A random mix from the whole library. Shuffle for a new set.
Paired with Zapier, the AI checks his spam folder for mail that should not be there; most scans find nothing, but the few real messages it rescues make it worth running. It also uploads and catalogues invoice payments for the finance team, work he used to do by hand.
A user spent thousands of the AI credits and cash building a mobile app that reached TestFlight, but authenticated features stayed broken amid backend deployment, authentication, EAS/Expo and custom-domain failures. Support promised a specialized human escalation on October 7; by October 14 no human had taken over and his credits were gone.
A dedicated segment of the same session shows the AI auto-dubbing his videos into English, opening his Urdu-language lessons to an English-speaking audience.
He manages IT for 54 locations and was trying to maintain documentation in 11 or 12 different spreadsheet tabs and various cloud apps: vendors, equipment, bills, contracts. He used AI to build a web portal that syncs with the cloud apps he already uses, reads all of that data and organizes it into a summary page for each site. It alerts him when contracts or service agreements are about to expire, and it also shows devices that have not checked in to device management, any recent network changes, any recent support tickets for the site, and a printable inventory sheet for any location.
Editing his own audio meant cutting out every breath by hand. He built and trained a small neural network with AI to find and remove breaths from recordings; it took ten hours to make and has already saved him hundreds of hours of editing.
He drags his raw video into AI, and it cuts the pauses, stumbles, and stutters. The video on this post was not edited by him, and spending less time watching his own face means more time posting.
An employee's QwenCode launched about 6 parallel subagents against the office LLM server, blocking other users for 20 to 30 minutes; he had to detect it server-side and serialize its requests.
Asked the AI to break his team's own Postgres MCP guards and it found pg_logical_emit_message, which writes to the WAL inside a read-only transaction, leading to a hardened replacement.
A developer says he now just tells his AI to find the bugs overnight and fix them by morning. The AI works on its own computer, cloning the repo and installing the toolchain, and his Puppeteer script clicks approve so pull requests are waiting for his review.
Set up the Figma MCP with AI to match web pages exactly to Figma designs across about 40 pages, where feeding screenshots had done poorly, and it did what he needed.
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.