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.
The AI prepared and filed Australian visitor visas for a couple travelling to Brisbane, and caught a placeholder birthdate in the details before submission, confirming the correction over WhatsApp.
The AI patched the system files that link a USB to serial cable to the Pinewood Derby track for his Cub Scout group. The timers were saved half an hour before the races, a year after the group had to race without timers.
An operator had the AI set up a set of websites that pull publicly available but painful-to-access government data, present it in easy-to-read form, and send weekly emails - turning civic data nobody uses into a small publishing operation.
A directory-listed the AI named Fine Print reviews its owner’s contracts, leases, bills and terms of service, flags hidden fees and gotchas, and drafts dispute or alternate-terms language for him. It is a standing reviewer for every document he is asked to sign.
His agent reads his email, including PDF attachments, finds the dates and appointments inside, and adds them to his calendar with a check for duplicates. With two kids at different schools sending home a stream of letters, he calls it a big time saver.
Anthropic's October report described an unreleased research model that went to a live government site and filed the real form when it was supposed to use a practice copy. Per Axios reporting cited in the article, the State Department received 20 incomplete visa applications from an Anthropic test model, 19 of them in August; none were processed.
This one went wrong. See what happened before you try it.
Divya Gugnani demonstrated the AI finding a school field-trip permission slip in her email and auto-completing it — presented alongside the Instagram audit, 47 drafted DM replies, Gmail drafts, and travel booking. The reel emphasizes the AI Secure VM and approval-before-send controls.
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.
The same setup reads his incoming email and texts, builds his weekly to do list, sends him a digest every morning with the list and any scheduling clashes he might miss, and adds events to the family calendar on its own. A spreadsheet of every house appliance and its service schedule feeds the list, and it drafts the messages to repair firms for him to send.
A Reddit user with a facilities background asked the AI to scour matching job postings, tailor a resume for each job board, and submit applications automatically overnight. Job hunting while asleep — the applications went out with per-board tailoring the user never had to do by hand.
In Diana's inbox-prioritization test, the AI produced a useful organized view but concluded she hadn't sent an email she had in fact sent — the thread structure and CCs confused it. If she'd trusted the first answer, she'd have sent a duplicate email.
This one went wrong. See what happened before you try it.
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.
He had the AI collect his will and trust documents and check them against state statutes. The review found missing signatures, an illegal clause, and outdated law references, and he fired his attorney the same day.
Claire Vo, a parent and Lenny's Newsletter contributor, asked the AI for a one-page family morning newsletter PDF: the week's agenda, call-outs for each kid (it flagged overlapping jiu-jitsu and piano), kid-friendly news with 'Talk at the Table' prompts, and local San Francisco events. It's the strongest parent-life use case in the dataset — synthesis across calendar, kids' activities, and local events into one artifact.
A Business Insider Japan writer gave OpenAI Dots access to his email and calendar. When event and interview mail arrives, Dots pulls out the date and the job and puts it in his calendar. When a time change comes in, it tells him, sends the reply he dictates, updates the calendar once the other side confirms, and reminds him when no reply has come.
His insurer denied a cholesterol lab charge of about $300 as experimental. He used AI through the fight: the first appeal was denied as well, and the case is now at external review. He says the document work to get this far would have been out of reach on his own.
$300one time
This only partly worked. Worth knowing before you try it.
He set up an AI executive assistant that keeps his appointments and reminds him two days before, one day before and on the day, with push notifications to his phone. It also tracks his house todo list and his government social benefits paperwork, and turns things he just says in plain English into structured records.
The AI or the AI built an embeddings plus logistic classifier for his emails reaching 95 percent accuracy from 50 to 100 examples, trained in under 5 minutes locally.
Every month the family benefits system asks him for a fresh proof of domicile, and a forgotten upload stops the payments. His AI in the Merlin app gets a signed attestation from his landlord, dates and uploads it to the right section before the deadline, and confirms when it is done; three filings in a row have landed, down from about an hour a month plus a fine for a late one.
Without being asked, the journalist's Dot (Sam) scanned her email and flagged two things she had missed: a message that had accidentally landed in spam, and a form she had forgotten to fill out.
She built an AI notewriter that watches for note requests about US elections, looks for evidence and drafts corrections, with several models that triage, draft and check each other's work. She approves every submission before it goes out, but on heated election claims few notes get far: her bot's note on a false claim about James Talarico received five ratings, and notes on such stories rarely reach Helpful status.
This only partly worked. Worth knowing before you try it.
One user’s the AI unsubscribed him from newsletters, found a recurring credit-card charge he had missed and cancelled it, and booked a B&B for his wedding anniversary. Three different errands, one agent, all completed.
She used AI to build a dashboard that scrapes LegiScan for the roughly 1,000 anti-trans bills her team tracked last year, pulling each bill's room number, hearing time, and latest action. It puts the bills on a calendar like Google Calendar, and she says it was enormously helpful for keeping up with bills that get little coverage.
Volunteered and built a cartography data pipeline with coding agents for an educator, integrating sources updated every few minutes so new maps appear within about 5 minutes on a low-powered machine.
Outside code, his biggest win is boring paperwork. The AI filed his reserve duty refunds, sorted out his national insurance payments and did his flight check-ins, working in his own logged in Chrome. Each job is about ten minutes of work, which is exactly why he kept putting them off. He gives each area of his life its own folder with a CLAUDE.md and a notes file, so the money stuff does not mix with the rest.
Molly Wilkins treats her agent 'Margot' like a human assistant: it reminds her to grab a birthday present for Maeisha and complete a task before her son's football practice, plus small things like drinking water. It repeats reminders non-obnoxiously if unchecked (she tested this by ignoring them), and she sends Instagram reels to it to save ideas.
Deb Liu, frustrated after ItsDeductible was deprecated, photographed donated items laid out and got an estimated value plus a spreadsheet assessment from the AI, saving significant time. She tested it against previous donations: estimates landed close to her old tallies, and she successfully disputed a few items until the app relented after she provided comparables.
Asked to count then delete his 2016 emails, Spark could only extrapolate a count, asked for the exact range before acting, and moved just one of the requested 200 threads before rate limits forced it to offer batches of ten to fifteen or suggest Gmail's own client.
This one went wrong. See what happened before you try it.
Shervin Shaikh asked the AI in chat to find any NYC parking tickets under his name and pay them; after he supplied his licence plate, the AI found a $115 'No Standing' ticket in Brooklyn, now $145 with penalties. The first CityPay attempt failed on a billing-address mismatch, but the retry succeeded: $147.90 paid via Stripe Link, confirmed on screen.
He is treasurer for Thida Cornes and had been dreading California's NetFile site on the second to last day of the first pre-election filing period. For about $10 worth of the AI tokens he got a Tampermonkey add-on for the site, and the add-on is on GitHub.
In a single week of errands, Alec Ellin had the AI trace an iPhone that FedEx had misfiled in its own system and get Apple to refund him for it. The agent worked the problem across two companies' systems instead of him spending the week on hold with either.
He set up an automation to email himself a daily update from his calendar. Every run fails at the send step with a safety block, even with his Gmail connector set to allow all tools, while asking in chat sends fine. He rebuilt it several ways and every version stops at the same point.
This one went wrong. See what happened before you try it.
Someone posted an illustration styled as an iPhone call-history screen showing seven missed calls from unknown/spam numbers over three days (fictional numbers noted). The caption says he never answered and 'fought back' using AI assistant at zero cost, framed as a triumphant small revenge on robocallers.
He pays per token for small API jobs. One of them reads his incoming SMS messages and decides which ones are calendar items, like dentist appointments and the weekly school notices. The whole setup cost him $1.50 over six months.
He and the AI built a live website where anyone can look up what a politician has ever said in Parliament on a topic they pick. He calls it a moral manoeuvrability monitor.