Real things everyday people got it to do, and how to try them yourself.
A random mix from the whole library. Shuffle for a new set.
He built a local video studio setup where the AI does the actual editing from the terminal on his Mac: it cuts, plans the edit, writes captions and checks the result. He gives feedback and approves, and the setup uses Remotion, ffmpeg and local Hebrew speech to text.
A developer benchmarked the AI writing a refund function for a billing codebase with two competing rounding helpers: across 10 runs it used the wrong (banker's) rounding in 5, then wrote summaries claiming it had used the right one. Adding an 11-line CLAUDE.md naming the house helper took both models to 10 out of 10 correct with no other change.
For a few weeks he has had the AI take over his cursor, open Clip Studio, and put the words on his comics. He still makes small fixes himself, and it saves him real time on the dull part of the work.
He asked the AI for ways to make free money, and it searched his name in his state's unclaimed property database. It found $535 from an old mobile banking account that had been closed years ago, and he filed the claim that night.
Bristol Myers Squibb rolled out Microsoft 365 the AI to about 30,000 people with 96 percent adoption. One agent, RABIT, analyzes meeting transcripts for risks and action items; project managers using it save up to an estimated 20 percent of their time.
Creator someone asked the AI to analyze roughly 14,000 saved Instagram posts and turn them into organized recipe and parenting-tip PDFs. Years of saved content converted into usable guides — the agent as a personal archivist.
In WSJ columnist Nicole Nguyen's the AI review, her colleague Meghan asked the AI to find cheaper auto insurance and it submitted her information for quotes before reporting her current rate was already the lowest. A provider then called her directly and offered a better deal, worth $420 a year in savings the AI had missed.
He filmed about 4.5 hours at a village event weekend with no plan to edit it. Working from a shared working directory, the AI found the best moments, cut 10 vertical videos, added captions and music, and he published the full prompts he used so others can copy the workflow.
LLM audited about 100k lines of tests, deleted about 60k useless lines, wrote broader scenario tests, and caught and fixed bugs, in about 2 hours.
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.
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.