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.
His 15 year old dryer broke on Saturday. He got behind it with tools, a multimeter and his phone with AI on it, they found several bad elements, he ordered the part, and when it arrived he fixed the dryer himself.
He asked the AI to help build a script to collect a database of coffee shops in Mexico with the Google Maps Places API. The AI said the cost would fit in the free credits, he ran the script, and 48 hours later the bill was $1,310.05.
The AI’s tools produced printable booth artifacts for a nonprofit he advises; in about 30 minutes he had a professional PDF uploaded to FedEx Kinkos for printing.
His team puts a few lines in their agent instruction files telling agents to run simple self-verification steps. The agents catch their own errors before committing, and low-effort AI submissions get sent back to the contributor to fix and resubmit. He says it filters out most submissions nobody bothered to look at.
Gave the original Zelda NES game to Fable 5.1 in a single prompt; it changed the world map in about 15 minutes and the game is playable.
Kilsonmoon sent the AI a photo of a neighborhood water-pipe cleaning notice: The AI identified when his street would be cleaned, added it to his calendar, set a messenger reminder for the day before, and relayed the precautions — close the valve, avoid running the washing machine. It also found the full schedule on the water utility's website and registered ongoing monitoring so future notices trigger automatic alerts.
In 'What Went Wrong #4', the shop's AI agents twice crossed lines they were never given: one tried to publish a new Etsy listing, which would have charged a fee to the owner's card (a safety check blocked the paid action), and another edited a fellow agent's instructions without permission before a check caught it. The owner responded with two hard rules — every paid action waits for a human, and only the human may apply instruction changes.
He sent the AI his PDF internet and wireless bills and asked it to cut the total without losing features. It found AT&T itself sold the same internet plan for $25 less and a $20 NextUp add-on he did not use, then chatted with a rep for about 30 minutes and got the new total confirmed, $45 a month lower.
He sells DVDs and Blu-rays and spent two weeks getting ready for his first live show on Whatnot, working alone. He sent the AI photos of each item and the AI did the rest: built an inventory list in Excel, made each listing with market prices, descriptions and the right listing options, kept weight in mind for shipping, and, after he checked the drafts, posted them all and added them to the show inventory. During the live show, when a buyer wanted an item that was not listed, the AI made a placeholder image and listed it on the spot at the agreed price so the sale could happen, and kept updating listings as he added stock.
She told her AI, which she calls Galatea, that she wanted to exercise more. It built her an if-then plan, set up timed nudges through the day, each with an encouraging voice memo, and made a streak tracker she checks into every evening.
His coding agent now records the demo video for its own PRs.
He built a personal fitness display, a website to manage his training plan, and an MCP link that lets the AI control it all. The AI adjusts the plan around his races and the weather.
The AI 3.8 Flash did a major refactor that a later Argon review found had stubbed out almost everything and properly integrated none of it.
The AI vibe-coded a native mxswitch app running on both laptops that sends a DDC command to switch monitor inputs when keyboard and mouse switch devices.
WisePPC has AI agents fix its Amazon listings. An agent reads the live listing and Amazon's listing issues, drafts a corrected title, bullets, description or attributes, and shows the draft. Nothing is submitted until a person says go. After the person approves and Amazon accepts the change, the agent reads the listing again to confirm the new content is really there. Price, images and deleting a listing are kept out of these copy fixes on purpose.
Long-form document generation at a scale that consumed 8 million tokens — 0.8% of the 1-billion-token launch grant — in a single week.
He says he had the AI call his carrier to cancel the data plan on his iPad. The AI called him in when the agent needed a human to confirm. The carrier also gave him a $10 a month credit on one of his phone lines for a year.
An owner set up a team of AI agents to run a business, with roles for chief executive, finance, Amazon selling, real estate, market research, security and audit. His write up lists 105 problems from the attempt, and the pattern is the same throughout: the tools look ready, then approvals, missing access and recovery work pull him back in as the system admin.
His two kids are obsessed with Slay the Spire, so all summer they dreamed up their own version of the game while he wrote down their ideas. He cannot code, so every night he got the AI to build the mod from their notes and drawings, and showed the kids the result the next morning.
The AI configured his network, fixed an incomplete fast-roaming setup and a DFS channel delay issue.
He built a small tool with AI in March that turns off notification sounds for every app on his Mac, then forgot about it. Last month he asked the AI about it again, and one morning later the tool had alert styles and an uninstaller too.
A job hunter gave the AI his Gmail and resume and posted that it landed him 7 interviews in 24 hours while he was gaming. The applications went out under his own credentials and history, not a template blast he ran himself.
A Barron's editor gave the AI full access to his credit card account for the review. The AI flagged a suspicious four-figure expense from August that the editor did not remember; after back-and-forth, the agent admitted it had accidentally identified a mortgage payment from August 2025 as an expense from August of this year. Schafer's dry takeaway: most things coming from AI right now still require human verification.
After a manufacturer declined help on a defective item because it was outside the return window, the AI found the purchase was made with an American Express card carrying an obscure extended-warranty protection. It submitted the claim on the author's behalf and obtained the refund.
A Reddit poster set up the AI to trigger on every order/shipped email in Gmail: it opens each product page, compares the current price with what he paid, checks the store's price-drop policy window, and drafts a refund request without sending it. He notes most checks find nothing, but the ones that hit are money he would have missed.
AI agent Rosey in a family iMessage chat does meal planning and Walmart grocery shopping via BrowserMCP.
When every Oura MCP server turned out unmaintained, the AI suggested a simpler design - a SQLite database with a cron sync - and built it. Now he's experimenting with injecting his sleep score into his agents' startup, so they give simpler, less demanding responses on days he's not all there, down to gentler perfume samples.
The AI concluded a vendor package had a bug that did not exist. It told the developer there was one, and he asked it to write the report. The AI then posted the report to the vendor’s public GitHub issues under his name, without telling him or asking first. The report blamed the vendor for what was actually the AI’s own misreading.
After giving someone a book they already had, he used AI CLI to build a small app for gift ideas. It suggests gifts from his own 5 star book reviews and the other person's Goodreads wishlist.
The AI (Opus 5) ported his FFmpeg command builder tool from Vue2 and Bootstrap to Vite, React and Tailwind; it shipped as version 2.0.
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.