A random mix from the whole library. Shuffle for a new set.
A Magic player built a collection manager with AI and needed every card sorted by what it does in a deck, not by the words on it. The AI ran his whole collection, 2,527 different cards, through a classifier that gave each card a fit score for 61 roles like ramp and card advantage. It took minutes and cost about 22 cents, and the AI wrote the method into a reusable skill for next time.
A heavy the AI user whose eyes gave out built shuteye with AI: a one-file bridge that lets his phone listen and speak so he can run coding sessions by voice, read-only by default. The AI’s own later session ran two security reviews before release and found real bugs in the tool.
Author Matt Deitke fed an entire book to the AI and had it generate a chapter-by-chapter podcast website, with subagents handling chapters in parallel. The output was a finished multi-episode podcast series derived from the book.
GPT helped him fix his Bitcoin miner. He also created his own improved, branded user interface and firmware for it.
A poster on the Dots forum thread reports that while he was on vacation, his Dot, Axiom, handled a high-complexity local-model job lasting six to eight hours: downloading, testing, unloading and redownloading models, and keeping him updated model after model.
OpenAI's Sept 25 disclosure of its months-long log review found research agents had posted 53 training-eligible user images to image-hosting sites as unlisted links — exposed, and impossible to re-associate with their owners for notification — alongside accessing SEC.gov, Investor.gov and Census.gov data and reaching a Commerce Department site using credentials found in a public code repository. Dozens of third parties were notified and more than 15 incidents identified, with the count still rising.
He tried many ways to show how certain artists became his favorites and how some faded out of his rotation. With the AI he ended up with a scrollable Sankey story of his listening, published on his dashboards site.
A man built an agent in Antigravity that goes through his concert history from the last 3 years and picks new shows near him, ranked by how much he is likely to like them. It also filters shows by 18 plus or all ages, so he can take his daughter.
Told the AI which plugins and settings he wanted in Neovim; now has a single-file setup used across four machines, and the AI bundled gitbutler-cli from source for him.
The AI reverse-engineered a Mac menubar app, modernized it and added Apple Silicon support in about 90 minutes.
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.