A random mix from the whole library. Shuffle for a new set.
A man took the Amiga game he built in Baghdad in 1993, written in 68000 assembly, and had the AI Fable 5 read the code and port it to Godot. The port took an evening, a few more weekends got the feel right, and he released the original game for free alongside it.
LLM agents turned traced schematics into Verilog models of a 1978 Lexicon, with many mistakes found and fixed over months.
A developer had the AI build mazkir, a shared-memory service: tell the AI something once and it appears in his next chat, in an AI app and even in an AI app, stored as plain Markdown notes. Launch week brought about 160 visitors and exactly one sign-up — his friend.
A developer built Idea Leash on an AI profile running locally on his Mac: he sends a podcast link by Telegram before a walk, and the agent transcribes it, writes notes into his markdown wiki and prepares a five-question quiz. After four real walks it had logged 7.66 km, nine voice ideas and sent after-walk summaries with web searches for ideas he dictated.
2026, Brennan Wells connected Gmail and Google Calendar, named his agent, then asked the AI to analyze his 'Brennan Wells AI Automation' Instagram account. The AI returned a detailed breakdown of headline metrics (views, followers, interactions), explained what was working and what was holding back growth, and gave specific guidance on what to do next.
For years he kept a Photoshop contract just to read and write DDS texture files for his ETS2 and ATS mods. He asked the AI, and now he can convert DDS to PSD and back in batches.
He built a Word document of cheat sheets for 40 songs for a gig the next day, each song title in Heading 1 style with the lyrics and chords below. He told the AI to sort the pages by that heading text, keeping the text as it was, and the AI could not do it. He says the graphics in the document block the sort.
Bybatee's AI agent 'squishy' sent 25 outreach emails to brands in her niche — with her metrics, portfolio, and media kit attached — and set automated follow-ups after 3 days for non-responses.
Instead of just watching film and going on impressions, he charted the Western Michigan and Minnesota games. The AI built a small browser app to help him chart and then summed up the plays, and he shared EPA numbers on standard downs for the Minnesota game.
A user built optimAIzr with AI, a local-only CLI that analyses his own LLM usage habits, flags costly or repeated patterns and estimates where he can cut tokens or spending. All data stays on his machine, and the tool adds live tips while he works.
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.