoted and empty, the delete ran against the current folder instead: the repository root the shell was sitting in. It deleted every file in the checkout, about 5,200 working files plus the git objects and refs. Only files the sandbox mounted read-only survived.
This one went wrong. See what happened before you try it.
A scheduled task on his Mac fired at 3 am, ran AI on his notes folder, read his git log for the last 26 hours, and wrote one video proposal as markdown. The steps of the routine live in a markdown file, so to change the routine he edits a note.
A WooCommerce store owner had a legacy on-site point-of-sale system whose vendor finally offered a backend way to pull customer emails from a mailbox - and he avoided implementing it for two months because the integration looked painful. One evening, about two hours with AI produced a small working plugin; tested that night, it now automatically does data entry he describes as hours and hours of manual typing.
The AI prepared and launched their Amazon ad campaigns in about 10 minutes. He says plenty of thinking went in before that, and the launch itself took the 10 minutes.
He built a team of AI agents that run on a schedule while he sleeps. They grade their own output against scoring rules, write new rules from what they learn, and start the next night better. He uses the loop for web pages, Instagram Reels, long videos and Substack writing.
The AI hacked together a compatible-enough S3 implementation for his self-hosted Sourcehut releases in about 45 minutes; it works well enough and is in use.
His 5th grade class studied Maricarmen and her eviction, a real case, and the pupils made work about it. He gave Notebook the AI directions to redo the class video so all of their work can be seen, and the video is posted with a PDF of the work on his class blog.
Inbox prioritization scored 6/10: The AI produced a useful view of what needed attention but concluded Diana had not sent an email she had sent — trusting it would have meant a duplicate email to someone already contacted.
This only partly worked. Worth knowing before you try it.