A random mix from the whole library. Shuffle for a new set.
He ported BlockOut, the 1989 3D Tetris, to the Nintendo 3DS with AI, with stereoscopic 3D, sound, touch menus and SD saves. He did two more games the same way, and all of them are open source under the GPL.
A user who bought a paid the AI plan specifically for Dots reports its live voice mode never finishes any action: it says it is checking, then stalls indefinitely even on trivial requests like the time or weather, across Android and web. The same account's text chat completes tasks, isolating the failure to the voice-agent path.
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.
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.
He ran AI for three days on a headless ThinkCentre Tiny in the corner, driving it from a browser. Out came a learning page that walks through one job of an AI agent from order to approval to publishing, and a playable online photo darkroom where visitors expose their own photo and the file never leaves their browser.
A first-year teacher sat down with a colleague of 30+ years whose class decks, built during COVID, had broken links, outdated content and material split across two or three decks per lesson. They fed her old worksheets and decks into AI, and in about five minutes it produced a single consolidated deck that followed the teaching framework it inferred from her own slides - she called it the best 45 minutes she had ever spent on professional development.
The Cowork integration appears to have deleted his AI container state. The container held 170 commits built up over four days of prompting, and that work is gone.
He no longer gets email notifications. His AI, named Mrs. Johnson, learned what he does and does not care about and messages him at 7:30, 12:30 and 5:30 with what is in his inbox.
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 scraped a friend's two social media profiles, made a plan, and had the AI create a website for them. In about half an hour he had a site to show them.
From the same NAS setup, with the same never delete without permission rule, the AI cleaned his large TV collection. Many files had come from torrents and carried extra junk: text files, .nfo files and samples. The AI removed the junk, built one main folder per show with subfolders per season, and deleted duplicate episodes.
While teaching a secure coding class, she asked the AI to build a small app that greets her with a compliment and a quote every morning. The AI built it, set it to run daily on her MacBook scheduler, and ran it right away, without asking her first.
The AI built and optimized his local decision engine for his private image organizer, reaching just under 85 percent accuracy across 500 validation prompts with sub-second responses.
Jeston Lu built an AI that scrapes his saved X posts every six hours and auto-categorises them into a Notion database so the archive stays searchable, with screenshots of the database shared in his post. The build drew strong engagement (1.6k+ likes) as a fix for bookmarks piling up and being forgotten.
He found the Excel games he used to play as a student, where you guess TV shows from their theme music. They no longer run on modern Excel and the site that hosted them died years ago, so he ran them through AI and put them on the web.
He built Tantal, a small compiled language for the MOS 6502, designed around the real limits of his PAL-2 computer: predictable code, direct memory-mapped input and output, and no stack based parameters. He developed it with AI, and the display example now runs on the physical machine.
Tired of LinkedIn's email notifications - each of the 77 toggles on its own page - a user let an agent flip every one off. The chore got done, and LinkedIn blocked his account for the automation, a consequence he admits was obvious in hindsight.
The AI with FreeCAD python scripts creates and modifies his CAD drawings, producing 3D designs, cut-lists and shop drawings for woodworking.
A puzzle solver designed tests for whether a circulated image hid steganographic data, and used AI to help write the scripts and qualify signal and noise across JPG compression formats. He ran the tests with standard tools on every copy of the image he could find, and nothing extracted from any of them, which settled that the image itself carries no hidden payload.
The AI Astra one-shot a phone's dimensions from a public 2D drawing into a STEP model; the dimensions match the drawing tolerances exactly.
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.