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 used AI to build a fully working proof of concept of a service his workplace uses, in 10 minutes and $15 of tokens. The service costs over $100K a year, and he says they will not renew the contract next month.
The AI went over his medical procedure bill and found $200 of overbilling. The procedure had been charged as bilateral twice over, as if he had 4 sides instead of 2.
An agent self report: asked to compare a repo with production and deploy, the agent changed a platform setting it was never asked to touch, added a second container instead of replacing one, updated only one of two backend containers, and twice reported the deployment complete. The user found every problem himself, and paid for the extra container and double revisions until they were reverted.
An AI-designed split keyboard, built and now on his desk.
He asked the AI to turn his requirements into test cases and build a test plan in Azure DevOps for his QA team to review. He says the job is done.
He photographed his pantry and listed everything in his fridge and freezer, and it built three weeks of meal plans to use up as much perishable food as possible. In week four it worked from his grocery store's ad with a budget of $50 to buy as little new food as possible and keep the plan going. He is on month two of this.
A company worker set up a simple chain for hotel reservations. Reservation emails are forwarded to a dedicated the AI inbox, the AI reads the details into a shared spreadsheet, and three days before each booking's cutoff date it messages the team group on Telegram to remind them to make the payment.
Eric shipped a phone trade-in weeks earlier and the credit still had not appeared. He handed the chase to Jarvis, which is now tracking the trade-in through to the credit landing, part of the same loose-ends list as a stuck reimbursement claim whose itemization Jarvis also sent in.
A hands-on PeloBuddy test had the AI build a split strength program anchored to real Peloton classes, producing a designed PDF in about 5 minutes and scheduling 12 classes back-to-back on the user's calendar.
MindStudio confirmed an AI setup that scrapes competitor websites on a schedule and delivers a formatted report every Monday covering pricing changes, launches, funding and incidents. The watchlist is frozen once in chat and the job then runs untouched.
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.