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.
Eleanor Konik had the AI and AI team up on dashboards for local nonprofits. The AI did the early research and dug up grant chances the groups had not seen, like a group that pays for field trips to battlefields, a free textbooks program for private schools, and creative arts projects, and the lists were put behind a password for her friends to use.
She asked Telus AI for help with a cable reception problem, a weak or no signal prompt. Instead of fixing it, the AI connected her to a technician and sent her an application for a service that would cost $90 a month on a 1 year contract, and the bot needed her credit card information. She said no.
He used AI to write assembly and create a Franchise Mode from scratch for the Ken Griffey SNES baseball game. The mod also adds 2026, 1994, and original teams and rosters, which meant doubling the size of the ROM.
Simmons asked László to learn his Zone 2 method from his training community and analyse three months of pace and heart-rate data ahead of the New York City Marathon. Finding Garmin's API needed a developer account, the Dot signed up for Intervals.icu on its own, pulled his runs, built a dashboard called Steady and set up post-run messages.
A man gave the AI strict tag research tasks and had it work through the whole ticker list again and again, searching and comparing XBRL tags in SEC filings. The pipeline now pulls 10-K and 10-Q filings for more than 600 companies, maps tags onto about 35 financial concepts, and produces cleaned data. Doing 3 tickers by hand had taken him about 3 weeks and still gave wrong data.
A self-described 'personal CFO for wealthmaxxing couples' on Facebook built an AI named 'Cupid' that stores her and her boyfriend's income, strengths, and goals, then proactively reminds them each month to have a 'money date' — bridging her moonshot-entrepreneur style with his investment-savvy approach.
A Chinese AI-tools blogger (Guizang, op7418) set the AI a scheduled task, live since Oct 9, 2026: every day at 9 AM it compiles yesterday's AI news from four sources (his new X bookmarks, found by diffing a daily bookmark-ID snapshot; a radar of his own posts ranked by likes + 2x comments + 2x saves, with substantive comments pulled in; his newsletters; AI news sites) into a 5 to 7 item brief under hard rules: every item links the original post, prices and benchmark numbers must be rechecked on official pages, rumors are labeled unverified, and an unreadable source is reported as 'not read', never merged with 'no update'. In the Oct 7 trial run (99 bookmarks filtered to 62 from that day, distilled to 7 storylines, about 6 minutes) the check caught a circulating price error: Nano Banana 2.1's 4K price was $0.113 on Google's pricing page, not the widely shared $0.076. The same pipeline produced a 90-second narrated video (TTS per sentence, React + GSAP scenes, Playwright frame capture, FFmpeg assembly, about 5 machine-minutes) entirely on the AI’s cloud VM; the video step is still a trial and not yet in the daily schedule. He published the full reusable prompt and his three open-source skills.
Engineer AJ Stuyvenberg let his AI handle his 2026 Hyundai Palisade purchase by email, and it played dealers against each other over several days. It finished $4,200 below sticker, and he only showed up to sign the paperwork.
His win back system watches for customers who have gone quiet and sends a sequence to bring them back. Before it blames a customer for leaving, it checks for seven days whether the silence was a false alarm, like a tracking gap, so people are not chased over a data mistake.
Allie K. Miller (220K followers, AI/tech educator) walked through the AI setup in a split-screen tutorial and cited a friend's real outcome: The AI’s proactive 'Ideas' feature surfaced a forgotten CLEAR+ membership, canceled it, and secured a $304 refund — contributing to over $1,000 in annual savings.
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.