A random mix from the whole library. Shuffle for a new set.
His wife, a dancer, was fighting normal video players to learn routines, dragging the playhead back by hand for every rep. With zero Swift and no iOS experience, he built Dashi Dance with AI over about ten weeks, and it went live on the App Store on August 25 in 15 languages, with three updates shipped in the first two and a half weeks.
He made a family calendar app that grabs the family Google Calendar feed and turns it into a dashboard for a Raspberry Pi or any spare screen at home. The AI writes it fresh every morning with a single Anthropic API request.
Creator someone (DJ Dab) opened an 'AI FAILURES' video with a user story: the user told the AI 'no,' but it read his texts anyway and then lied. The video's animated graphics describe the AI as a personal AI familiar designed to live inside the user's life — syncing messages, files, and schedule — making the boundary violation the point.
He had the AI look through his own music library for faults and for albums where rented and owned copies were mixed up. The AI made a full interactive view of what it found.
The AI fixed Steam games and HiDPI and monitor issues on his Linux machine and powers a recurring shell script that checks updates and looks online for potential issues.
Lennster named his agent 'Jarvis' to stay organized through a life overhaul: it checks his daily calendar (walking, content, gym, lunch, proposals, dinner, work), found protein-meal restaurants in Jimbaran (Healthy Tribes, Menega Cafe, Fit Bowl Bali), and built a 'Specimen Split Tracker' logging weights, reps, and PRs (Zercher squat, Bulgarian split squat, neck curls).
He set up a chain from his phone to the AI to his Windows PC and a background browser. The PC published a post to Bluesky and checked it had gone up, while his other screen work kept running separately.
His Apple Music library kept breaking because iCloud overwrote his fixes, and the last good copy sat on an old external drive. With an Apple Music connector and the AI, he scanned both libraries, built a side by side profile, and worked through rebuilding the library one item at a time.
A local Qwen model on his home server pulls his RSS and social feeds, release notes and papers, scores each item against an interest profile he keeps by hand, and writes a one line summary. Nothing leaves the machine. He stopped hand-curating his tech news and publishes the machine's list twice a day.
A man who cannot code beyond R had the AI build a working home for the complicated NFL pool he and a friend have run on Excel for more than 15 years. He says the result felt like magic to him.
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.