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 likes listening to online radio in the car but does not like the TuneIn app in his Tesla, so he built his own radio app with AI. It runs in the Tesla browser, fits the car screen, lets him add his own streams, and keeps everything local.
A man asked the AI to log into AA.com and United.com to check his tickets. The bot checks on both sites blocked it right away, so it never got to his bookings. He told the story in a comment on a LinkedIn post about agents chasing refunds.
He asked the AI to cancel his Adobe plan. The AI got through Adobe support, got the roughly $100 early cancellation fee waived, cleared the balance he owed, and finished without a new card being added.
A renter hit with an Enterprise damage claim had the AI dissect the claim and draft a dispute email built entirely on its evidence gaps - photos with no timestamps and no walkthrough record showing damage. Enterprise replied the next day saying the claim was closed.
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.
After dry-running a personal-assistant the AI through August, its owner let it pay a real $3,731 bill that arrived by email; routines now watch his Gmail for invoices three times a day. The first live payment went through under the watch setup he had tested for a month.
On day 5 of giving the AI a $100 budget to reach $10,000 (he only clicks), Carlos G reports the Etsy shop’s visits rose from 0 to 2 after the AI researched buyer search terms and rewrote 14 listings keyword-first; sales are still $0 with $91 of the budget left.
Set up NixOS on an ancient laptop using AI to factor the config; now uses the same config to manage three machines with easy rollback.
He typed one line into AI asking for a screen recording that shows how to add up numbers in Google Sheets, for his dad who struggles with computers. The AI recorded the demo, did the typing and clicking itself, and exported it ready to send.
Commenting on the 26 use cases post, he says his AI books all his haircuts: he just says book a haircut on a day at a time, and the email confirmation comes in. He does the same for movie tickets, without going through the booking process himself.
Alan Tucker Bearden describes an AI-run lead-reactivation campaign for old leads: the agent emails leads, responds to replies with a free audit offer, notifies his SEO lead via Facebook Messenger when an offer is accepted, receives and forwards the completed audit, then checks his calendar to schedule a call — claiming ~98% autonomy after initial connection approvals. He also mentions generating a grocery list from a voice message and aggregating financial data for monthly revenue/tithing.
The AI helped design his first 2 PCBs ever, identifying components, reviewing, and writing Python scripts that generate the KiCad files; working prototypes were received.
Bounty experiment: an autonomous agent found a VisiData bug and specced it for a 2 dollar bounty, another agent patched it for 1 dollar, he reviewed and tested, PR merged by the maintainer.
Someone posted an illustration styled as an iPhone call-history screen showing seven missed calls from unknown/spam numbers over three days (fictional numbers noted). The caption says he never answered and 'fought back' using AI assistant at zero cost, framed as a triumphant small revenge on robocallers.
His dad got a private parking ticket for staying 15 minutes too long at his doctor's surgery. The AI drafted the POPLA appeal, it cited the Equalities Act, and his dad saved £100.
Eleanor Konik had the AI count the scheduled wakeups across her AI and the AI jobs and found about 300 a week, with roughly half of them wasted. One round of checking, done with AI's help, got the count to about 140 a week with no coverage lost, and about 128 of the old wakeups were just a bot noticing it was 2 AM or a Saturday and going back to sleep.
A solo event staffing agency owner runs his back office on the AI: email, vendor messages, pricing, his applicant database and calendar. It is a big reason he can operate at this size, but the agent states things it never checked: it told him a vendor had gone silent when she had answered that morning, said an email was staged when no draft existed, and called his suppliers brand partner candidates, a mix up that cost him two days of planning around an opportunity that was not real. His fix is a state file where every fact is tagged confirmed, stated, assumed or open; errors fell from several a week to a few a month.
Some of his items would not work in Apple Passwords, so he had the AI write scripts, using the 1Password CLI and AppleScript, that imported those items into Notes for him. Because the scripts were deterministic, he does not think his sensitive data was shared.
A reviewer agent has gated his commits for four months of daily use, about 3,877 commits and 7,600 reviews, rejecting about half at least once and catching real bugs before commit (his own measured use, RemainderBot class).
A man runs agents called Pi on a VPS behind a small app he had them build. One listens to a WhatsApp group and spots bills, a second Pi with DeepSeek reads each bill, pulls out the amount, due date and reference, and updates the database, and a merge step clears duplicates.
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.