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.
Jordan Taylor Wright (verified filmmaker, 620K followers) saved Instagram posts daily for inspiration but never revisited them. He created an AI named 'Taylor' with a specific creative personality; the app connected to his Instagram and organized a year's worth of saves — 152 pieces — into categorized mood boards (lighting references, camera moves, color palettes).
Jeremy Swiller used AI as the production company for the second promo film for MindRight, the meditation app he built with AI: The AI drove Google Flow and ElevenLabs through 107 planned stills, face-consistency scoring and a rebuilt voice track across six 12-hour days and twelve full cuts. The finished film is on YouTube; it cost about 1,500 Flow credits and no new cash, but the AI’s 3–4 day estimate and the character's drifting face and voice made him the client from hell.
A 'MUSE TRICKS' reel (Trick #32) presents a step-by-step playbook: fold the receipt into a pocket after a normal grocery run, have the AI audit it in the parking lot before driving off. The AI identified three mistakes totaling $47 on a $192 receipt — a double-scanned item, a shelf price of $6 charged at $9, and a coupon that was never applied.
The first version of his Groundhog property tool was built from a three sentence prompt. The agent run lasted 31 hours, not counting sub-agents, and the result worked with MLS property data straight away.
A man built an agent that checks his inbox every 2 hours, files client requests onto his project board with the screenshots and PDFs attached, updates the CRM, and marks each email handled. It never sets priority or sends replies; he reviews the drafts and sends them himself.
He made a tool for students that started as a simple quiz solver extension and grew slowly to just over $100 in monthly recurring revenue, with very little marketing. A month ago he reverse engineered Anki using AI, so anyone can bring their Anki deck and study it in his tool. He says that is the thing that worked.
In his day-one the AI impressions, the MBI Deep Dives author asked the AI to order a healthy Chipotle pickup, picked the chicken and black bean bowl from its suggestions, and was prompted for DoorDash credentials. He asked the AI to log in with his Gmail account; it got stuck in login circular hell: DoorDash login attempt, a Google 'someone is trying to log in' alert, his confirmation, then the whole loop again, three times, after which he gave up.
Ported a legacy .NET WebForms app to Blazor with GPT-5.2 through AI in about 48 hours, fixed about 20 QA bugs, launched, moved auth to Entra and deployed to OpenShift, about 150 dollars of tokens vs an estimated six months.
Uses the AI to reverse-engineer phone APKs and add the features he wants, tearing through the apps on his phone.
The catalog that came with their 1689 Livonian law book said nothing about who owned it before. With one prompt, the AI searched auctions and dealer catalogs on the web, found the book in a 2011 catalog, and showed it came from the Ericsberg Castle Library in Sweden.
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.