A random mix from the whole library. Shuffle for a new set.
Peter Yang gave the AI Duet one short request and a link to his YouTube channel. Duet pulled a year of his published videos and their public data and built a report with charts, which found that personal AI agent videos are his breakout topic and that his solo videos now beat his guest videos unless the guest shows a real demo.
DeepSeek upgraded gnarly, exploitable PHP 7.x code to fully patched PHP 8.3 in about 15 minutes for a few dimes of tokens.
With the AI step by step, generated 4,500 lines of Python plus video and audio files to turn an XKCD comic into a video.
A field service worker loaded the AI with every user and service guide for the products he repairs, plus all advisories and known issues. He runs each job's action plan through it: The AI checks the parts are on the original parts list, flags advisories, and builds a step by step PDF for the repair. On a product he barely knew, its diagnosis named a different component than the plan he was given. After six hours with his engineering team he followed the agent's call and it fixed the machine.
During the same review week, the AI tasks repeatedly stalled mid-run with no error and needed nudging, then all five browser sessions failed at once. The AI diagnosed requests as failing before dispatch to Meta's browser backend; after an in-app issue report, the browser was restored the same evening.
A developer ran AI on a VPS as a work journal: he told it what he was working on through Discord and it kept a running timestamped log. Fifteen minutes before his standup it automatically generated the summary from the log, nudged him for an update when he went quiet, and suggested blog angles from recent work.
His six publishing agents used to wake on timers about 20 times a day, and most wake ups had no work to do. Switching to waking only when a task arrives cut the daily bill from $5.86 to $1.21, about 79% less, and September's four long form articles cost $50.53 total.
Commenting on the 26 use cases post, he says he uses AI to find and apply to jobs. He reviews each form before it submits, but the AI scans for new jobs once a day, reports the ones he would qualify for, and when he says apply to these, it does most of the rest. It remembers his preferences, like salary range. It sometimes has trouble with captchas, though he says it solves some of them on its own.
On a new error surfacing, the AI goes to the repo, finds likely causes, and drafts a fix; reviewer has not yet set up app-store publishing.
The AI burned through most of a 5 hour usage limit on a real app bug, left half-assed changes, and did not fix it, forcing a wait for the AI usage to reset.
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.