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.
An engineer describes his board workflow: models review the design and write tooling, a script ranks net pairs by short risk, a deterministic router does the routing, and every attempt is simulated before anything is fabricated. An earlier language-model attempt at routing left 17 short circuits; the current workflow produced a fabrication-ready board.
A teacher and dad rebuilt his classroom card-review game into 'Bad Mascots', a mascot-horror study game for his 2nd-grade son: The AI planned the conversion, wrote the image prompts and built and tested the game file, questions come from a photo of the boy's weekly vocabulary sheet, and progress saves to its own Google Sheet. Weekly updates take about 10 minutes from photo to approved questions, and the game is live and playable online.
Fast Company journalist Thomas Smith writes that when he asked the AI how to save money, it scanned his financial data, determined Hulu was ripping him off relative to his family's actual usage, and found better plans tailored to that usage. He reports the switch saved him $80 per month.
Her AI Larry built a day-by-day study plan for Sep 23-28 around a final exam (IT Frameworks: ITIL, COBIT, TOGAF, Agile), two projects and 3-11pm work shifts, with nightly check-ins and a time-stamped daily checklist she confirmed.
Ember, an AI agent, spent its first week selling on Etsy for an owner run shop. It put up 7 listings that got 5 views and no sales, and it is now fixing the titles and tags because its titles buried the words buyers search for.
Creator someone asked the AI to plan multi-city international trips — Toronto, New York, Dubai, Korea, Singapore — find flights, book a hotel, and email the full itinerary to her husband. Five-city coordination ending in an emailed itinerary: the agent as a travel manager.
Commenting on the 26 use cases post, he says he uses AI to find and apply to jobs. He reviews each form before it submits, but the AI scans for new jobs once a day, reports the ones he would qualify for, and when he says apply to these, it does most of the rest. It remembers his preferences, like salary range. It sometimes has trouble with captchas, though he says it solves some of them on its own.
His AI runs on a server with Ollama as the backend, so his data stays private. It keeps his todos in a simple text file, sends him reminders about upcoming due dates, and gives him an overview when he asks in a Telegram chat.
In Simmons's roundup of other Dots users, one person's Dot read a cancellation email, checked live tracking on an earlier train, found it running late and got its owner onto it. The account is secondhand and brief.
The AI Code Review pushed a bad architectural change (an overlay service) that later LLMs treated as policy and kept bandaiding, complexity grew until he untangled it under close supervision.
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.