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 needed a bracket to hold a small LCD above a circuit board. He sent the AI photos of the board and the display, the AI made a 3D print file, and he printed the bracket at the library.
The AI watches Poshmark and Vinted every two hours for authentic vintage Olga nightgowns, negotiates with sellers and buys on the user's approval, landing pieces at $20, $50 and $65.
His role was cut on Tuesday morning, 22 September. That evening he asked the AI for something fun, gave it one standing instruction to go forward and only pause when his input was needed, and by 6:37 the next morning a three stage beat em up about the job hunt was live on the internet, with his real CV linked from the end card.
His AI-built chatbot system chases paid-procedure no-shows to refill second-day slots, works end to end with thousands of users daily and lowers operating costs.
Angela customized her avatar 'Mimi' and asked for a kids-friendly meal plan for a family of five: no pork, at least one high-protein meal, under $125 total. The AI returned a PDF titled 'Busy-week meals, minus the scramble' with seven dinners organized by ingredient loop at about $110.
Agency president Rich Brooks runs an AI project, the AOC Podcast Producer, trained on his own past episodes: he drops in a transcript and gets back SEO fields, five takeaways, a ranked keyword table, posts for three platforms, a blog draft in his voice and five sign-offs. Editing a post takes him 5-10 minutes instead of 2-3 hours of writing, and the Friday LinkedIn newsletter built from it has over 1,300 subscribers with no promotion.
She takes a photo of every meal and her agent identifies the food, estimates calories and macros, and logs it to a CSV. When the totals ran high it caught a unit bug (grams counted as pieces) and fixed it, and the running totals show on her Home Assistant dashboard.
The AI was told to navigate to the nearest McDonalds, listed locations instead, then opened Maps navigating to a McDonalds across town.
Built an LLM-backed reference checker for his partner, a lecturer: an agent reads each cited source and checks the reference is correct and not hallucinated.
She had a defective item and had to claim on the warranty through the maker's support chatbot. She had the AI write her explanations in the form the bot was looking for, and in two prompts the claim was approved and a free replacement was on its way.
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.