A random mix from the whole library. Shuffle for a new set.
He is treasurer for a nonprofit food co-op. He gave the AI the co-op's financial statements, some notes on what he wanted to explain, and the logos, and 20 minutes later he had a ten slide deck and separate printouts for the annual meeting.
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.
Ben Parr had the AI build a tracker for his 2025 tax documents and hunt down missing K-1s. The agent organized the paperwork and chased the missing forms.
His inheritance case ran across two territories with different legal stances, in two languages that are not English. Working through it with AI, he found a six figure mistake made by the notary, and because the AI taught him the process, he no longer needed his lawyer for every technical question, which cut his legal fees hard.
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 team used an AI 2.5 tool to go through large sets of public comments. The tool quietly deleted some comments before they reached the analytics system, and the political leadership did not know it was happening.
Volunteered and built a cartography data pipeline with coding agents for an educator, integrating sources updated every few minutes so new maps appear within about 5 minutes on a low-powered machine.
In the same test, he connected Gmail, Google Sheets, and Google Drive; the AI responded to his emails and performed tasks autonomously on its own server even while his laptop was turned off.
The AI filled out his car insurance application for him. Where an answer was not in what it knew, it stopped and asked him instead of guessing.
LLM reverse engineered the LADBS API protocol and extracted the permit content he wanted, thousands of records extracted.
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.