A random mix from the whole library. Shuffle for a new set.
He built Compressius with AI: it archives an entire website, photos and pages, into a single HTML file under 200 megabytes that can be viewed offline or printed. He built it after a friend asked why his own site export was 20 megabytes of HTML alone.
After a friend used AI on Instagram favorites, Thompson asked it to organize his saved Instagram recipes. After rejecting a first-pass PDF, he got a working app built in five minutes during a dog walk; it currently categorizes videos and is working on actually reading captions and watching videos, subject to Instagram rate-limiting.
Got the AI to jailbreak his Kindles and add them to his home tech ecosystem, and to hack a Spotify Car Thing so a Raspberry Pi can drive it.
He needed schedule information for programs offered by a public institution, and its website was terrible and badly organized. The AI made a new website that organized all the information into a filterable table that runs on his phone.
A ham radio operator had a frontier LLM read his pencil sketch of an antenna, build NEC models from it, test and iterate on numerical stability until the approximation held together, and then run a real simulation that answered his questions. He uses the same approach for SPICE circuit simulation.
His Nostr relay moved from a single container to a Kubernetes cluster, redeployed by the AI with an uptime monitoring setup watching it. He reports the relay is faster and the migration went smoothly.
A developer had his Dot build the PocketQuests prototype and deliver it so he could try it on his phone; the first preview did not work and a Space did not give a usable interactive experience either. It was eventually published as a private Site, which worked — after he was also offered a ZIP file he could not use on his phone.
The AI made a PHP script that used the Google Photos API to pull all his photos to his archive location; the extraction is done.
He downloads all his lecture slides and feeds them into NotebookLM for an audio overview. A pipeline then transcribes the audio, has the AI write a timed spec, uses AI Design for the animations and the AI for the filler content, then renders and stitches everything into an hour long recap of the whole semester.
He made the schedule for a film showcase through AI. It created the events with the exact running time of each film, the address, and the travel time, and he had it add a reminder to pick up the tickets.
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.