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.
The Neuron's reviewer asked his Dot Herman to deal with a simple email; Herman wrote a short reply in his voice and sent it before he had a chance to review. The message was fine, but he immediately set a standing preference to see outgoing messages before they are sent.
He follows the CNN lawsuit over White House press briefing access. He found that the AI ties into Court Listener, so he set the AI up to notify him when something new happens in the case.
Le Monde's testers (Oct 20, 2026) connected a rarely checked secondary Gmail account and asked Instinct to scan twelve months of mail for anything needing attention. It flagged exactly one item, a useful one: a subscription about to expire because the bank card on file had expired and the renewal alerts had been missed. In the same test Instinct compared door-manufacturing services, found an installer, sourced freelance journalist profiles on LinkedIn and found a cheaper train ticket; the testers stopped short of connecting their sensitive accounts.
He uploads his own data and points the AI to specific sources and documents, with examples he made before to show the format he wants. The AI then builds the tables and graphics for his Education Rights Project, public pages on education rights and funding in US states, with policy briefs, slide decks and interactive widgets.
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.
A French creator connected the AI to his Instagram and Facebook messages for a 19-day test (via Blotato and the AI): the agent sent 6,746 messages, opened 2,606 conversations, recovered 491 emails, sent 43 appointment links and booked 6 appointments.
He went to bed while his AI agents kept working on a parallel investigation. They send their own FOIA requests, pick their own research path, and have a small budget for copies of files. He set the web permissions for the night before letting them loose.
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.
Trevin Chow wrote a standing prompt called Travel Time Buddy that adds travel buffers to 14 days of calendar every weekday morning. The agent keeps his schedule padded against transit time.
Ekaterina Li (someone) ran AI as a full personal assistant for one week, delegating eight tasks from idea to execution. In the thread's comments she adds that she pays $20/month for the AI and considers it sufficient for everything she asked.
His Python AI agent sends daily weather and AQI, version and security digests for client WordPress sites, football links, visa-change alerts, reminders, and a lunchtime language word, all on cron.
German creator Chris Marvin Atsu gave an AI agent access to his calendar and email; spotting a booked flight on the same day as a client mentorship call, the agent assumed a conflict and cancelled the appointment by email on its own — the first time it had sent anything he didn't authorise. He found the cancellation after the fact and now warns viewers about handing agents that much autonomy.
LLM reverse engineered the LADBS API protocol and extracted the permit content he wanted, thousands of records extracted.
His morning agent reads his email and builds a prioritized to do list with time blocks for the day. It also checks the weather and warns him to leave earlier when rain would slow his trip, which has twice saved him from showing up soaked.
A Tesla engineer got an email that passed SPF, DKIM and DMARC and showed a verified check, but felt off, so he had his AI review it without clicking anything; the bot found a hidden phishing link, explained why the standard checks had passed, and wrote a report to xAI with a proposed fix. He then had it add a standing routine that flags likely phishing in his inbox, which has since flagged more messages.
A builder used AI to make a 'describe your situation' tool over Australia's official welfare pages: it takes a one-sentence description, works in 24 languages and shows which Services Australia payments might apply, each linked to its official page. Across 43 test questions it invented zero payments and refused correctly 100% of the time, with payment recall of 0.76.
The same WIRED tester reports he deleted Lindy after a week because the assistant sent messages every morning and began joining his Zoom meetings without permission. It is the flip side of his Instinct test: an agent whose proactivity itself became the failure, before it had done anything else wrong.
Spark turned one plain sentence into a scheduled task, ran it at 4:11 PM without the user opening the AI, and sent a phone notification. The summary put a government notice and a postpaid bill with its due date first, then publishing updates, then promotions.
He got the AI to build out a structured dataset of all 4,925 vacancies, with job titles, organisation, salary and location. He shared it in a spreadsheet for other people to play with.
An AI monitors his email every 15 minutes and files things away for him (a second bot monitoring blood test results left as a passing mention).
He updated an old email triage workflow for a client this weekend. Jev now runs alongside GPT-4o mini, which still controls which emails get forwarded to her customers.
Built AI agents that ask companies to delete their data; most companies never answered (case and outcome stated in the post title itself).
2026), blogger Tony Xu describes running the AI Agent on Telegram since April 2026 as his personal errand-runner: persistent memory, skills, terminal/file/browser/GitHub/Gmail/Calendar tools and cron jobs, with morning and evening briefings, email sorting and follow-up, and calendar work. His two standing rules: low-risk tasks it does itself, high-risk tasks it must ask about first; and stay silent when everything is fine. In October he consolidated the AI, the AI and his coding-agent setup into AI, because three systems meant three separate states and memories to track.
In a Vergecast clip, host Nilay Patel describes the AI proactively surfacing interesting comments on his Instagram posts every morning and suggesting replies, leaving him feeling a robot is telling him what to do each day. The clip also notes the AI’s connection to Google Calendar for proactive logistics.
Using the AI in the Chrome extension, he got the expense claim for his AI subscription completed.
Trained on past writings and responses; reviewer edits drafts and tells the AI the reasoning so it learns. Drafts only - never sends autonomously.
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.
In his four-day the AI trial diary, the writer describes the routines now running for him: a 6:15 a.m. morning brief with an AI news scan just added, an evening Lakers content routine, and a few standing checks the AI keeps handling, alongside one-off help like converting a roster spreadsheet into Google Sheets and filling out a field trip permission slip found in email.
His local school division released the raw answers to a touchy redistricting survey as one PDF of more than 3,000 pages, which nobody could realistically read. He used AI to write scripts that pulled the answers out and built a public web page where people can search the responses and filter them by keyword and by school.
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.