The AI cleaned up my Gmail inbox of 12,000 emails
Mufti Hassan had the AI clean up his full Gmail inbox. The chapter title gives the size of the job: 12,000 emails.
A random mix from the whole library. Shuffle for a new set.
Mufti Hassan had the AI clean up his full Gmail inbox. The chapter title gives the size of the job: 12,000 emails.
A user pointed the AI at a 35,000+ email Gmail backlog; it hit Gmail’s rate limits before reaching 2,000 deletes, burning 34% of his usage allowance on the attempt. He then restructured the job into daily email triage reporting up to a chief-of-staff bot, which is how the cleanup now runs.
Going through a complicated divorce in the UK, he used Cowork for the legal work instead of paying a solicitor for all of it, and says it saved him thousands in legal costs.
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 is juggling several legal cases of his own, and his lawyers do not have time to answer him every day. The AI transcribes audio, organizes his evidence and writes the case summaries he hands to them. He calls it the best tool he has ever had, and says stopping would mean going back to doing all of that alone.
Tech journalist Lance Ulanoff connected his personal Gmail to his AI 'Charlie' and asked it to check for anything pressing he had missed. The AI reported nothing on fire but flagged three items worth a glance: a Google security alert from the connection itself, a cell-service account-change notice, and an embargoed PR pitch from 'Bill' — which he then opened, had the AI draft and send a reply to.
In PCMag's five-task gauntlet comparing Dots, the AI and the AI (summarized by WindowsForum), the final test pointed the agents at a Gmail inbox to identify marketing clutter and unsubscribe from the senders. The AI identified the emails but failed to launch its browser to actually follow through on external unsubscribe links when required, leaving the execution undone; Dots, by contrast, catalogued 700+ senders and clicked through unsubscribe pages.
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.
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.
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.
Without being asked, Harry McCracken's Dot began flagging incoming messages it judged urgent or important in an inbox flooded with PR pitches. It also resurfaced an email from a freelance author that he had overlooked for weeks and nudged him to respond.
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.
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.
Eleanor Konik had the AI and AI team up on dashboards for local nonprofits. The AI did the early research and dug up grant chances the groups had not seen, like a group that pays for field trips to battlefields, a free textbooks program for private schools, and creative arts projects, and the lists were put behind a password for her friends to use.
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.
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.
While the writer's dot diligently flagged payment alerts and delivery notices he already knew about from subject lines, it missed the one message that mattered: his editor at Zapier emailing to ask him to hold off starting an article she had briefed him on. Had he started the work, the missed flag would have wasted real effort.
Tetsuro Miyatake had the AI call Volvo Cars as 'Hailey' on Matt Schlicht's behalf to check routine-maintenance availability for his XC90. The service department had openings all the following week starting Monday at 8 a.m.; the AI clarified it was checking availability only, not booking, since a phone number was still needed.
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.
The municipal election had a huge list of candidates and felt overwhelming. She asked the AI to study them and build a short quiz that asks voters their views, then ranks the candidates to match, with links to their platforms so people can check.
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.