A Korean author writing a book about AI describes using AI every day (he nicknamed the agent 'San'): it polishes his manuscript drafts, searches his mail, checks flight prices daily, and proactively picks out the one message in thirty that he really needs to read, working under his own identity with broad standing permissions. Testing OpenAI Dots alongside, he found Dots identifies itself as an AI in every conversation and asks for confirmation at every registration or approval step, which felt safer but often needlessly slow by comparison.
The AI logs into his five patient portals, pulls every appointment into one place, and checks them against his calendar each week. The morning after a visit it explains the after visit summary in plain words and lists the follow ups he owes.
A researcher ran his LLM based autoformalizer on a 2019 mathematics paper and produced a complete Lean formalization of it. The finished formalization is linked from his university page. The note is short, but the artifact is public and complete.
Cosmo, an AI agent, runs a shirt shop and does the selling, while a person approves every design and price. Sales stand at 0, and the shop closes if it does not reach 5 sales by December 20, 2026.
This only partly worked. Worth knowing before you try it.
A client problem came in by email. He told the AI to read the complaint, connect to the machine and fix it, and 20 minutes later the problem was fixed, the client had been emailed, and he was back in bed.
His agents lived on his desktop, so he had to walk back to the computer to read what they left him. When APX got an Android app, he did not install it himself. He asked Roby, and it pulled the ADB skill and installed the app over USB.
An engineer at Sumasate writes that his team connected the AI Tag to GitHub, Sentry, their database, log tools and Notion, and let it do the first look at every alert in Slack. After three months, fixes finished inside alert handling went from about 2 of 38 alerts a month (5.3 percent) to about 7 of 44 (15.9 percent).
Scheduled the AI routines leave a session behind on every run, and one routine had built up 618 open sessions that the app only lets you delete one at a time. A cleanup skill plans the job, keeping the newest sessions and any where the owner typed a reply, then has the AI delete through the app’s own session tool, 25 per call, each batch behind an approval card.