A random mix from the whole library. Shuffle for a new set.
The AI called car dealerships and plumbers to collect quotes for the user and scheduled a dentist appointment, the calls and booking done in about five minutes of the user's time.
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.
He uses AI to turn screenshots and emails into calendar events. He also uses it to find email receipts and tickets when he needs them.
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.
In two weeks of real inbox-and-calendar work, The AI Crux had the AI book three conference rooms. Calendar work was functional but conservative: it refused anything outside 9-to-5 local without an explicit override, which the reviewer framed as a guardrail more than intelligence.
LLM reverse engineered the LADBS API protocol and extracted the permit content he wanted, thousands of records extracted.
Harry McCracken's Dot, Chip, cross-checked his calendar against his email and spotted that a speaking engagement he had entered on one date had been rescheduled by the organizers to a different day, which the confirmation email showed. He says he would otherwise have shown up to an empty room.
Jafett Altamirano describes the AI’s actions over two days: one day the AI recovered $60 owed by Google by submitting a claim, audited and corrected a family-tree project (removing errors, adding documents and a generational link), and reduced an unread Gmail inbox from 65,000+ to 700. The author emphasizes all of this was free.
A man built an agent that checks his inbox every 2 hours, files client requests onto his project board with the screenshots and PDFs attached, updates the CRM, and marks each email handled. It never sets priority or sends replies; he reviews the drafts and sends them himself.
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.
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.