The AI set up his whole media stack in an hour on an old mini PC
The AI set up the whole arr stack for him in an hour on an older NUC under Proxmox.
A random mix from the whole library. Shuffle for a new set.
The AI set up the whole arr stack for him in an hour on an older NUC under Proxmox.
A music fan had the AI pull all 17 years of his listening records from his streaming history service, so the data now lives on his own machine. A few days later he had it build a personal browser that shows what he listened to each month, drops one time plays and noise tracks, and lets him queue songs to his home speakers in one click.
His AI connection tracker is synced with Bluesky, X and LinkedIn. It reminds him to check in on people and tells him what they have been up to.
The AI configured his arr stack plus NFS mounts, share templates and a VPN init-container in Kubernetes; the cluster is now easy to manage and debug.
Migrated a fairly complex setup to NixOS 1 to 1 with an LLM agent and gained declarative services, backups and redeploy tooling.
Creator's agent 'Poppy' helped stage a backyard drive-in movie night for her kids: it found toy cars on Facebook Marketplace, messaged sellers, sourced decorations, built a shopping list, ordered groceries (popcorn, chicken nuggets, carrots), and produced a printable family fall bucket list.
Worked weeks on an AI-generated, human-guided proof of Hilbert-Smith with a complete 100k LOC Lean4 formalization, rushed out after OpenAI's release.
Built an LLM-backed reference checker for his partner, a lecturer: an agent reads each cited source and checks the reference is correct and not hallucinated.
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.
Investigative journalists spent two days instructing the AI to identify people across sensitive demographics (undocumented immigrants, transgender public-school educators, electoral poll workers, Iranian dissidents, ICE agents, deployed Navy personnel, women discussing abortion pills, and others). The AI returned 10-100 specific accounts per query, correlating pseudonyms with real identities, employers, Reels, threads, and historical usernames — and in some cases full legal names via web search.
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.