A random mix from the whole library. Shuffle for a new set.
A researcher updating his own old question says he now asks his agent to download the papers his reference manager could not get. The agent works in the browser while he is signed in with his school login, and he clicks through the human checks himself.
A man generates all his passwords with his own little tool, which hashes the site name, username and a version number with his passphrase. He had the AI port the tool to iOS, and the setup recently saved him when his laptop died: he could rebuild every important password from memory with a fresh copy of the config.
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.
Migrated a fairly complex setup to NixOS 1 to 1 with an LLM agent and gained declarative services, backups and redeploy tooling.
He says he cannot code, but he used AI to produce a working replacement for Lightroom for his own photo work. It works well enough that he ditched his Adobe subscription.
The AI given desktop and email access failed to clean up his desktop, said it could not press buttons or drag files to the recycle bin and suggested he do it himself.
A man built LatestArr with help from the AI, his first real app. The self hosted tool collects what is new across Plex, Jellyfin, Emby and his book, audiobook and game libraries and emails a clean digest, and he shared it as open source and asked for testers.
The AI diagnosed a long-standing 4K display issue and he now has a CLI tool that fixes it.
AI engineer Sajal Sharma built an AI on Telegram that tracks his tasks and notes and handles scheduled work. On camera he asked for a project overview, checked progress toward a reading goal, and had the assistant search the web for a book series and add the books it found to his reading list.
He built a small notes setup for himself in about an hour. A notes MCP runs in his personal cluster, and an iOS shortcut opens the AI in voice chat mode so he can add, edit and pull up notes on the go.
He normally develops his astro photos in Siril. This time he handed the AI the raw stacked FITS file straight off his Seestar S50 and asked for three things only: flatten the background gradient, remove the noise, and stretch the image to bring out the spiral structure.
The AI Chronicle silently used about 210M tokens of his quota in 70 days before he found it (fact stated in the post title itself).
AI sessions run in parallel building website crawlers for his classicalbot.com project on his VPS, about 10 parallel at most.
On a free year of the AI he has built and scheduled a stack of personal skills: a calendar manager, an expense tracker fed only by emailed invoices with his full history backfilled, a monthly utility cost comparer, and shopping re-up tracking that watches how fast he uses things like coffee beans and toilet paper and schedules the next buy. A weekly skills manager rates all the others and suggests improvements.
Tell the AI to set up an app on his server and it does it all and leaves a documentation note in his Obsidian vault; setup effort near zero.
The AI agy hooked itself to Discord, set up and troubleshoots SSH servers on his home network, commands it remotely.
A screen-recorded walkthrough of an app called 'Song List' inside an AI app AI shows managing a personal music repertoire: 264 total songs, 76 marked 'In show,' 188 'Needs work,' across 76 artists. The presenter navigates 'In show' and 'All' views and uses the search bar.
An old printer orphaned by macOS 27 got a second life: The AI wrote the driver while using its owner as the diagnostic instrument - asking him to judge whether each line was progressively less visible, whether page one's DPI was lower - until the printer printed correctly again.
He mined his old Twitter archive with help from the AI. His old threads of more than three tweets and his collections of links are now on his own site as historic blog posts.
He merged five scattered file messes into one, then the AI and an LLM wiki in Obsidian reviewed and cataloged everything. He says knowing what is in it and how to get it back matters more than tidy storage.
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.