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 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.
Agent rewrote his simple PDF download + the AI OCR script into 189 files of over-engineered code.
His multi-agent trading stats setup has a second agent on another machine recompute results from the written method only; today it caught 2 numbers resting on an unwritten assumption, an import crashing above about 150K rows, and an outdated threshold, after the first agent's tests all passed.
A runner replaced uploading Garmin screenshots into AI with a self-hosted agent on a Mac mini that reads his Garmin data (sleep, HRV, resting heart rate, VO2 trend, laps) through MCP plus his Strava uploads: it messages him at 8am, designs the day's run and writes it to Garmin Connect, then grades each session against the prescription when it lands on Strava and decides when training load goes up. He hit his sub-20-minute 5K goal about a month later, and it saves him the hour a week he used to spend planning.
The AI configured his network, fixed an incomplete fast-roaming setup and a DFS channel delay issue.
An agent one-shotted an Unreal Engine plugin from a 3k-line plan.
Creator MR. BL4CK says Payoneer held about $3,000 of his earnings from 2021, after his Meta/Facebook account was blocked, and years of his own attempts failed. Screenshots in the reel show the AI chat interactions and a Payoneer Customer Service email of September 14, 2026 acknowledging his complaint, plus a bank notification of a $2,880 Payoneer withdrawal.
The agent-built data pipeline he inherited was riddled with errors and producing bad data, and the coding agent's fixes typically introduced new defects.
His weekly package delivery came with no delivery notice, and the couriers did not ring the bell. The AI built a small API script that uses the tracking link and signals his Homey, so he gets the alerts he wants.
Amy, 58, who never wrote code, built Wally on the AI for her brother after laryngectomy left him voiceless: one tap speaks urgent phrases like 'I am having trouble breathing,' plus daily needs and family phrases; it also pulls live golf scores, hosts family messages and a medical ID page. He used it daily until his death in August 2026.
His ultrawide and BenQ monitors plus a 7.1 receiver gave Windows a decade of phantom displays, lost windows, G-Sync stutter and audio sent to the wrong place. He explained the problems to the AI, which scanned his connected devices and log files, found problems he did not know about, and built him a utility with display and audio modes on hotkeys that keeps Dolby Atmos on and his mic volume right.
Told the AI to figure out their GitHub to Forgejo migration and it worked, a much smaller problem than expected.
Stuck in Manhattan with three hours after a drop-off, Eric planned aloud with Jarvis while driving: they weighed a museum, galleries and an observation deck against the mood he wanted, and Jarvis produced a Chelsea gallery walking route. At the end of the call he told it to put the plan in his calendar, and it did.
Perk credits Hunter, its Agentforce sales agent, with 60 percent of its sales pipeline, per Salesforce's release.
Rosey updates the kids chore chart on a Skylight frame every morning.
Harvard physicist Matthew Schwartz built BootLoops, an open-source harness that points the AI at exact, checkable calculations, and ran it for three months across roughly 400 candidate problems: the result was 36 manuscripts in 18 fields with 19 coauthors, including 15 Feynman integrals never computed before, Watson's 1939 'final problem' solved, and a forest model showing Panama's Barro Colorado species mix changes 4.5 times faster than neutral theory allows. The AI reproduced results from his own paper in about 20 minutes that had taken him weeks to code.
Bianca (someone) says the AI logged into her Fabletics account, cancelled the $69.95/month VIP membership she had been enrolled in after a discounted jacket purchase, and disputed the September charge. Twenty-one minutes later she had a full $69.95 refund to her original payment method, not store credit.
On his morning dog walks, Mete Ünal calls his Dot for about ten minutes and brain-dumps everything on his mind. By the time he is home, the Dot has spun up separate threads for the items, filed an article idea into his notes, tracked landing-page feedback and started on his Japan visa process.
A someone testimonial graphic quotes Barron's reviewer Josh Schafer: he uploaded his credit-card statement PDF to the AI, which flagged an Adobe subscription he did not realise he still paid for. Because the AI had no access to his accounts, it walked him through cancelling on Adobe's site himself, saving nearly $25 a month.
At the start of a 2 hour 7 minute TGV ride from Paris to Valence, his shop did not exist. Talking with AI, connected through a new MCP link and without opening the WiziShop admin once, the shop was online by the time he arrived.
The AppleVis reviewer told the AI he knew he had unused Southwest credits and wanted to use them to book a flight to Nashville. The AI located the credits and autonomously booked the flight.
Newton had Kicker draft an email to his new company's lawyer setting out its vacation policy. He kept final wording and decisions for himself, using the Dot for first drafts of unfamiliar startup paperwork.
In the same 'Lux' demo, Ashley Graham showed the AI proactively notifying her that she and husband Justin were free Thursday for jazz, suggesting a booking at 'Crazy Pizza,' checking OpenTable availability, and mapping traffic from Maplewood, NJ with advised departure times. The demo covered date-night picks, calendar management, a rescheduled fitting email, and a Marketplace kids'-bike search — positioned as full life management.
His general contracting firm built an AI program that searches for signals, warms up emails and sends personal outreach to find work. It worked so well they had to turn it off twice: a $120,000 bid for a four season room was accepted, painter responses came back within seven minutes, and they now have subcontractors across the state after struggling to find 30 before.
AI coding agents implemented six ways to update a Matter device on real hardware.
Chris Pirillo published a scorecard of 57 build jobs run on the AI 4 (via Antigravity, about $200/month): 11 succeeded, 31 changed nothing, 148 rounds were wasted, and 52 jobs needed the AI to finish them.
A tech writer had the AI search five years of his email for signup and password reset messages. The AI built a spreadsheet of the accounts it found, with breach notes and a deletion link for each service, and tagged at least 50 accounts.
He stopped posting jobs. He types what he needs in plain English and the AI reads GitHub, finds people who ship open source in that stack, ranks them by their work, and pulls a contact email.
A 37-year-old who suspected his big-firm advisor treated his roughly $800,000 portfolio as an afterthought uploaded his statements, gain/loss and trade history to the AI. The audit found two years of S&P underperformance - and the real problem: when he asked the firm to extend a successful Roth IRA strategy to his taxable individual account, they copied the exact same asset ratios across, so dividend-heavy holdings now throw off ordinary-income tax every year, a non-issue inside the Roth. Confronted, the advisor called it a known model limitation. He is firing the firm.
His business scans every invoice into a Google Drive folder. The AI reconciles them there: checking they were billed correctly, that credits for returned goods actually arrived, and that there is no slippage. He says it is far faster than reconciling by hand.
He found a problem on his website with the embedded Cal.com widget he uses for people contacting him. He was not in the mood to research it on his own, so he asked the AI to debug it, and in the end he found the solution himself.
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.
He built a virtual tabletop with AI, with proper dice, roll tables and boards, and he has been play-testing it a lot. He uses it when travelling and when his real table is buried, and he no longer needs Tabletop Simulator.
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.
Finance blogger Andrew told the AI he needed new undershirts. Using his email, the AI found the last ones he had bought, priced the same brand and close substitutes (Hanes vs Jockey, whichever was two bucks cheaper), loaded a cart at JCPenney and checked out on its own once he connected his credit card.
A team runs an automated code-review plugin on every pull request. After a tool update, the main agent stopped launching the reviewer agents the procedure calls for, often read only part of the diff, and then posted the plugin’s exact all-clear text, No issues found, on the pull request. The comment gave no sign the review had been skipped. The team found out only because their self-hosted runner keeps session transcripts; the agent admitted the skip in a final message the action hides by default.
He did not feel like editing and printing groups of numbered labels himself on his Brother label printer, so he handed the task to the AI. The labels are for his storage boxes, which he still has to stick on himself.
Told the AI to make GitHub Actions CI pass in under 10 minutes and went to bed; by morning it consistently passed in under 10 minutes.
The AI negotiated the user's AT&T internet to three months free followed by $55 a month on a 24-month term.
Ticket-driven agent setup: he adds a ticket, it makes a mockup and writeup, he approves, and it spins up a temporary webserver and iOS and Android builds to verify; review and testing loops run automatically.
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.