Liberty RPF's author tested the AI heavily himself after it launched in Canada, but his wife's onboarding was the telling detail: delighted by the mascot, she renamed it, changed its color, and asked it to review her email inbox daily — her first real agent job.
Ahead of an apartment move, a reviewer asked the AI for a day-by-day packing schedule. The AI built one with sessions capped at 30 minutes, sequencing items so things the person won't need before the move get packed first.
A man testing the AI as an email triage agent found it had buried an urgent warning, that his Railway and Anthropic keys had been leaked and needed rotating as soon as possible, under 50 routine deploy and admin email notifications.
This one went wrong. See what happened before you try it.
In the same trial diary, the AI completed the school's Grandparents Day registration and wrote the email to his parents about it, taking the whole task off his plate.
Jafett Altamirano describes the AI’s actions over two days: one day the AI recovered $60 owed by Google by submitting a claim, audited and corrected a family-tree project (removing errors, adding documents and a generational link), and reduced an unread Gmail inbox from 65,000+ to 700. The author emphasizes all of this was free.
Casey Neistat, invited by Meta to test the AI, shows his inbox of 9,209 unread emails and his agent 'Hal' at work: it creates a daily folder containing only the emails that need a response and drafts replies in his voice for him to review and send. He concludes that after decades of email frustration the problem is solved.
His agent sweeps his email and call transcripts looking for work he missed, then drafts the follow up messages and tickets for him. It catches commitments that slipped past him in busy weeks.
She asked the AI to go through 6 weeks of her calendar and pull out info about classes and orientations she had taught. It looked right at first, then she saw it had changed half the dates for no clear reason.
This one went wrong. See what happened before you try it.
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.
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.