A random mix from the whole library. Shuffle for a new set.
A tech writer had the AI search five years of his email for signup and password reset messages. The AI built a spreadsheet of the accounts it found, with breach notes and a deletion link for each service, and tagged at least 50 accounts.
He is a photographer who found typing alt text for every photo slow going. He built a small agent on his own n8n server: he sends a photo through an Apple shortcut, the agent reads the picture with a local Qwen model, adds the camera data, and saves the finished alt text in an Obsidian note, ten photos at a time.
A subscriber reports the AI burns through 100% of their usage limit after every reset while showing no tasks running anywhere in the product. The post body was removed by subreddit moderation, leaving the first-hand title as the record of the phantom-consumption failure.
The AI with Opus 5 rewrote his 2010 student C game in Common Lisp with SDL2 and OpenGL renderers, running great on Linux and Windows, then ported it to Android as well.
He had the AI configure his smart TV through its debug connection to use a filtered DNS service. Ads on the TV stopped, which he jokes is either a great morning or the start of a robot uprising.
His podcast ran for 21 years and more than 1,000 episodes in 4 languages. The new site at pomcast.com keeps 154 videos in under 4 MB of plain HTML, and it lists the 121 episodes that only survive in his backup and the 111 that seem lost.
Used the AI to reverse-engineer a neural network accelerator in a Chinese WiFi camera SoC and implement an ONNX compiler and runtime, resulting in a working 20 dollar AI smart camera.
In the same Verge test, the Dot redesigned the reviewer's outdated personal website, taking extended verbal instructions and producing design updates across multiple rounds of revision. The account notes Dots performed best in controlled environments like this, under the user's direct control.
Liang Gou wrote no code himself: he directed the AI to design and build a complete grading app for his wife, a high school math teacher grading 100+ papers a week at 3 to 5 hours per test. The rubric engine reconstructs a rubric from a single graded example, its eval bank comes from real AP Calculus AB free-response exams, two models cross-check grades, and the agent tested the app itself in a browser before deployment.
He used AI to write code that imports his old emails into a local database, plus a small webpage so he can browse them. The job took an afternoon instead of a couple of days.
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.