I got my three Draw Steel Obsidian plugins ready for anyone to use
He built three Obsidian plugins for his home Draw Steel game. Over one weekend, with AI, he got them ready for public use and anyone can start using all three now.
A random mix from the whole library. Shuffle for a new set.
He built three Obsidian plugins for his home Draw Steel game. Over one weekend, with AI, he got them ready for public use and anyone can start using all three now.
The AI, proxying commands through him, diagnosed and fixed in about an hour a box that OOMed and needed rebooting every few weeks.
He gave the AI one line of needs, a budget box with 2GB of RAM or more in the US. The AI compared RackNerd and Hetzner, picked a 2GB server in New York for $35.99 a year, filled in the checkout, and he approved the payment.
The AI built a complex quiz web app for himself and friends with multiple question types, screen sync, media uploads and scoring, in about a week of evenings (build reported in-window; the comment's complaint about current models left aside).
He wanted a control monitor to fit under his screen and follow the angle and shape of his Stream Deck. He uses AI with reference photos to get the base shape, adjusts sizes after measuring with a caliper, printed a quick baseplate to test the fit, and fixed a 1mm clearance problem with the lock after more measuring.
Creator Matthew Berman describes giving an AI access to his local machine on a standing weekly job: it scans every file, finds deletion candidates totalling about 380GB, and sorts them into low, medium and high risk. The bot operates under one hard rule — it may categorize but must never delete anything itself.
Migrated a fairly complex setup to NixOS 1 to 1 with an LLM agent and gained declarative services, backups and redeploy tooling.
Eleanor Konik had the AI count the scheduled wakeups across her AI and the AI jobs and found about 300 a week, with roughly half of them wasted. One round of checking, done with AI's help, got the count to about 140 a week with no coverage lost, and about 128 of the old wakeups were just a bot noticing it was 2 AM or a Saturday and going back to sleep.
The AI agy hooked itself to Discord, set up and troubleshoots SSH servers on his home network, commands it remotely.
Vibe coded personal apps including Meem Makr, which he uses every morning to tell his family when coffee is ready, and a WiFi QR code PDF generator.
He wanted to digitize his papers. The AI worked out how to use his feed scanner, and for about two hours he sat feeding pages in while the AI ran the scanner and catalogued the documents. He could talk to it through a conference speaker and watch it work in VS Code.
The AI built him a Bluesky bot that posts HN Wikipedia articles and posts an archive pick after 48 quiet hours; it is live and posting.
A user runs a long-lived agent session over Telegram: more than 4,000 messages and about $231 of usage in one session. Replies had been delivered normally until late in the session, when for 3 consecutive turns the agent produced text but never made the Telegram reply call, so nothing reached him at all. In the same stretch it also stopped saving decided design decisions to memory, as its standing instructions required, and he had to re-explain the decisions in a later session. A manual service restart and a log review found the cause.
After CrowdSec stopped supplying its community blocklist, he had an LLM build a replacement blocklist from public sources for his Debian VPS.
Creator Wendell Yu says the AI read his 17 years of Facebook posts and wrote a profile report of his life from them. The segment is the first of five first-hand cases in the video.
He saved articles and never read them, because on his phone he ended up on social media or email instead. So he built a reading app with AI and the AI that bundles his saved articles into one EPUB for his Xteink X4 Pro e-reader.
Two of his astrophotos, M 27 and the Pleiades, went through a local processing pipeline that his AI agent Orobas built and ran. It stacked the images in Siril, cleaned up the background in GraXpert, and stretched them with logged settings.
A coding agent built and tested complex genealogy record-matching scoring rules against real datasets; results sort of acceptable but it missed human-obvious cases and produced false positives.
He built an automation with AI that runs on Val Town. It reads his Goodreads progress updates and reviews from RSS and cross posts them to bookhive.buzz as AT Protocol records.
He had some the AI quota left, so he had the AI write a Blender script for orchid pots with Voronoi cells. The design then went to his 3D printer, which produced the pots with no problems.
Konik had the AI build a database of summer camps and birthday-party venues within a 40-minute drive, with camp-week price comparisons and logged reflections on each. It found a nerf-wars venue she chose for her son's winter birthday.
He found the Excel games he used to play as a student, where you guess TV shows from their theme music. They no longer run on modern Excel and the site that hosted them died years ago, so he ran them through AI and put them on the web.
A reviewer asked the AI to find gluten-free beer nearby and provide the restaurant's phone number. The AI returned two good picks but one spot had been closed for years, and it admitted to making up a restaurant phone number 'out of thin air.' A documented hallucination failure in a local-search task — exactly the kind of error a user would only catch by calling.
A hobbyist with no hardware experience wrote a custom board setup for a cheap ESP32-S3, flashed the AI Gadget code and paired it with his AI account. He then gave it remote controls for lights and sound, made it play Jingle Bells with flashing LEDs, and wired in a voice service so it answers out loud in a voice he picked.
The AI downloaded 28 gigabytes from his old DokuWiki host, converted the pages, links, and images to Markdown, and stood the wiki up on his own server with page history dating back to 2006. The job ran under light supervision while he was out.
His Notion had 805 random tags because too many AI agents were writing in it. He made a bot to clean it up, and about an hour later it had fixed 12 tags and retagged more than 1,100 bookmarks. Keeping the workspace tidy is now the bot's only job.
On a standing schedule, his agent deletes stale node_modules folders across his projects, freeing about 50 gigabytes each run. He lists it first among the small automations that make his setup feel agent-run.
He keeps all his todos in Things, but Things has cloud sync and no official API, so his AI could not reach them. He told the AI to build it, and a minute or two later his todos were syncing from his LLM across all his Apple devices.
He tried to use AI to find out how to control the fan speed and read the temperature on his Snapdragon laptop. It ended up poking some registers that disabled the keyboard, so he had to hard reset the machine.
Myra Chiasson (mom/UGC creator) presents her 'mom hack': The AI automatically generates a personalized weekly dinner plan every Sunday at 8 AM with a new menu and grocery list, accounting for dietary restrictions, preferences, and kid-safe foods, easing the stress of 'what's for dinner' with a picky-eater child and her protein goals.
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.