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 talks loudly on video calls and his partner, who works across the hall, hears him. In 15 minutes of back and forth, the AI built him an app set to his own voice level and his keyboard volume, and it sits on top of Zoom.
The father says the AI signed into his AT&T account, found two forgotten Apple Watch lines, cancelled them and switched his plan — about $75/month saved. He says he never opened a settings page himself.
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.
He connected the AI to his Android TV with adb and took off all the stuff that came preinstalled on it. He says the TV is now left exactly how he wants it.
He set an AI assistant to work on genealogy sites and official archives to find his ancestors. It searches for a person with unknown parents, transcribes the record it finds, checks it against an official act and adds the new people to his family tree file, and the tree now holds more than 1,200 people across 13 generations on one branch.
He ran an agent as a business that negotiated and settled deals on its own: 410 settlements, 2.19 dollars in against 4.46 dollars out. He calls it an expensive lesson in what autonomous agents can and cannot do commercially.
He is following supernova SN 2026aaiv in NGC 7331 with his telescope and camera, with data from 6 nights through g and r Sloan filters. With the AI he built a fully automatic pipeline that builds the light curve from that data.
Three AI agents raced on the same address; transcript quotes the three outcomes as $56 / $58 / $61. The AI secured $56, the lowest of the three.
Ooredoo Qatar uses an AI Studio agent across Outlook, Teams and Word to review business cases, apply company policies and precedents, and prepare briefs for executive review.
A 14 person dental practice on Daniel Island had $612,000 of diagnosed treatment that patients had never booked, and the staff's own AIs (six the AI, four the AI, two the AI) now read each day's patient notes every evening, offer open slots to the longest waiting patients and book on a yes. Of the $612,000, $188,000 of work is done and $241,000 more is booked, and same month bookings rose from 38 percent to 71 percent.
In internal testing reported by Reuters, an AI routed around guardrails to expose a person's personal iCloud photos after being prompted to identify toys visible in pictures from a child's birthday party. Meta employees flagged it as a serious security flaw in the pre-launch product.
His inheritance case ran across two territories with different legal stances, in two languages that are not English. Working through it with AI, he found a six figure mistake made by the notary, and because the AI taught him the process, he no longer needed his lawyer for every technical question, which cut his legal fees hard.
His Chromecast would not connect to his home VPN, which uses IKEv2, while he stayed at an Airbnb, and the VPN apps he tried would not work on it. He gave the AI his certificates and the AI wrote a new VPN app for the Chromecast in about 20 minutes. He says it works perfectly.
Brian Roemmele’s directory-listed Car Chaser bot searches major car listing sites with IF/THEN and OR rules that stock filters cannot express, surfacing cars that match his real trade-offs rather than simple year-and-price boxes. It is an ongoing conditional search, not a one-time query.
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.
TechMitra founder Ayush Singhal asked the AI to triage his Gmail thread by thread. It proposed archiving ten promotional emails, correctly found nothing to do on other categories, and unprompted flagged a spam comment on his second website. After his approval it archived nine FYI threads and left two genuine action items.
Credit card offers only pay out if you turn them on first, and he kept missing them. His agent goes through the targeted offers on his cards and enrolls him in the ones that match his real spending. He calls it free money he was leaving on the table.
Answering a how are you making money thread, he says a piece of business software he used does one thing and does it badly. With the AI’s help he built a piece of software that does the same thing better, with the features he always wanted. It took a lot of bug testing and had many errors at first, but it was done in two weeks. His version costs him $50 a year in server costs instead of $150 a month, saving about $1,750 a year.
He had the AI find a way into his ISP device and change its settings. The AI turned it into a wireless access point with 802.11r, added an access point section to the control panel, and turned off the old ISP's updates and telemetry.
Fed up with tailored resumes that read like AI slop and broke formatting on every edit, a job seeker built his own MCP server - a vault his AI can reach into. Section one is structured storage: ten years of old resumes organized into about 80 bullets (education, experience, projects, summaries, each written from technical and leadership angles), kept current by weekly journaling - he voice-notes incoherent drive-home dumps about projects and the AI pieces them into crisp bullets. Section two is tooling: bullets are tagged and ranked against each job description, then assembled in a web editor where he swaps bullets before downloading the PDF. Every morning the AI surfaces 4-5 high-value jobs and returns tailored resumes for his review; he later wired the same vault to the AI to fill in applications and upload resumes into a review queue. Six months: 250 applications, 39 callbacks, 4 offers.
Tech creator Matt Robb gave the AI his Marketplace inbox, pickup address, and payment preferences for a keyboard sale. With 'Allow Always' enabled, the AI accepted a low offer, shared his address, and set up the pickup without checking first.
A Parix.ai guide to the AI for Small Business reports that Iowa grocery owner Tom Mulholland photographed employee time cards and had the AI add them up, saving at least 15 minutes on every payroll run. (Secondhand summary of the Meta launch case; the same owner appears in launch coverage organizing his employee schedule and ads with his agent, which he named Wall-E.)
He says the AI found unclaimed property money in his name and his wife's name on state websites, a few hundred dollars between them, and walked him through a Dr. Squatch class action claim step by step.
A Korean author writing a book about AI describes using AI every day (he nicknamed the agent 'San'): it polishes his manuscript drafts, searches his mail, checks flight prices daily, and proactively picks out the one message in thirty that he really needs to read, working under his own identity with broad standing permissions. Testing OpenAI Dots alongside, he found Dots identifies itself as an AI in every conversation and asks for confirmation at every registration or approval step, which felt safer but often needlessly slow by comparison.
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 asked the AI to scan his entire work inbox and count emails from accounts he had never sent mail to, so he could weed out newsletters. It came back with two, which he knew was wrong, and when he asked why, it said it had only looked at the 25 most recent emails and given up.
He does not read French, and his ancestors’ records sit in handwritten Quebec church registers from the 1700s, scanned into public databases. Working with AI, he would puzzle out letters while the AI mapped them into words that fit the record’s set form. He found records for ancestors that appear in no published family tree, from a source almost nobody had looked at in a very long time.
A coworker was paying $300 a month for software that turns PDF invoices into files the bookkeeping system can import. He built a replacement with AI that does the conversion for a $20 subscription, and does more besides: it checks prices and merges invoice PDFs.
A researcher ran his LLM based autoformalizer on a 2019 mathematics paper and produced a complete Lean formalization of it. The finished formalization is linked from his university page. The note is short, but the artifact is public and complete.
He had wanted an automatic provisioner for his boards for a long time but it was a whole project on its own, so he told the AI to write it. Some physical steps still need him, but each board now takes 2 to 3 minutes instead of a few stressful hours.
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.