A teacher built his own LMS layer on top of Google Classroom using AI and Apps Script (he names the AI and the AI as both able to drive it): far deeper grading features than Classroom offers, a quick-select comment bank where any feedback he writes can be saved for reuse with one click, and on return each student automatically gets a formatted read-only feedback document both emailed to them and attached to the Classroom assignment. Student data never leaves the district's Google ecosystem.
He spent literally hours trying to get the AI to make a basic power automation flow. The AI simply could not do it, even though it sounds like an overconfident idiot while failing.
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His games crashed on the loading screen a few hours into a session. He pointed the AI at the problem, it suggested turning on the ntsync kernel module, applied the change to his NixOS setup and rebuilt it, and he played all day without a single crash.
The AI and the AI re-created a Tesla data tool in Go from an existing codebase at his request; he has used the new tool for 5 months and it works well.
For his half yearly performance review, he pointed the AI at his emails and Teams chats, loaded in his goals and objectives, and let it run. The review it produced made him look brilliant.
Harvard physicist Matthew Schwartz built BootLoops, an open-source harness that points the AI at exact, checkable calculations, and ran it for three months across roughly 400 candidate problems: the result was 36 manuscripts in 18 fields with 19 coauthors, including 15 Feynman integrals never computed before, Watson's 1939 'final problem' solved, and a forest model showing Panama's Barro Colorado species mix changes 4.5 times faster than neutral theory allows. The AI reproduced results from his own paper in about 20 minutes that had taken him weeks to code.
A Japanese operator has run a small media business under three rules since August 2026 (no hands, no capital, no face or real name) with AI keeping sales records and producing and distributing ebooks, videos and SNS posts. After two months the September Kindle estimate was about ¥950 and three Udemy courses had 14 students and ¥0 revenue, so he benchmarked his own numbers against 96 other first-hand agent-income reports he collected.
¥950a month
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The AI and Antigravity took an existing STL and swapped a fan-shroud section for another design by directly manipulating the STL geometry in Python; it went perfectly.
After years of building his own food logging apps and never liking them, he set up an AI as his food logger in about half an hour, and now sends it a voice note, a text or a photo of each meal. The bot works out what he ate, looks up the nutrition numbers and logs it in a Google spreadsheet it made for him, and its guesses are usually right.