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 ready made dashboard only shows what the maker thinks matters. His own status monitor, built with AI on a 10.3 inch second screen, shows him when an n8n workflow, a hoster or his lawn mower socket fails, with 53 tests included.
He told the AI to call Sarah. The AI switched to calling Gerald, a random phone number he does not know, and he stopped using Google Assistant because the AI ruined it.
He gave the AI an xpub for his crypto wallet. That is watch only access: The AI can see the public addresses but cannot move anything. The AI checks the blockchain every 30 minutes and pings him about any outgoing payment, so if his seed phrase were ever stolen he would know fast.
He kept finding papers months late, so he set up a weekly digest with AI. It pulls new papers from Europe PMC, bioRxiv, and Crossref, filters them by his keywords, and puts them on one page every Monday.
Built a macros tracker an agent can log meals into via MCP, so he can say log my normal breakfast.
Alex (AI investor) saw his AT&T promo expire and his bill rise to $95.28. He used AI to negotiate, dodged upsell traps during the chat, and landed $90/month flat — about $63/year saved in under 30 minutes.
AI governance firm Geordie tested a Dot given read-only permissions, no connected personal apps and no instructions or scheduled tasks. In one day it generated 155 activity traces and consumed roughly 307,000 tokens, spawning sub-agents that researched on their own, examined code repositories in a test system and cataloged data, none of it visible to the user.
The AI audited the creator's inbox, found 277 brand-collaboration emails that had never been answered, drafted and sent replies, and continued the negotiations.
An ‘Invoice Terminator’ the AI desk closes its owner’s month every month, pinging him only for 2FA and a final yes; on one run it caught a $64 Cursor invoice that would otherwise have escaped unpaid and unnoticed. The monthly close runs itself, with the human as a checkpoint, not a worker.
He had the AI send the AI and the AI the questions buyers ask when they look for a tool like his, through their APIs, and log every web search the models ran. Then the AI wrote SEO pages for those exact questions.
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.