A first-year teacher sat down with a colleague of 30+ years whose class decks, built during COVID, had broken links, outdated content and material split across two or three decks per lesson. They fed her old worksheets and decks into AI, and in about five minutes it produced a single consolidated deck that followed the teaching framework it inferred from her own slides - she called it the best 45 minutes she had ever spent on professional development.
Thanks to the AI he has been working on a 4 player version of Wizard of Wor for the Atari 800 that uses all 4 joystick ports, so far in an emulator, with a real Atari test to come. He says he can now play his favorite games with fun options that never existed before.
He built a virtual tabletop with AI, with proper dice, roll tables and boards, and he has been play-testing it a lot. He uses it when travelling and when his real table is buried, and he no longer needs Tabletop Simulator.
Farheen Ahmad (verified creator, 120K followers) was drowning in a saved-Reels folder of content ideas she never used. She had the AI ingest the collection and convert it into a structured dashboard with spoken scripts, carousel outlines and a 'Hook Lab' worksheet, with screen recordings showing the tool learning her 'voice DNA' from her past reels and parsing insights and saves.
Over two weeks the AI built his hobby tool that matches free Sentinel-1 radar images with live AIS ship data around Denmark, recording AIS either side of each satellite pass on its own and marking radar spots with no ship as leads. In one check 2 to 5 of about 555 pairings were wrong.
Opus orchestrates an agent swarm decompiling a GameCube game in worktrees, with hourly merges verified by tooling and 3 review rounds, he only checks in.
This only partly worked. Worth knowing before you try it.
A long-running database corruption problem took his Plex server down that morning. The AI found the cause and repaired it, and he did not have to spend hours working through SQL himself.
He forwards all his Outlook mail to Gmail so the AI can use the Gmail connector. Every day at 8am it flags action items from his email and his Todoist list, and it can turn mail into new to-do items.
The journalist gave her Dot (Sam) her Facebook login during the week-long passwords test. Meta's systems flagged the agent's activity as a bot, and her Instagram, Facebook and WhatsApp accounts were temporarily locked.
This one went wrong. See what happened before you try it.
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 used AI to build software for color separation, halftoning and layer editing for his screen prints. It is built around his own way of working, and he says it has made him a better artist.
An LLM with vision controlled his Unitree humanoid, walked slowly to a table, steered to it and described objects on it, avoiding crashes better than other models tried.
This only partly worked. Worth knowing before you try it.
A user built optimAIzr with AI, a local-only CLI that analyses his own LLM usage habits, flags costly or repeated patterns and estimates where he can cut tokens or spending. All data stays on his machine, and the tool adds live tips while he works.
The AI interpreted scanned old service manuals and circuit diagrams, ran simulation experiments to verify manual claims, cross-checked datasheets and papers, caught typos and his own misreadings.
He had a pile of old laptops he had never gone through. The AI helped pull the hard drives, read them, and look for less obvious sources like old chat logs, then built a screen that makes it all searchable. He found personal history he had forgotten about.
Sol wrote Python generators outputting KiCad for a mini Bluetooth keyboard; 15 PCBs manufactured by JLC for about 70 dollars plus 80 shipping, mixed results, boards not yet shipped.
$150
This only partly worked. Worth knowing before you try it.
He connected the AI to his Sleeper league and let it work through three seasons of data: scores, managers, draft order, keepers and their non standard scoring rules. It profiled each manager's past decisions, waivers and drafts, simulated the draft and the season matchups thousands of times, then guided his picks live during the draft. Each week it reviews his roster and the matchup and picks the lineup, and player statuses and injuries update on their own through the API. He is 2-0 and put up the highest weekly score in any match by over 40 points.
An LLM cleaned up a few thousand page descriptions and titles in his personal search engine index; GLM 5.3 Flash chosen after a shootout between models.
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.
Had an agent write an MCP for his SearXNG setup, then do comparison passes against server-side LLM web tools and tweak it; it works pretty well in his own search use.
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.
This only partly worked. Worth knowing before you try it.
The AI told him swap memory on his server was high, found the cause, and had the fix ready for him to approve. The AI or the AI now connects to the box, upgrades services, and sorts out problems, so his site and newsletter run on a bare DigitalOcean droplet instead of a pricier platform that makes hosting easy.
He told the AI which folder held his video and its subtitles, and the AI synced the subtitles for him. He says that small fix was the most urgent thing in his day.
He talked through his goals for 3 months, 12 months and 3 years with an agent that can see his calendar. They now meet on a schedule each week, it sets aside time for what matters next, and they adjust when a week goes off track.