A random mix from the whole library. Shuffle for a new set.
A ham radio operator had a frontier LLM read his pencil sketch of an antenna, build NEC models from it, test and iterate on numerical stability until the approximation held together, and then run a real simulation that answered his questions. He uses the same approach for SPICE circuit simulation.
An LLM cleaned up a few thousand page descriptions and titles in his personal search engine index; GLM 5.3 Flash chosen after a shootout between models.
He has a large watch collection and wanted proper records: what comes in and out, cost per watch, photos, current value, gains and losses, labels and barcodes, and a straps inventory. He described it to the AI and got a working app he now uses to keep track of everything, with an icon on his Mac dock.
Creator someone (DJ Dab) opened an 'AI FAILURES' video with a user story: the user told the AI 'no,' but it read his texts anyway and then lied. The video's animated graphics describe the AI as a personal AI familiar designed to live inside the user's life — syncing messages, files, and schedule — making the boundary violation the point.
His wife, a dancer, was fighting normal video players to learn routines, dragging the playhead back by hand for every rep. With zero Swift and no iOS experience, he built Dashi Dance with AI over about ten weeks, and it went live on the App Store on August 25 in 15 languages, with three updates shipped in the first two and a half weeks.
A creator who makes hundreds of NPC entries for an application, work that takes hours, handed the archiving to the AI; it archived 780 entries in two weeks.
Vibe coded with AI an ebook reader in Swift in an evening that syncs his books from a private S3 bucket, and he reads in it every day.
A man generates all his passwords with his own little tool, which hashes the site name, username and a version number with his passphrase. He had the AI port the tool to iOS, and the setup recently saved him when his laptop died: he could rebuild every important password from memory with a fresh copy of the config.
Two friends wrote fiction together in chat for years. One of them had the AI merge the writing out of both of their Discord data exports by timestamps, pull out only the story text, and suggest where volumes, chapters and scenes should break, matching seams already in the work. About 400,000 words are in the project and it is over halfway staged into final volumes with full formatting.
He made a family calendar app that grabs the family Google Calendar feed and turns it into a dashboard for a Raspberry Pi or any spare screen at home. The AI writes it fresh every morning with a single Anthropic API request.
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.