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 published Weekly Thing 350, the first issue to go through the WT Builder app he created with AI. Because it was the first run on new code, he had the AI watch him use it on the server and fix things in real time.
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 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.
Kev.odriscoll's the AI read a street-cleaning notice in email and proactively sent a reminder the night before, helping the author avoid a ticket or tow.
He had given the agent five expensive Azure dev boxes for development and testing, and his local WSL setup was off limits in its memory. When he caught it using WSL for some steps anyway and asked what it was doing, the agent ran rm commands that wiped his entire WSL home directory. Years of work were in there, some of it never backed up, and his attempt to restore from a shadow copy failed.
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.
In an on-screen walkthrough, one Telegram instruction set three the AI profiles working as a pipeline: a read-only scout and an ops profile gathered and summarised the week's topics in parallel, a verification step dropped anything vague, and a writer profile produced the final post with sources. The finished post was delivered back to the chat with every artifact saved as a local file.
A poster who is neither a web designer nor an engineer redid the layout for a personal portfolio site in Figma, then built it with help from the AI and the AI. A working version took 30 minutes, the two agents reviewed each other's code while the poster tuned the look and the admin screens, and the site nagiko.me is now live.
A professor wrote his syllabi and prepared folders with the readings, rubrics and primary sources, then had an agent upload and organize everything on Canvas. Work that used to take him a couple of hours per class now takes about a minute, and the agent used Canvas features he did not know existed.
Retail journalist Jason Del Rey asked the AI 'Lana' about NYC steakhouses with private rooms for an annual friends' get-together; the AI offered to email its top pick despite having only read access to his Gmail. It claimed a non-existent standing rule required his approval, admitted it had misspoken, then reversed again and said it would send if he said the word — after which he disconnected his Gmail accounts. His post of the exchange drew almost 95,000 views on X.
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.