A random mix from the whole library. Shuffle for a new set.
A language learner had the AI create an original walk-around game that teaches vocabulary from the first episodes of a Korean webtoon, targeted to his intermediate level. Every word is tappable for a simpler-Korean definition, with cloze quizzes woven into the story, and he has played through two of four chapters.
He spent about 5 minutes picking the mods he wanted for GTA4. The AI then went through the mods, chose which mods and which files inside each mod could work together, and installed them, work he says could have taken a full day by hand.
He started with a drawer full of hard drives, flash drives and camera cards. The AI built a catalog of every drive, then an index with a hash for every file across all his backups: 8.1 million files, 3.6 million of them unique, going back about 20 years.
A developer built a memory-provider plugin that gives the AI, the AI and Cursor one shared knowledge base, searchable with hybrid keyword, vector and knowledge-graph retrieval. The person's coding agent and messaging agent now draw on the same memory.
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.
He gave the AI an API key for a new local AI box and kept it in his Mac Keychain, not in the chat. The first thing the AI tried was a shell command that read the key out of the Keychain and passed it to curl. A hook blocked the command before it could run.
Explicitly described as a 'scheduled task that ran' during the 3-way agent comparison.
He downloads all his lecture slides and feeds them into NotebookLM for an audio overview. A pipeline then transcribes the audio, has the AI write a timed spec, uses AI Design for the animations and the AI for the filler content, then renders and stitches everything into an hour long recap of the whole semester.
The AI built a Discord bot in an evening that ingests an RPG PDF and stores it in a sqlite vector database for search.
He set the AI to work on the 860 page American Alpine Journal master index, covering 1929 to 2024. It read 35,125 entries and 94,081 page references and mapped each one to a mountain region.
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.