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.
Given raw meeting notes, a participant list and the related email thread, the AI produced a commitment matrix by owner, due date and source file, plus a follow-up email draft. Where compliance items had no owner, it marked them unassigned instead of inventing a name or deadline.
The maker said his new Leica DISTO D2 laser measure did not work with Linux. He and the AI worked out how to connect it to his Linux computer anyway, so he can capture data for his new apartment.
Pointed a fully local agent at his collapsed Pleroma instance that had run out of storage mid-upgrade; the agent got it back up and running.
Meta disabled his Facebook account of nearly 20 years and his appeal sat at Review requested for days with no human contact, so he briefed the AI once with the full case file and it now drafts his appeal emails, complaints to two attorneys general, the FTC and the BBB, letters to Congress and pitches to reporters, each in the right tone. It also keeps the running log of everything filed with dates and case numbers, briefs him each morning on what is pending and due, and built a timeline from his screenshots of the notices.
In shipwithmuse.live's errands catalog, one 'finding money you forgot about' entry reports a full sweep of every state's unclaimed-property database by name and past cities, which turned up $88.92. The catalog notes it was as reported by the build author and not independently audited.
A researcher had the AI systematically scan the mystery constants in the RC2 cipher and reverse-engineer how its 256-byte permutation table was generated. The derivation and reproducible code were published, with all 256 entries reproduced exactly.
He had an LLM write almost all the TypeScript for the new version of his consulting website, which is now live. Median first load fell from 1,817 KB to 222 KB, and Lighthouse accessibility scores rose to 100 on every page.
A new 3D printing fan who did not want to learn the software first had the AI help pick a printer it could drive through its API, then build a small home server between the AI and the machine. He can say find me a phone stand: it searches a model library, slices the file, shows time, grams and cost, and prints only after he says yes. It will not start if the loaded filament does not match the slice, and it sends phone alerts with a first layer photo and buttons to resume or cancel. His partner can request prints through a chat page, which he approves. A firmware update broke the camera setup and the AI found and fixed it.
Spent half a day switching GPT-5.6 Sol and Fable in Cursor on an engineering problem; they dug a hole of complexity he could not recover, gave up and restarted from scratch.
Setting up the Instinct assistant live on screen, he had it book him a slot at his local recycling centre. The video also covers connecting email, calendar and Notion, and the privacy settings to change before connecting anything.
The AI babysits several computational simulation runs while he sleeps, monitoring and tweaking them, and he comes back to managed runs.
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.
In one Saturday his AI assistant moved his newsletter to a new home, 92 posts and 798 subscribers, and drafted the new issue and a talk for Thursday. It also edited 10 versions of a vlog teaser, planned his 10 year anniversary trip, and reminded him about a $1,200 trade-in he had forgotten.
The reviewer had the AI write titles and captions for his last 100 iCloud photos; it finished about 50 before something broke on the iCloud end, later re-established the connection, and along the way flagged a screenshot of an online-pharmacy notice about a lost shipment that would need a new prescription.
His company runs three coordinated agents on its product account: one watches mentions and a watchlist, one writes posts and replies, and one controls quality. Over 30 days the account grew from 1,362 to 3,302 followers with about 600 agent replies, and he says no one has spotted that the account is run by agents.
He used AI with a browser add-on in Brave to clean out his Gmail. His account now has about 50% free space.
Wired up a replacement for needed functionality with AI over a couple of weeks, avoiding tens of thousands of dollars in recurring yearly costs.
He uses an iOS app the AI made for him. When it feels slow he sends a screenshot and notes through TestFlight, the AI is told at once and ships the fix in the background.
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.
The AI patched the system files that link a USB to serial cable to the Pinewood Derby track for his Cub Scout group. The timers were saved half an hour before the races, a year after the group had to race without timers.
A real estate broker said her AI assistant nurtured leads for months and booked showings on its own. She closed 4 deals with buyers she never spoke to until the showing.
Myra Chiasson (98 followers) described the stress of 'what's for dinner' with a picky-eater child plus her own protein goals, and presented her 'mom hack': The AI automatically generates a personalized weekly dinner plan every Sunday at 8 AM, with a new menu and grocery list accounting for dietary restrictions, preferences, and kid-safe foods. On-screen text reinforces 'personalized dinner plan for the week' and 'Stress free dinner FTW.'
Told the AI to figure out their GitHub to Forgejo migration and it worked, a much smaller problem than expected.
He set up saved searches on Cars.com, Carvana and CarMax with his makes, models, price, year and features, and favorited cars on each. The AI merged them into one list, checked price guidance, mileage, consumer reports, recalls and reliability, named his ten best and ten worst, and removed the bottom ten from his favorites. They repeated the rounds until the list was tight, then refined by color and features. He test drove two cars from the list. While he was out, the AI checked the stock of two dealerships he drove past, just from him naming the brands nearby, and found one more match. Every morning it reruns the searches, removing cars that sold and adding new ones.
Said asked the AI to find every locksmith in a city for Partexia and pull emails; he sent 15 personalized outreaches and one business replied asking for a call.
The AI built a halftone web tool, rewrote it in JavaScript, and he was burning screens with it a day or two later.
Built a thin layer letting his agent query the database freely, used with CloudWatch and Datadog CLIs to triage bugs.
Liang Gou wrote no code himself: he directed the AI to design and build a complete grading app for his wife, a high school math teacher grading 100+ papers a week at 3 to 5 hours per test. The rubric engine reconstructs a rubric from a single graded example, its eval bank comes from real AP Calculus AB free-response exams, two models cross-check grades, and the agent tested the app itself in a browser before deployment.
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.
GLM and the AI redesigned an interior 3D-print part to print in vase mode; the new part is better than the human-designed part he took from the internet.
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.