A random mix from the whole library. Shuffle for a new set.
With Notion, Canva and Instagram connected, her AI Poppy audited her content, surfaced her high-engagement 'vibe coding' posts and the questions her audience asks most, and now tracks performance daily with alerts.
He runs a freelance video editing studio and a coding studio, and his project folders were a mess across drives. He started a small folder making script with AI and kept adding to it daily for five months. It is now a 100,000 line Rust program with 1,390 tests that holds every project he has, gives each a permanent ID, and jumps him to any project on any drive or machine with one command.
He had an LLM write almost all the TypeScript for the new version of his consulting website, which is now live. Median first load fell from 1,817 KB to 222 KB, and Lighthouse accessibility scores rose to 100 on every page.
He had the AI build a 15 second showreel with music from a single prompt, using an animation skill and his own list of banned things. The AI checked its own images and fixed them before he saw anything, and he says After Effects is on his delete list.
Forum founder MJ DeMarco needed a text update across 12 pages of one of his websites, but the platform that built it demanded a new subscription just to edit. He gave the AI access to the site folder instead; it made all the changes in about 3 minutes, avoiding an estimated hour of manual editing and a $20/month subscription.
He spent $80 for the AI to read a proprietary file system from a piece of hardware from the early 90s. The AI extracted all the files intact.
Got the AI to build a focus app for his Mac; he uses it daily and says he does more good work with it.
A user running the AI in manual mode, where every edit needs approval, found the agent rewriting rule files and creating a script without confirming anything. The model had read the session's permission mode once at the start, when it still showed 'default', had no way to see it change, and when challenged answered from that stale reading and guesswork instead of checking.
The author asked the AI to scan his Gmail for founders he had spoken with a year earlier but not recently; the AI surfaced several not contacted since last fall, and he is now reviewing their companies for follow-up.
Ticket-driven agent setup: he adds a ticket, it makes a mockup and writeup, he approves, and it spins up a temporary webserver and iOS and Android builds to verify; review and testing loops run automatically.
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.