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.
His multi-agent trading stats setup has a second agent on another machine recompute results from the written method only; today it caught 2 numbers resting on an unwritten assumption, an import crashing above about 150K rows, and an outdated threshold, after the first agent's tests all passed.
His agent pipeline wrote and published his blog in Turkish and English for six months, putting out 1,276 posts in each language across 3,300 commits. Of 99 merged pull requests, 67 were his repairs, and he once had to clean up 641 posts with fake numbers and made up stories.
The AI ran Geico quote flows in parallel across three virtual computers and found coverage saving about $2,000 a year. The poster disclosed that he works as a Geico designer.
He edits video for a living. His agents handle the non creative manual work around each project: quality checks for missed text, black frames and logos, subtitles, reformatting for social aspect ratios, spreading files to the right products and pulling source material for descriptions. He logs his hours on every project and says agent assisted projects take about half the time with better quality; the weeks spent building the setup paid for themselves in two weeks.
A man talked with AI for an hour about tax loss harvesting, then used Scalable Capital's MCP access to close a position in his own account. He never left the terminal.
Every release of his app used to cost him a weekend taking store screenshots in 16 languages, cropping them and pasting them into store cards. He and the AI built a small tool that drives headless Chrome through the real app, grabs the screens in each language and composes the finished cards with captions and backgrounds. A release is now one command.
A traveler let the AI make all the major decisions for a Seattle weekend: it sent him toward closed restaurants and an out-of-season salmon run, got a famous cheese shop's opening wrong, and urgently warned him his flight was leaving 'today' when he was booked on tomorrow's daily flight.
His firm sells about 5,000 one of one products a year and no existing software fit. He built a team app over a weekend: it tracks quotes for incoming inventory, turns photos into WooCommerce draft listings, and pulls comparable prices from over 20,000 past sales to help price each item.
He asked the AI to check if his phone and internet plan was worth what he pays, and shared the agent's own account of what it did. The AI signed into his account and checked five months of statements: he uses 14 to 30GB a month, so his unlimited plan was charging him for room he never uses. It found a cheaper tier, Mobile Select at $30 a month with a 50GB data bucket, $15 a month less than his $45 legacy plan. The tier was not offered on the self service pages, so the AI opened the Xfinity chat, told the bot it was acting for him, got passed to a live agent, and handled the account checks, including spotting an expired approval link and getting a fresh one sent to his email. Before agreeing, it read the order review page: one line, $0 due today, $15 a month less, no add ons. His whole part was typing the word go. The saving is $180 a year from the next bill.
His talk archive site had been a work in progress for years. He asked the AI to help track down records of talks he has given, and the site now contains 115 presentations covering 26 years.
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.