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 worked in SEO since 2009 and has no coding background. He shipped a SaaS with paying users anyway. His rule is that a different model reviews everything the AI builds, and that habit once caught 14 real bugs while all 10 tests were green. He liked the workflow so much that he turned it into his product, MegaLens.
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.
Has 14 applications in production completely managed by AI agents he deploys, externally inspected for security and accuracy.
A testimonial graphic quotes someone: 'my first money with someone — connected my email, asked to find all flights I had in last 5 years, find the ones that were delayed or cancelled.' The agent mined years of inbox history for compensation claims.
For a few weeks he has had the AI take over his cursor, open Clip Studio, and put the words on his comics. He still makes small fixes himself, and it saves him real time on the dull part of the work.
Creator someone gave the AI her Florida bucket list. The AI booked a 9pm reservation for two at Japón at The Setai via OpenTable, then booked a beach horseback ride plus dinner afterward.
His studio runs much of its back office on agents, each with its own instruction file. The email step reported success on sends that had failed, and they later found 44 messages still sitting as drafts. Scheduled jobs were marked done before their output existed, which cost five deliverables in one day. They fixed it with a plain check after each risky step: after sending, look for the message in the Sent folder; before marking a job done, check the file is actually there. Now only a failed check needs a person's eyes.
He pointed the AI at a downloads folder with over 1,000 media files and at his Jellyfin library. The AI made a queue file he could import into HandBrake, and he says it saved him a lot of time.
A business owner's lead profile runs every Monday on its own. It formats his warm leads, finds cold leads that match his criteria across a rotating list of cities and niches, then digs into each business to find what he is missing, owner names and exact contacts, checked against business registries. He gets one standard weekly report: best fit clients, outreach details and the facts to judge each lead.
He had the AI work out how the When2Meet scheduling site works and turn it into a skill. Now the AI can read his calendar and fill in the When2Meet availability grid by itself.
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.