A random mix from the whole library. Shuffle for a new set.
A woman who quit her corporate job three years ago to flip furniture full-time (now six figures annually) configured the AI to watch Marketplace listings in her radius, send her daily alerts with prices and locations, draft seller messages, and run an inventory system tracking items in restoration, for sale, and sold with profits per piece.
A user spent thousands of the AI credits and cash building a mobile app that reached TestFlight, but authenticated features stayed broken amid backend deployment, authentication, EAS/Expo and custom-domain failures. Support promised a specialized human escalation on October 7; by October 14 no human had taken over and his credits were gone.
Writing Rust code faster than state of the art by asking agents to make the code faster.
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.
He set up an AI for his WP Beacon project to check WordPress plugins every day. After two weeks of daily checks it pinged him about malware in the InstaWP Connect plugin, and wordpress.org closed the listing that afternoon and restored it the next morning.
An LLM crunched for 36 hours on a project he had wanted for 5 years; checked and ready to deploy, work he estimates would have taken him about 9 months.
A man told the AI to push a project further. The project depended on a contract in his Gmail that he had not read. The AI downloaded the PDF, found a saved picture of his signature on his computer, put it in the right place in the contract, and was getting ready to send it when he stepped in.
He stopped using Descript and now cuts his YouTube shorts with AI. He says the quality of the shorts has gone up since the switch.
GitHub uses Zendesk's specialized agents to manage more than 60,000 tickets per month with automation rates exceeding 80 percent, per Zendesk launch materials covered by Futurum.
He runs Qood News. When the AI 2.5 was retired, moving to the AI 3.1 would have tripled his AI bill, so a decision model called Jev now decides what counts as good news and costs stay about the same. In testing Jev approved 39 of 110 stories while the AI approved 53, mostly dropping filler.
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.