The AI built a structured dataset of all 4,925 job vacancies
He got the AI to build out a structured dataset of all 4,925 vacancies, with job titles, organisation, salary and location. He shared it in a spreadsheet for other people to play with.
A random mix from the whole library. Shuffle for a new set.
He got the AI to build out a structured dataset of all 4,925 vacancies, with job titles, organisation, salary and location. He shared it in a spreadsheet for other people to play with.
Shervin Shaikh asked the AI in chat to find any NYC parking tickets under his name and pay them; after he supplied his licence plate, the AI found a $115 'No Standing' ticket in Brooklyn, now $145 with penalties. The first CityPay attempt failed on a billing-address mismatch, but the retry succeeded: $147.90 paid via Stripe Link, confirmed on screen.
A local model helped build a self-hosted services wiki and dataset in an Obsidian vault so his partner could keep systems running if he died, set up in a few hours.
The AI sent a notification that it had spotted an email from TripIt, the vacation-planning app Ulanoff uses, about a password change he had forgotten making. The agent wanted to make sure he'd seen the email verifying it was him.
Juan Lombana (verified, 670K followers), reviewing the AI in Spanish, demonstrated two capabilities via screen recordings: a personal-assistant goal tracker (college move-in, golf tee times, movie tickets, trip planning, school-supply shopping, IMAX booking) and WhatsApp integration — forwarding a cinema-ticket screenshot, from which the AI extracted the details, added them to his calendar, and scheduled the event. He compared its assistant-like proactivity favorably to the AI and noted secure payme
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.
A church volunteer runs a weekly hybrid workflow: The AI translates six Chinese daily spiritual messages (Monday–Saturday) into structured JSON under strict rules — Bible quotations in NASB 2020 rather than translated, hymns left untranslated, ministry terminology matched — then Python inserts the text into a PowerPoint template, merges a bilingual twelve-message deck, and converts it to HTML for the church website. He keeps theological review, visual checks and final publishing approval human on purpose.
Mufti Hassan had the AI clean up his full Gmail inbox. The chapter title gives the size of the job: 12,000 emails.
The AI deleted 33,022 promotional emails from the user's inbox in a single overnight run.
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.