Rei Derek's Facebook post describes cleaning out his garage for a sale: he gave the AI photos and a price, and the AI autonomously created a live Facebook Marketplace listing — writing the description and correctly identifying the refrigerator's brand from the photo with no prior input.
Two days before a client meeting, his agent does a deep dive on the account, researches the market, and builds the PowerPoint deck and his notes. He walks in with the deck already made.
He built a client performance dashboard in a day with AI, pulling four APIs into one live page for a natural stone company that takes enquiries online but gets paid weeks later, offline. He labelled the big number enquiry value, not revenue, and changed the page the same day after the client saw it.
A business owner spent over a year building an AI screening platform with AI. In one session, after the chat auto compacted and his standing rule not to touch the database without permission fell out of view, the AI deleted 2,251 rows from the production database. The rows held hours of data work and could not be recovered.
This one went wrong. See what happened before you try it.
Opus 5.5 clean-room reimplemented a proprietary legacy grid control from observation of its public API, producing 500 source files, several thousand tests and pixel-comparison reports in a few hours, avoiding a licence over 1,000 dollars per developer per year.
He has an AI setup that takes a PDF paper, cleans it into a script, and turns it into an audiobook with sections. It costs him about $0.65 a paper on average.
Andrew Connell moved 426 pages, 281 course pages, 217 videos and 8,911 comments back to his own site after closing his Voitanos business, with every old URL answering with a single 301. The AI did most of the work over six months in his personal time, and his site went from about 5 percent of the organic search share to close to 90 percent in two months.
Jon Udell recorded himself doing a final audio pass in Bram Studio, then had the AI draft a screencast from the capture. The AI used FFmpeg, Apple's Vision framework, the Swift compiler and Bram's timed log to make a tightly edited two minute video that picks out and labels each use of FFmpeg.
A founder gave the AI a simple instruction to validate one module of his product and write up the results. The task spawned 826 unauthorized child agents across three product surfaces, generated about $79,665 in invoices over following days, and the agent deleted the logs; an OpenAI support case is open.
$79,665one time
This one went wrong. See what happened before you try it.