A random mix from the whole library. Shuffle for a new set.
After every client call he drops the Google Meet transcript into his note system unread. The agent pulls out the decision, the reasoning and the next actions, and files them with the right project. He has built up more than 450 linked notes this way since April, and keeps the raw transcript beside each note because names sometimes come out scrambled.
His work document had text overlapping in the footer, and the AI fixed that part. When he asked it to fix the spacing it had removed, it handed back a file link that went nowhere instead of the file.
Fable built a minimal proof assistant, then checked its soundness and found and fixed 5 ways it could prove false theorems.
An AI IDE built a device certification app in about a day, then upgraded his production test codebase to a v1.0-ready state with automated configs, error handling and simulators over two weeks.
A consulting-practice owner had 166 AI agents across seven workflows read his real system files and build a 4.5-minute animated walkthrough of his twelve-department operation on October 15, finishing in 4 hours 21 minutes. Fact-check agents traced every on-screen claim to a source file and made 19 fixes before the video was published the same day.
XBOW's agent built a Chrome full-chain exploit affecting a billion users in six days.
He had the AI build him a screen recorder as a single local file, with a camera bubble, live transcript, and YouTube upload with real subtitles and chapters. He built it because he wanted to stop paying for Loom.
Hitachi built AI agents for more than 200 use cases in its global power and utilities business, including verifying photos of every tool and wire before and after a job. Frontline worker productivity rose 400 percent and safety improved.
A sim racing creator has the AI drive DaVinci Resolve three ways: generating timeline files, writing and running Lua scripts through the program’s scripting engine, and full computer use. He uses it programmatically to add analysis to his sim racing lap guide videos.
Today he turned Thomas, his AI agent, into an actual employee. Thomas drafts and publishes posts to X and LinkedIn with his approval, makes product demo videos in a clone of his own voice, reads his Stripe revenue, handles customer messages coming in, and files an end of day standup.
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.