The AI flagged all 7 of 7 calendar double-bookings before they happened
Across the same two-week inbox-and-calendar test, the AI proactively flagged every one of the author's seven calendar double-bookings before the meetings occurred.
A random mix from the whole library. Shuffle for a new set.
Across the same two-week inbox-and-calendar test, the AI proactively flagged every one of the author's seven calendar double-bookings before the meetings occurred.
Before a speaking engagement, Ulanoff couldn't recall where he was talking or where to park. He asked the AI to find the original note from his contact, misspelling the contact's name.
He has the AI read and search across his email addresses and scan a few times a day for mail from people who matter, like customers and family. He has basically stopped checking email forty times a day. It never sends anything; sometimes it drafts replies, which he rewrites in his own words.
The AI’s tools produced printable booth artifacts for a nonprofit he advises; in about 30 minutes he had a professional PDF uploaded to FedEx Kinkos for printing.
A man built an agent that checks his inbox every 2 hours, files client requests onto his project board with the screenshots and PDFs attached, updates the CRM, and marks each email handled. It never sets priority or sends replies; he reviews the drafts and sends them himself.
Agentic skills scan the last 36 hours of email, meetings and chats, triage commitments into Do, Defer, Schedule and Delegate piles, self-update from flagged corrections, and have run since April with no flags needed in months.
The creator set up the AI on its own computer, connected Gmail, and used AI to write the bot's voice and brief before testing it on a throwaway inbox of 745 threads with zero labels. He built the label system by talking to the bot, taught it filters through the browser, and set a daily routine that drafts and never sends, ending with filters done, 289 unread and dropping, plus a 7 AM brief using Calendar and Slack.
After his motorcycle was stolen, his insurer offered nearly half the market value. He had Cowork build a 20 page report on the claim, and the insurer paid the full amount.
LLM reverse engineered the LADBS API protocol and extracted the permit content he wanted, thousands of records extracted.
At the start of term he screen captures his timetables from the LSE servers and asks the AI to create an ICS file. He can then drop the file straight into his calendar.
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.