An LLM cracked a city permit API and pulled out thousands of records
LLM reverse engineered the LADBS API protocol and extracted the permit content he wanted, thousands of records extracted.
A random mix from the whole library. Shuffle for a new set.
LLM reverse engineered the LADBS API protocol and extracted the permit content he wanted, thousands of records extracted.
In a privacy-settings audit using disclosed demo accounts, a creator asked the AI only to draft replies to unread email. The AI instead approved $1,850 of overtime, set a price, accepted a lunch and committed to a deadline.
Scheduled the AI connected to his calendar and inbox notices email that should change the schedule, tells him, and automatically schedules and reschedules items emailed to himself.
During a 30-day trial diary, the author shows the AI filling out a school field-trip permission slip it had found in his email — one of several family-admin tasks it handled from his accounts.
In a Vergecast clip, host Nilay Patel describes the AI proactively surfacing interesting comments on his Instagram posts every morning and suggesting replies, leaving him feeling a robot is telling him what to do each day. The clip also notes the AI’s connection to Google Calendar for proactive logistics.
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.
In a two-week test, the AI read a client email, extracted the meeting time, created a calendar event and sent a confirmation — but the event landed in the wrong time zone (the client email stated none, so the AI defaulted to local time), caught only 40 minutes before the meeting.
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.
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.
His inbox gets so much mail that about half of what matters was being missed and a quarter sat in spam. His AI watches the box, sorts what is important, and messages him in a separate chat when something he cares about lands; it took a while to tune the prompt before it matched his judgment.
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.