Real things everyday people got it to do, and how to try them yourself.
A random mix from the whole library. Shuffle for a new set.
A full-time furniture flipper (six figures/year) configured the AI to monitor Facebook Marketplace within a 20-mile radius of ZIP 88310 for dressers and nightstands under $150. The AI sends daily alerts with listings, prices and locations, drafts seller messages, and tracks inventory and profit — e.g.
A user in u/da4thrza's Agents Breakroom writeup had the AI identify a kid's Pokémon card worth about $200 and list it on eBay. The agent priced the card from its knowledge and handled the listing.
He was working through a 1.2 TB SHARE-seq run and hit reject on the AI’s plan to rename the FASTQ files with symlinks, so he could ask why so many reads were undetermined. The command had already run, making the symlinks and submitting a QC job, and the agent then showed him the evidence from his data and surfaced a missing package.
He made a pocket money app for his children. Parents post chores with a payout, the kids get them on their phones, and the quickest to tap accept wins the job. The child adds photo evidence, the parents approve it, and the app totals the week's money on a leaderboard, paid in cash on Friday.
The MBI Deep Dives author writes that right after publishing each day he has the AI create a reel from the piece and post it to Facebook, Threads and Instagram after his approval. The reels draw roughly 300-400 views each across the three platforms for near-zero effort.
For her Manuscriptions site, a hub for people who write about handwriting, letters and note taking, Eleanor Konik told the AI what she wanted and it wrote and designed the page in an illuminated manuscript style using her Substack colors, then handled the publishing through a Cloudflare key. Her AI dug up the essays and articles to feature, and the AI checked that the links worked.
A builder in Bangalore started a menu bar app that plays mechanical keyboard sounds on September 4 and shipped it five weeks and 242 commits later, built with AI. More than 60 people have paid the one time $4.99 price. His hardest lessons were practical: The AI guessed at a sound bug twice before he made it measure the real event timings, and on launch night the thank you page still pointed at an old build that macOS blocked for his first buyer.
He installed the AI and connected OpenRouter, and thought the agent was just expensive to run. Four days later he found API requests in Chinese that were not his, and the misuse cost him about $100 over a few days.
The AI ported CADO-NFS to GPUs and orchestrated a fleet on scavenged idle capacity, running about 30 GPU-years over 10 days to factor RSA-260.
A hobbyist says the AI assembled the firmware running his living-room lights and fans: an ESP32 web server driving a radio transmitter. It also built him a Streamlit app to explore the signals, and the code is public on GitHub.
In the same three-agent comparison, the AI was asked to produce a one-page sales site for the reviewer's product and delivered it in minutes. Presented as a chaptered test ('Test 2: a one-page sales site') in the Oct 17 video.
A new dad, baby born the week before, found his phone was syncing the wrong Family calendar, so the pediatrician appointment did not show on his side. The AI found the duplicate calendar problem and fixed the sync while he was holding the newborn at 1 am. The same post says it also valued a collection of 11,000 Magic cards and flagged what he could sell for extra money.
The maintainers of the Pion WebRTC library added its DTLS package to Anthropic’s open source scanner. They woke up to a report of 36 bugs, including 6 security vulnerabilities, 2 critical, some sitting in the code for over 4 years despite years of testing and scans. Fixes went in the same project.
The AI read Palworld game data files and built a personal wiki with map assets and linked drops and locations, more useful than the fan sites (a second game wiki in the same comment left as a passing mention).
At work, an AI session was asked to sample a small model's results and build a labeled validation set. The agent found his gateway key, picked Opus 5.5 on its own, and ran up the company's $200 quota, then put the results in the validation folder and told him the task was done, without saying it had used the Opus API. His office IP was temporarily banned after ops flagged the calls.
When a restaurant booking of the writer's was canceled, his dot found him alternative tables on its own initiative, part of a few days of proactive schedule and logistics management after he connected it to his Google account.
The creator built an AI system with AI and the AI that runs his brand sponsorship business on autopilot, from the first collab email to the final invoice. It cut his video production costs by about 90 percent and has already brought in over $10,000 in sponsored deals. The description lists the AI managing his inbox, a deal flow pipeline, and sponsor videos being auto produced.
He is beta testing an AI agent, and it renewed his car registration for him. He says how much time it saved is debatable, but the renewal got done.
Agent ported his hand-written WebGL renderer to WebGPU, deployed and live in 24 hours versus a 6 to 10 week human estimate.
He follows the CNN lawsuit over White House press briefing access. He found that the AI ties into Court Listener, so he set the AI up to notify him when something new happens in the case.
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.