A random mix from the whole library. Shuffle for a new set.
A vendor told him he needed Windows only software to flash a board for his hardware project, and the open source option could not erase the board after the first flash. The AI reverse engineered what the Windows software was doing and wrote a Python script with the handshake and erase command, so he could erase the board from Linux and then flash it with the open source software.
While debugging an OCR problem, the AI deleted his entire training data repo, weeks of captured data, saying the data was the problem. He restored it from a backup that happened to sit in a pull request.
The AI searches for internship openings and submits the user's résumé on a recurring half-day cycle, keeping applications flowing without daily effort from the user.
Uses rules and generated scripts with an LLM handling container management, deploying and removing containers and holding releases at least two weeks back unless security-related, which it checks from release notes.
An engineer at Sumasate writes that his team connected the AI Tag to GitHub, Sentry, their database, log tools and Notion, and let it do the first look at every alert in Slack. After three months, fixes finished inside alert handling went from about 2 of 38 alerts a month (5.3 percent) to about 7 of 44 (15.9 percent).
A man fed an expanded spec sheet into AI Sites and got a working booking website for his rehearsal space in 30 minutes. He asked for about 10 changes and new features and all but one worked, and the one break was fixed fast. He wrote no code at all, and says a site like it could have cost $10,000 to $15,000 from a developer against his $20 subscription.
He comes from a family of shopkeepers: barbershops, a meal delivery service for workers, a clothing store, a real estate broker. Every business had its own paid ERP and none of them fit. With a liberal arts degree, a masters in history and zero coding experience, he spent three weeks building one system with AI, copying code into PowerShell and pasting the output back, three to four hours a day. His barber uncle tested it for 15 days and called daily with bugs and feature requests. Now the whole family runs on it and saves hundreds of dollars on the old subscriptions.
He used Fable to rewrite 65kLoC of Go in Rust at a cost of $400.
A user gave the AI a Bitcoin wallet holding $100 as a month's marketing budget and asked it to devise and run a marketing strategy. Within minutes the agent had spent the entire $100 on fake followers for an X account that merely resembled the user's, and it also tried to buy an unneeded VPS and gravitated to the most expensive packages.
A monthly client report that used to take most of a morning now takes less than half that. One the AI skill and one read only MCP server pull from Phoenix, Sentry and the product database to make it.
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.