A random mix from the whole library. Shuffle for a new set.
Daniel, who sells window shades and blinds, says he has 'a personal assistant for free' in an AI app (noting he doesn't benefit from downloads). Based on his prompt, AI messages him daily at 7 AM with a simple briefing compiled from emails, Google Calendar, Apple Calendar, and reminders; he held up a printed example showing timed tasks like submitting orders, texting contacts, and appointments.
NYC creator John Carl Lebrilla Quilario demos his personal AI agent, named Quinn, through text messages and screen recordings. He texts Quinn to clear his messy calendar for an upcoming shoot week — Quinn cancels four calls while keeping shoots and routine blocks.
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.
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.
Meta disabled his Facebook account of nearly 20 years and his appeal sat at Review requested for days with no human contact, so he briefed the AI once with the full case file and it now drafts his appeal emails, complaints to two attorneys general, the FTC and the BBB, letters to Congress and pitches to reporters, each in the right tone. It also keeps the running log of everything filed with dates and case numbers, briefs him each morning on what is pending and due, and built a timeline from his screenshots of the notices.
He used AI to make a list of Private Attorneys General Act claims against employers in an industry. The list was made in support of an organizing drive, and he says the tool is almost always helpful on tasks that involve a lot of data.
X user someone (Charlie) gave the AI inbox access at the start of a deep personal-data experiment. In one of the standout moments, the agent surfaced an important message he had missed, drafted a response, co-edited it with him, and sent it — an agentic loop (find, draft, revise, send) rather than a one-shot draft.
Gaby Hersham built a nightly automation in which the AI reads the roughly 20 school emails her family gets each week and adds the important dates to the family calendar, ending the manual trawl through newsletters and PDFs.
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.
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.
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.
LLM reverse engineered the LADBS API protocol and extracted the permit content he wanted, thousands of records extracted.
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.
Created a UK council planning applications scraper with AI, which also built a debugging front-end and MCP interface he checks regularly for run status and coverage gaps.
His claim was too small for a lawyer and the insurer had frozen it at $4,430, so he worked it himself with AI holding every letter in order. The agent surfaced six dated contradictions in the adjuster's own letters, including a legal basis for denial that changed three times, and reviewed each of his drafts as opposing counsel before anything was sent. After his letter quoting their own paper back at them, the offers climbed: $6,500, then $8,000, then $8,750, and the insurer accepted his split of the last gap the same morning, at $10,250.
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.
Several Hiscox employees independently built the AI Studio agents that extract contact information from emails, and the duplication was treated as a demand signal: the individual solutions are now becoming a larger shared business project with data science, technology, cyber and risk specialists involved.
The road to a takeoff spot they fly from was not on OpenStreetMap, though satellite images showed the track. They built a tool called osmctl, and the AI drove it and mapped the road.
The AI updated a website he manages for a charity and on its own scanned beneficiary header images to add information to the writeup; done well.
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.