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 has done a couple of circuit boards using AI and Fable. Each one came back from manufacture working first time, which he says beats his own success rate doing boards by hand.
Astra rebase of his repo ran 6+ hours and still was not done, scope creep and full test suites rerun, vs Sol doing it in about 1 hour.
He used AI to test and document the unsupported switch controller in his own EdgeRouter X. The work unlocked hardware-accelerated port mirroring, and he posted the documentation on GitHub.
He exported 10 hours of his AI usage (8,915 model calls, about 1.15 billion tokens) and had the bot study it. Chat with him was only about 11 percent; background subtasks the assistants started on their own were the rest, and 96 percent of input tokens were old context being read again. He set five standing rules, including a five minute wait limit and a cap on task size. A day later a second export showed total tokens down about 19 percent and tokens per call down about 28 percent, with average context per call down from about 128K to about 92K.
Today he and the AI hacked a cheap Wish smartwatch he had abandoned for years. Now the watch talks to an AI model running locally, like a bargain basement Alexa.
Bounty experiment: an autonomous agent found a VisiData bug and specced it for a 2 dollar bounty, another agent patched it for 1 dollar, he reviewed and tested, PR merged by the maintainer.
The AI took a webinar email and made a calendar event for it on its own. It could not pull the URL out of the email, and it could not edit the event after offering to.
A vendor told him he needed Windows only software to flash a board for his hardware project, and the open source option could not erase the board after the first flash. The AI reverse engineered what the Windows software was doing and wrote a Python script with the handshake and erase command, so he could erase the board from Linux and then flash it with the open source software.
He is a caregiver, not a doctor, who has the free time to read the research. He built a clinical neurology course of about a million words that educates doctors on how to better diagnose, treat and reverse dysautonomia, a condition he describes by the dismissal patients hear: anxious little girl syndrome, you will probably grow out of it. The course has intricate quizzing programs, and he plans to go a layer deeper with interactive 3D patient model experiences for the quizzing, so doctors think through cases instead of just answering questions. He calls it his proudest thing.
He built an app that lets their nanny track her worked hours in it, so the family does not have to keep track so closely. The app holds their contract details with her, including the exceptions for vacation and sick days, and gives a total at the end of the week for payment reconciliation. It is one of several small apps he has built for family life.
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.