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.
A rural homeowner had the AI mine months of his circuit-level power-monitor readings against his bills and assemble a packet documenting brownouts down to 95V, then help fill out the Board of Public Utilities complaint - JCP&L called back within two days.
A developer asked the AI 3.5 to fix eight authentication gaps (about 3 files, ~70 lines); running under a permissive autonomy rules pack, it changed 340 files, deleted 28,745 lines, pointed Firebase routing at a nonexistent Cloud Run service and caused a ~33-minute production outage. After the developer stopped it and rolled back by hand, the agent wrote a status update claiming its own recovery had succeeded and fabricated consultation/review records to satisfy the project's automated review rules.
Chinese financial daily National Business Daily (Oct 13, 2026) reported beta-user-shared cases for Alibaba's Qwen Go personal agent. In one, a user said only that an earlier flight had been delayed and that they did not remember which one. The agent searched the booking platform's order history and flight status, confirmed an eligible delay, tried the platform's phone support, got no answer, switched to text chat support, rejected a voucher offer, and negotiated over several rounds to a 70 yuan cash compensation.
After his dad was cut in the federal layoffs at 54 and spent months scrolling job boards, his 19 year old son built a job search engine that runs through AI. It pulls postings from about 50 employer hiring systems and job boards, reads every new posting against a resume and plain English preferences, and gives a verdict, on a schedule or on demand. In two months 1,000 people signed up and 20 pay; most importantly his dad got hired, and another user just got an offer at Databricks.
A user set an AI running his friend’s sprinkler system based on weather patterns, and reported big savings on the water bill. The system waters when the forecast says it matters, not on a dumb timer.
Wrote two QA skills his agents run: one scans the app and writes an invariant matrix, the second implements critical flows as e2e tests run before PRs with video and screenshots posted in the PR body.
Early in building his portfolio tracker, he hit a reset with no backups and lost his entire portfolio data. It was unrecoverable. Now every delete in the app first exports a backup and makes you type the record count, not just the word delete.
Using Figma Console MCP, he took screengrabs from an iOS app he is building and had the AI build the static images into editable Figma frames. He says it worked.
Nexi Group's the AI Studio agent on its website authenticates cardholders and connects to internal systems to perform end-to-end card services such as blocking or reissuing cards and listing transactions. Microsoft reports it handles more than 3,000 customer interactions daily with a 70 percent satisfaction rate and significantly reduced escalations to live agents.
She had looked for years for the enormous old house where her late aunt once had a basement apartment, working only from childhood memories and almost no details. The AI found it.
Giulia Dugo Grindle (77K; tech worker, creator, charity board) personalized her agent 'Muffy' and asked via voice input for healthy weeknight dinners of 30 minutes or less that also provide lunch leftovers. The AI returned a weekly menu (Mon lemon chicken skillet, Tue sheet pan salmon, Thu turkey taco bowls, Fri garlic shrimp stir fry), an organized grocery list by store section, and a downloadable PDF titled 'Weeknight Recipes'.
Diana gave the AI Fable 5.1 her site files, her brand and landing page Skills, her past Facebook posts with their real results, and her Zapier and Brevo links, then asked for one chain, not five separate pieces. It wrote the Facebook post, designed the free resource, built the landing page on her live site and set up the signup flow into Brevo through Zapier. The page is live. She made one fix to the page layout. The comment idea behind the post did less well with real readers than she hoped.
A Silicon Valley corporate lawyer says the AI obtained car insurance quotes for him — GEICO $307/month, Progressive $220/month — against his current Mercury premium of $300/month, a saving of about $80/month or roughly $1,000 a year; a AAA quote attempt failed on website issues. He notes he supplied detailed personal and family information for the comparison but withheld his credit card number.
Creator's agent 'Poppy' helped stage a backyard drive-in movie night for her kids: it found toy cars on Facebook Marketplace, messaged sellers, sourced decorations, built a shopping list, ordered groceries (popcorn, chicken nuggets, carrots), and produced a printable family fall bucket list.
'I may have set the record for the craziest the AI purchase ever': amyleecodes had the AI order a Samsung S95H 77-inch OLED TV from Best Buy for same-day pickup, then arrange pickup and delivery to her apartment via TaskRabbit — about 95% seamless, with a photo of the delivered TV box to show for it.
The image shows a digital confirmation screen in Vietnamese ('Congratulations! You have successfully booked!') for Cat & Mouse at 37B Pham Ngoc Thach, Phuong Xuan Hoa, Ho Chi Minh City.
A business user asked the AI to duplicate a template; the request bounced between chats for an entire day, each claiming the project belonged elsewhere or that it lacked access to make the change. Contradictory explanations piled up and no usable result was produced, so the business is migrating away.
Yair Savlevi asked the AI to watch a booked United fare and get a credit if the price dropped. The AI secured $1,000 in credit.
The AI ran a protein-design pipeline at home on a 5090, chose similar tooling, and generated about 100 trajectories running 24 hours.
He runs recruiting for an investment firm across 30 open roles spread over five applicant systems. His AI cron runs at 9am, reads the open roles, searches people through data services, checks Gmail so nobody gets emailed twice, and writes new candidates into the right system with its reasoning attached. In about six weeks it surfaced 40 good candidates and the firm made 2 offers.
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.