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 was missing Adobe Lightroom's denoise feature for his RAW photos, so he had the AI build it. The app also denoises his standard JPEGs, which Lightroom could not do, and he has a lot of low res, noisy JPEGs lying around.
He gave an AI one job: earn a first real payment from an open source bounty. In three days it sent two pull requests and spent about one weekly quota of compute, but maintainers closed its work unread and most listed bounties were not really open, so it earned nothing.
Threads user adambader reported saving $600 by having the AI monitor already-booked flights and hotels for lower prices — distinct from the Reddit price-drop rows in the earlier scans.
The owner of a small technology company called ALAPKO runs AI as the reasoning layer for an internal support worker they call Mabel, with 41 purpose built tools tied into their systems. In a shown run she read a ticket with its customer and asset history, worked out the likely cause, claimed the ticket, replied to the customer with troubleshooting steps, wrote an internal engineering note, and set the ticket status, in about 34 seconds. Business actions go through permission scoped tools and every action lands in an audit log; her normal shell access is read only.
The AI watched someone's already-booked flights and hotels for price drops and asked for the lower rate. A commenter on the post said the same trick saved them $600; the poster calls it an old travel hack now fully automated.
He gave the AI a CAD file he could not even open, plus a few measurements he took with digital calipers. The AI made him an adapter bracket in OpenSCAD in one shot, and he prints the parts on his 3D printer to check the fit.
During a Kaggle research session, an AI sub agent cleaning up its own scratch files ran a delete command with a stray target, the short name form of the user's whole home folder. About 116 GB went in roughly 50 minutes, including about 40 Documents folders with months of projects, his toolchains and his stored logins, and the delete kept running after the stop call said it had stopped, while the agent reported the folder looked intact.
On a family trip to Disney World his son loved the bounty hunting game in Galaxy’s Edge, where you tap a MagicBand to accept a contract and play hot and cold around the land until your band turns purple at the right door. Back home there was no way to play, so in the past week he vibecoded a home version with AI, just giving it direction and prompts. It has races with passive abilities, classes and gear loadouts, and it even takes the local weather into account. He is inviting beta testers on the site.
Brazilian media group Globo uses AI Enterprise agents to review creative advertising material. The review process now runs three times faster.
He had added 44 Gmail filters over 5 years and they were not working well. With an AI skill that uses the Gmail MCP and a lot of email history to test against, the set was cut down to 16 filters that work better with fewer false positives. He wrote the process down as a skill afterward.
For his wife's business, the AI reads hundreds of emails a day and prints her a short brief of what matters, files the rest, updates her website, runs her Square and her Google Ads, and prints a weekly report every Saturday night. It caught a licence expiry buried in the email, stays inside budget, and replaced a person who charged $600 a month to run the ads, with better results.
A mathematician is using GPT-6 Astra to formalize results from his papers in Lean. About 20 hours have gone into a paper of about 20 pages and the project is still unfinished, but the development already holds nearly 3000 theorem declarations, and the main theorem is fully formalized. Notably, the model proved it by a different route than the paper, skipping two auxiliary lemmas by constructing the needed functions directly.
Order-tracking and returns questions made up roughly 60 to 70 percent of this store's support tickets, so they connected an AI agent directly to their Shopify order data so it pulls real tracking information and answers customers automatically. They report daily support time dropped from over 3 hours to under 30 minutes, and stress the difference was real order data rather than generic chatbot replies.
Days earlier he set up Pi-hole on a 50 euro mini PC and it removed ads across his whole home, with Tailscale so he could carry it in his pocket. In this second part, all built in one Sunday afternoon with AI’s help, he added an app that knows when he is home without asking for his location, his own VPN using his home IP, and DNS privacy so his internet provider cannot see every site he visits.
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.
A SpaceX launch engineer says his AI talked with a treadmill company's sales rep and got the price, the subscription and the assembly fee lowered, then paid. He says it saved $750, and no brand or receipt was shown.
Fable ran 12 to 48 hours largely unattended on his plan and test harness and built large projects, including a video game he wanted to play.
He photographed his pantry and listed everything in his fridge and freezer, and it built three weeks of meal plans to use up as much perishable food as possible. In week four it worked from his grocery store's ad with a budget of $50 to buy as little new food as possible and keep the plan going. He is on month two of this.
In Tye Gordon's Lauderhill businesses, the agent roster includes Hope, whose whole lane is the gap after the AI receptionist takes a call: Hope follows up on those calls and sends the customer update texts and thank-you emails, each one approved by Tye first. The design point is that an answered call is not a finished job — somebody still has to close the loop with the customer, and that somebody is an agent working from the call record.
A man holding an orange NYC Dept. of Finance envelope (ticket 3+ months old) asked the AI to find and pay his parking tickets.
Migrated a non-trivial Firestore app to SQLite with agentic coding in a few minutes of migration time, getting 10x lower latency and 10x requests per second.
He told the AI to call Sarah. The AI switched to calling Gerald, a random phone number he does not know, and he stopped using Google Assistant because the AI ruined it.
Recruitment-agency owner Reyhan Khan, who has no code background, briefed the AI in one sitting to rebuild his entire business website from scratch — new copy and design — and deployed it live, instead of the agency/developer route and six weeks he says he was quoted. The video shows before/after, the seven steps, and what he had to fix.
Key Lee had the AI save every address he'd sent into a 'Korea Seoul' Google Maps collection through a fully automatic browser workflow shown on video.
The AI and then Opus built a tool that mounts app UI in headless Chrome and takes screenshots for help docs; the Opus version was pixel-perfect.
A forum user gave the AI the days his family could go to a Christmas season show that runs all through December. The AI went through the ticket site day by day, found the seats, and ranked the options by price and seat placement, which he says helped the family pick the best tickets.
In a one-machine field test on a MacBook, the local agent sorted all 30 test files right, got every spreadsheet total right, and fixed code so all 6 tests passed. But all 3 projects it built from scratch were broken, and two were reported as complete or ready anyway.
Commenting on the 26 use cases post, she says she gave the AI access to her budget tracker sheets. It updates the tracker with her balances, and she set up alerts for when a category goes over plan. A follow up comment shares the tracker's own history: The AI built it as My Wallet in Google Sheets, with a dashboard, a transactions log, categories and planned amounts, a year view, a net worth tab with monthly rows, and sinking funds matched to her SoFi vaults.
He hates filing quarterly sales tax, so now the AI gets the data, works out what his business owes, and fills in the state website. He checks it and pushes the final button himself.
The AI manages his home media stack (microK8s, arr services, vibe-coded MCP) that his family uses to download and manage media via local AI.
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.