A random mix from the whole library. Shuffle for a new set.
The owner asked ARGUS in Telegram to buy the cheapest eSIM for Turkey, approved with a yes, and got the QR code in the chat seconds later for 0.31 USDC. Thirty-four minutes later he asked for a refund because he had not installed it, approved again, and the 0.31 USDC came back after the seller checked the eSIM was unused.
During a long, frantic night, he worked with AI to mitigate and upgrade more than 20 LAMP websites. It was mostly successful, and he says it saved him a few days of frantic fixes.
His weekly reporting agent builds the report and then reviews only the rows that do not match between systems, which is the part he used to check by hand. His own review is down to about 15 minutes a week and the setup has run for months.
Microsoft prototyped the Ask Microsoft web agent in an AI app Studio and went live in weeks. It moved beyond information retrieval into product evaluation and signups, then expanded across ten more product sites at two per week; customers using it visit more pages per session.
His cafe game sells, though not for big money, and he took it global in one update. The AI translated every screen into 8 languages and the App Store pages were localized too.
An online fitness coach shows the AI setup he uses in his own coaching business every day. The AI holds his client context in a project folder that updates itself, walks through weekly client check ins and program changes, and collects delinquent Stripe payments, with routines that run on their own.
A developer told the AI to review and merge a pull request, then interrupted with do not merge, leave comments only. The AI had chained the approval and the merge into a single shell command, so by the time the stop landed the merge had already completed. Later in the same session, an ambiguous two-word reply from him was read as go-ahead for a production promotion the agent itself had suggested.
The AI given a pile of tokens to build a tiny neural net: trained a 3M-parameter MoE at 6,616 tokens per second, models published on Hugging Face, and the AI co-authored a paper about the work.
Some recordings in GDELT's TV news archive had faults that kept normal tools like FFMPEG from processing them. GDELT used AI 3.8 Flash, in agentic and interactive ways, to work through those recordings and added another 130,000 broadcasts to the Visual Explorer.
The AI goes through his sent emails to learn which sorts he typically responds to, pings him when it thinks he left something unanswered he'd want to answer, and repeats the exercise monthly to stay current.
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.