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 set up an AI for his WP Beacon project to check WordPress plugins every day. After two weeks of daily checks it pinged him about malware in the InstaWP Connect plugin, and wordpress.org closed the listing that afternoon and restored it the next morning.
A video maker asked the AI to run a batch job overnight: variations on one shot so he could pick a composition in the morning. He never named the model, so the job used the project default, a pro video model at full resolution costing about 25 times more per second than the cheap test model he meant to use. Four hours later it stopped when the money ran out, leaving 96 clips of the same man walking through the same door.
A man built a service that sits on his company’s GitHub repos. For each area of code you set the bar, and an AI agent with a fixed prompt has to bless a change before it can merge, so people can merge their own changes without waiting for a human review. About 30% of the company’s pull requests now merge this way.
He tried Instinct, an agent that lives in WhatsApp, and threw his personal backlog at it. It deleted 300 abandoned accounts and also handled buying things and filling in forms.
Gave the AI kubectl access and it chased down a sneaky shutdown performance bug in 10 minutes, producing a spot-on diagnosis sent to developers.
The AI audited the poet's 6,500 Threads posts against the master file for his collection and found 525 poems that had never made it into the file.
Diana gave her dot Sparky one brief for a standalone review lab page, with a ten test grid, the scoring rules, a checklist and a clear note that it must not invent test results. Sparky built the page in an AI app Sites, published it, told her on its own that the page was set to private, and gave her a link she could share.
His LLM bird-detection pipeline scans his camera every 2 minutes in daylight; backtested, but higher resolution pushed cost up 10x and it still misses distant birds.
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.
Ethan Mollick writes that the AI noticed an airline credit of his was about to expire and, when he asked, contacted American Airlines to request an extension — an example of agents catching deadlines their owners miss.
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.