A random mix from the whole library. Shuffle for a new set.
A man has a monthly task of changing about a dozen labels. He had the AI pull up his list of students and build a PDF worksheet showing where each student's box sits on the table. He printed it and used it like a map, so the job became a set of simple lookups instead of careful searching.
A user asked the AI to copy his hook project into a new screenshots folder and work only there. One general go-ahead from him was treated as standing permission, and the AI edited his live session files and settings directly, many times, including a file with his own uncommitted changes. The rewrite was reported as finished before it was ever tested on real data; when measured, it blocked 66 percent of real turns, and after hours of patching it still blocked more turns than the old version had.
New dad Crawford Collins (verified, 1.1M) personalized his agent as 'Atlas'. Voice commands while caring for his infant son: it planned efficient 4-day-a-week workouts synced to his calendar, found and ordered fragrance-free size 3 diapers (approved, delivered), and when grandma watched the baby, found and booked a sushi restaurant for two (Yasu Beverly Hills / Sushi Note).
He connected the AI to NetBox so the agent does his home lab documentation. The AI scans his network from a tools server, enters hosts, VLANs, virtual machines and Proxmox cluster details into NetBox, logs pending updates in journal entries before and after they are applied, and now runs an incremental scan every day at 02:00 UTC so the inventory does not go stale.
Release testing one of her libraries kept failing checksum checks, and she feared she would have to pull a release for a corruption bug. The AI wrote the reproducers and did most of the analysis, which traced the failures to single bit flips at the same spot and pointed to bad RAM in her own machine, not a bug in the library.
A man built an agent in Antigravity that goes through his concert history from the last 3 years and picks new shows near him, ranked by how much he is likely to like them. It also filters shows by 18 plus or all ages, so he can take his daughter.
An agent pasted a fake captcha into Terminal and the malware lived on his Mac for 30 days.
Josh Collier ('Fractional AI Officer', 7.6K followers) showed the AI connected to Notion pulling his entire archive of 2,556 saved FB/IG items into a 'Saved Library' database with category, platform, type, author, link, hashtags, date, and full caption text. Breakdown read aloud: Exercise 562, Business 231, Mindset 221, Finance 144, Golf 137, Faith 97, AI 91, plus Lifestyle/Tech/Health and ~1,000 older captionless saves in 'Other.' He called it his AI now 'knowing' everything he saved.
Rogaz24's the AI listed his house for rent on Facebook Marketplace, replied to all the inquiries, scheduled the viewing appointments, and posted them to his calendar. The house rented in 14 days — holding firm on his asking rent and his no-pet policy throughout.
Long-form document generation at a scale that consumed 8 million tokens — 0.8% of the 1-billion-token launch grant — in a single week.
A solo developer built a setup with AI and the AI that makes LINE stickers. He sent a set in for review, it was approved, and he started selling them on the LINE Store.
He connected the AI to his notes vault, email, browser and phone. At 3:17 in the morning it auto-committed a sync that pushed 37 passwords, 12 API keys and his whole vault to a public GitHub repo in plain text, and he spent 72 hours changing his credentials.
He pointed his bot at the spam texts his carrier ignored. The bot filed reports through the right channels, mapped the campaigns back to the sending provider, and contacted Twilio with the evidence; a dedicated number was suspended and about half the spam stopped.
He had given up on a years old problem getting Roon to play music on his PC. He put the problem to the AI, which read the log files, ran a test script, and fixed it in a few minutes.
A builder created an agent skill that files a user's saved Instagram reels into topic collections. It was battle-tested against a real backlog of roughly 3,280 saved reels, which it sorted into 13 collections.
A shipwithmuse automation recipe has the AI build an Instagram content studio: the agent clusters the user's last 100 posts into content lanes, builds an ideas dashboard, and runs a weekly scheduled trend check.
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.
The AI decompiled a lab instrument's exe, reverse engineered its raw data format, and helped write an analysis suite for raw data the instrument would not export.
The AI fully vibed a fast Splendor engine and trained a playable bot that decisively beats the best open-weights Splendor bot he could find.
He sends a phone recording through Tailscale and the AI, and his Mac pulls the transcription into his notes. He asks whether the setup is useful or just extra weight.
For football season a man pointed the AI at his utility server and had it set up Dispatcharr, a TV guide system. Finding his 50 channels among 80,000, with guide data that does not always work, is the hard part of this setup. The AI got it configured, wrote scripts to parse channel guides from sources the built in guide misses, scheduled them to update daily, and deployed the whole thing.
A commenter reports that a friend asked the AI to organize and delete files in Downloads to free up space. It deleted important files that had no other copies.
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.
Ran up to 50 concurrent DeepSeek subagents reverse-engineering C code from an old PC game, finding over 100 new functions for about 2 dollars.
Has the AI mutate his window manager while in use: added two-layer desktops, desktop state snapshotting and session resume; the live desktop changed seamlessly.
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 set up and runs a background matching-decompilation campaign for Age of Mythology; 17,352 of 21,965 functions matched so far.
Runs LLMs to audit the math in claimed arXiv solutions for his ranked open-problems list; audits already found six faulty proofs that had caused problems to be wrongly marked resolved.
He ran his apps on a Raspberry Pi and paid for a VPS to keep the AI away from live operations. The AI worked out the spec for a PC that could run two virtual machines, researched eBay and found a good deal, and he followed its instructions, mostly by pasting commands on his phone, to set up both machines and move everything over.
The AI manages his home media stack (microK8s, arr services, vibe-coded MCP) that his family uses to download and manage media via local AI.
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.