A tiny trained classifier sorts his email at 95 percent accuracy
The AI or the AI built an embeddings plus logistic classifier for his emails reaching 95 percent accuracy from 50 to 100 examples, trained in under 5 minutes locally.
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.
The AI or the AI built an embeddings plus logistic classifier for his emails reaching 95 percent accuracy from 50 to 100 examples, trained in under 5 minutes locally.
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.
He wanted to digitize his papers. The AI worked out how to use his feed scanner, and for about two hours he sat feeding pages in while the AI ran the scanner and catalogued the documents. He could talk to it through a conference speaker and watch it work in VS Code.
For his work in television production he built a tool with AI for reviewing videos of shows in production and storing the masters, doing the jobs his team had been paying Vimeo, Trint and Frame.io style services for. It runs on one small server with a graphics card and has saved about £40k.
The AI sent a notification that it had spotted an email from TripIt, the vacation-planning app Ulanoff uses, about a password change he had forgotten making. The agent wanted to make sure he'd seen the email verifying it was him.
Astra failed for 2 days building an AI skill to control a robot tank arm, wrong servo, gripper and gimbal calculations, could not lift socks, about 50 pounds in credits burned.
Steve Morseman gave the AI his ISP account info and asked it to cut the bill or improve service. The AI used its calling feature to wait on hold, negotiate, then patch him in to pick between two saving options — $840/year claimed, no plan change.
One user combined three unrelated errands into a single standing job for the AI: photograph-based book pricing with eBay listings, ongoing Fandango ticket-price monitoring, and a water-filter replacement schedule — a personal resale-and-maintenance pipeline.
Nina Dobrev asked the AI to track flight prices from 4 cities ($7,472.74 total) and build a 10-day Rome itinerary for her girls' trip. Multi-origin price tracking plus a full itinerary — group-trip planning with real numbers.
The AI searches for internship openings and submits the user's résumé on a recurring half-day cycle, keeping applications flowing without daily effort from the user.
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.