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.
On day 19 of using her AI Mila, the agent offered three beginner low-impact workout options built around her garage equipment — she did all three — and keeps weekday workout reminders running.
He kept finding papers months late, so he set up a weekly digest with AI. It pulls new papers from Europe PMC, bioRxiv, and Crossref, filters them by his keywords, and puts them on one page every Monday.
A music fan had the AI pull all 17 years of his listening records from his streaming history service, so the data now lives on his own machine. A few days later he had it build a personal browser that shows what he listened to each month, drops one time plays and noise tracks, and lets him queue songs to his home speakers in one click.
Arbisoft says its team used to check more than 2,000 receipts by hand. Now an AI agent flags what can be claimed on its own. The company says review time fell 56 percent and the change saves more than 800 hours a year.
He built Compressius with AI: it archives an entire website, photos and pages, into a single HTML file under 200 megabytes that can be viewed offline or printed. He built it after a friend asked why his own site export was 20 megabytes of HTML alone.
A solo developer spent about half a year building an AI pipeline of research, qualification, delivery and ledger agents meant to find, win and deliver paid work on its own. Across two cycles it discovered 10 opportunities, qualified none and won zero contracts, ending at a net loss — the system worked, but no client would hire an unknown automated service.
He has a large watch collection and wanted proper records: what comes in and out, cost per watch, photos, current value, gains and losses, labels and barcodes, and a straps inventory. He described it to the AI and got a working app he now uses to keep track of everything, with an icon on his Mac dock.
His team runs a fuzz framework that drives a Migration Assistant with Playwright, has an LLM judge results, and files issues back into their system.
The author set the AI on finding the cheapest Broncos Sunday Night Football tickets with seat parameters; it scoured Ticketmaster and resale sites, then kept monitoring pricing every four hours for days. Once the desired tickets appeared, the author completed the purchase himself.
He runs about 15 apps and sites and could not keep track of what needed doing. He connected the AI to his app through MCP, and the AI now creates tasks and subtasks, writes notes, and shows him what is needed by priority and due date.
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.