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.
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.
Hemant Kadam, demonstrating his 'craziest use case' after a couple of days on the AI, opened the app to a Sarvam DevOps Engineer application page. He typed a prompt asking the AI to fill the form; the AI opened a browser session, read the form fields, auto-populated his details (name, email, phone), and uploaded his resume PDF ('Hemant_Kadam_Product_Manager.pdf').
UFC fighter Justin Gaethje (verified, 3.7M followers) introduced his AI 'Highlight' for his training, travel, and business schedule. A notification reminded him of a Phoenix flight; he asked for tee times and the app showed options (Legacy, Aquila, Raven, Encanto) — he booked Raven Golf Club at 1:30 PM.
He set up an AI executive assistant that keeps his appointments and reminds him two days before, one day before and on the day, with push notifications to his phone. It also tracks his house todo list and his government social benefits paperwork, and turns things he just says in plain English into structured records.
Lixka, an accelerated nursing student at Mercy University, uploaded all six syllabi to her AI 'Mila'. Mila identified that Monday, September 28th was a 'triple-header' — two quizzes and a Pharm lab she hadn't noticed — then built a sustainable weekly rhythm around fixed classes, clinicals, and workouts, and asked permission before creating three tracked goals: quiz prep, reflection paper, and workouts/downtime.
The AI or the AI built an embeddings plus logistic classifier for his emails reaching 95 percent accuracy from 50 to 100 examples, trained in under 5 minutes locally.
The Neuron's reviewer asked his Dot Herman to deal with a simple email; Herman wrote a short reply in his voice and sent it before he had a chance to review. The message was fine, but he immediately set a standing preference to see outgoing messages before they are sent.
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.
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.