A random mix from the whole library. Shuffle for a new set.
Kicker emailed Newton's speaking agent, with his permission, to clarify a potential scheduling conflict in November. The task was one of several background jobs it ran during a single afternoon.
Agent manages the import and export process for the international move of his pet, including comms and form filling, and corrals the family's move documentation.
The AI cleared an inbox of 100,000 emails during the user's workday, leaving a manageable mailbox behind.
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.
He pasted one prompt into AI, and the AI read the Carly email setup docs itself, finished the signup, and took the verification code. The inbox, named Loopy, now takes tasks by email and asks before replying to anyone outside.
Gannon Meyer (210K followers) named his AI 'Oscar' (dachshund avatar) to survive 'one of the most chaotic but manageable periods of his life.' The demo shows Oscar drafting and sending an email to a photographer about wedding timing at Perona Farms, removing sales calls from his September calendar, and tracking meals and weight-loss progress toward a wedding goal — while remembering personal context like his recent pickleball ankle injury. Oscar proposes actions but executes only after a
In PCMag's five task test, the Dot went through more than 15 years of the reviewer's marketing mail, built a spreadsheet of over 700 senders, picked the ones worth dropping, and clicked through their unsubscribe pages itself. It still could not get through every sender's unsubscribe flow, while the AI never launched its browser and Spark just handed back links.
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.
He had the AI work out how the When2Meet scheduling site works and turn it into a skill. Now the AI can read his calendar and fill in the When2Meet availability grid by itself.
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.
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.