An agent one-shotted a game engine plugin from a 3,000-line plan
An agent one-shotted an Unreal Engine plugin from a 3k-line plan.
A random mix from the whole library. Shuffle for a new set.
An agent one-shotted an Unreal Engine plugin from a 3k-line plan.
He set up an AI that wakes up when a new the AI release lands. It reads the changelog, picks out only the parts he cares about, and sends him a DM when there is something of interest.
His AI runs on a server with Ollama as the backend, so his data stays private. It keeps his todos in a simple text file, sends him reminders about upcoming due dates, and gives him an overview when he asks in a Telegram chat.
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.
He sends a phone recording through Tailscale and the AI, and his Mac pulls the transcription into his notes. He asks whether the setup is useful or just extra weight.
He asked the AI to make a modern version of Rescue Raiders, an old game he loved as a kid, with new graphics, goals and tech trees. The AI went back and forth with critic and art agents until it was done, and the finished game is live for anyone to play.
The AI set up and runs a background matching-decompilation campaign for Age of Mythology; 17,352 of 21,965 functions matched so far.
Farheen Ahmad (verified creator, 120K followers) was drowning in a saved-Reels folder of content ideas she never used. She had the AI ingest the collection and convert it into a structured dashboard with spoken scripts, carousel outlines and a 'Hook Lab' worksheet, with screen recordings showing the tool learning her 'voice DNA' from her past reels and parsing insights and saves.
He used AI to get his 15 year old game, built on an old version of XNA, running again. The AI got Flite running for the first time in about fourteen years, and he is looking forward to playing it again.
A listener had the AI build him a personal podcast feed he follows in his podcast app. Each day it looks for one episode he would actually enjoy, based on his taste and recent talks, and skips the day if nothing is good enough. It downloads the pick, writes out the words locally, finds the sponsor blocks and cuts them out, checks the joins, and adds the episode to his private feed with a note on why it was picked.
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.