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 read Palworld game data files and built a personal wiki with map assets and linked drops and locations, more useful than the fan sites (a second game wiki in the same comment left as a passing mention).
After SAS cancelled and rebooked his family's Oslo flight and a human agent said the dropped prepaid meal fees couldn't be fixed, a father asked the AI to pursue the reimbursement he had never filed since July. The AI searched all his SAS emails and found the airline had already reimbursed the fees the day of the change - buried under that day's notification spam.
Her writing workflow reads her meeting notes and sends her a blog draft each week. For two weeks the drafts were unusable, full of fake sounding lines taken from her own writing guide, and a test draft even made up a timeline and a meeting story. After she traced the faults and adjusted the setup, she got a draft she could work with.
A corporate salesperson who cannot code keeps all his customer files in one folder that the AI reads directly. Before a meeting it pulls out up to three things to check, and after a meeting it turns his voice memo into minutes and a thank you email and files them.
His son is in half a dozen orchestras and bands, plus cadets and Explorers and Scouts, and his daughter is in reception class at a different school. Both schools send everything by email, the important details are often buried inside one of several PDF and Word attachments, and he kept missing things. Over the years the schools had collected three different email addresses for him, which made it worse. He got the AI to help him build a system that runs on a schedule in GitHub Actions, reads the school emails and drops the events into a shared Google Calendar. It costs him about $2 a month in API credits, which he calls much cheaper than a missed guitar lesson.
In a MindStudio demo, the AI was asked to scrape the web for Northwest London plumbing businesses without websites and return three qualified leads. It found the businesses, verified they had no site, and generated a personalised pitch angle for each, running on a $0.24/hour CPU instance.
Spark read 20 to 30 of the founder's sent emails, extracted his two writing registers, greetings and sign-off patterns, and saved a reusable ghostwriter skill. Days later in a fresh task it drafted a PR email in his media-outreach voice without being told which tone to use.
His team is replacing a client's 15 year old system. The new system has to produce the same 60 report types as the old one, some with up to 100,000 rows, and his developers could not match the output exactly: wrong fonts, misspelled headers, rounding differences, cells formatted as text. He gave Fable 5.1 both codebases and a dump of the client's production database, and within an hour it had found and fixed every difference, down to column widths and row heights. Matching the reports by hand would have taken weeks.
Andrew asked the AI for the cheapest price on a new iPhone and AirPods, the best trade in value for his old phone, and whether a new model was about to drop. The AI found Amazon beat Apple by about $50 on the AirPods and a trade in worth about $200 more, and he bought on Amazon himself in the end.
Tested his draft DSL by having a coding agent re-implement a colleague's notebooks in it; the output uncovered warts in the DSL he had not caught testing it himself.
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.