Opus decompiles Windows 95-era games to byte-exact source in about a week each
Uses Opus 5.5 to decompile Windows 95-98 games in about a week each, getting byte-to-byte exact output with clear names and no Ghidra smell.
A random mix from the whole library. Shuffle for a new set.
Uses Opus 5.5 to decompile Windows 95-98 games in about a week each, getting byte-to-byte exact output with clear names and no Ghidra smell.
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.
He linked Antigravity IDE with AI Agent on Windows as an experiment. It watches for transit delays and weather updates, then sends him a neat HTML summary email.
His talk archive site had been a work in progress for years. He asked the AI to help track down records of talks he has given, and the site now contains 115 presentations covering 26 years.
An LLM performance-tuned his Godot voxel game over 3 days, taking it from 12 fps to 60 fps with diagnostics and render changes.
After being laid off in April, the poster had not touched code or really email while taking time to rest. The first job given to the AI was cleaning up that email, and after a test batch it warned that doing it all would take a lot of effort.
GPT helped him fix his Bitcoin miner. He also created his own improved, branded user interface and firmware for it.
The AI vibe-coded a native mxswitch app running on both laptops that sends a DDC command to switch monitor inputs when keyboard and mouse switch devices.
He had the AI vibe code a version of smitty, the AIX system admin tool, for Linux in Python. He says that alone is worth the 20 dollars a month he pays.
A developer built himself an AI evening edition. It goes through the posts and articles he saved, checks each one against his actual setup, and sorts them into adopt, trial, park or skip. Any change it suggests waits for his yes. The first run cleared his whole backlog of 30 items, and a planted fake post with hidden instructions was flagged and skipped.
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.