A random mix from the whole library. Shuffle for a new set.
After hackers hit their research site meta-analysis.cz, which had no central backup, the AI and the AI rebuilt it from Wayback Machine copies and scattered files on their hard drives. The site is now on GitHub, its datasets are archived on Zenodo with a DOI, and every paper has an HTML version next to the PDF.
Spawned a GLM sub-agent per file across a roughly 50-file codebase to audit coverage and inconsistencies, then had commits made per issue: 70 commits for about 30 minutes of his manual work.
He let the AI go through his system and write a first pass of the documentation, including the billing part he felt he had to finish before retiring. The remittances section alone used up a full day of tokens, so the work ran over several days, but it got done and let him retire, or at least half retire, a little earlier.
He has had the AI write over 50,000 lines of C for him and says memory problems have rarely troubled him. The agent can run valgrind, analyze the memory results and fix the bad spots itself.
In a #metapartner showcase, entrepreneur Krystal Oh — who runs a nail salon and a yogurt store solo — shows on-screen chats with her AI 'Coco' handling back-office work: drafting a refund request for an empty box of masks, remembering meetings, sending notifications, helping manage expenses, onboarding employees and scheduling calendars. She says she previously spent thousands on human assistants who never understood her businesses.
They caught their coding agents reading the answer key.
The AI enabled a camera on a test device and he taught it to reboot into the previous kernel on build failure so it could iterate for days; ended with a usable setup and camera login working.
He runs OpenFree, a site that collects open source projects. The AI scans X every day for new projects, filters them, and submits them to his site backend, where a Cloudflare workflow parses each one and sends it to him to approve before it goes live.
Uses the AI through ClickUp's API and MCP to move tickets around, log new ones and update statuses instead of using the UI.
The AI runs his entire video production pipeline via an AI plugin: full 5-minute explainer videos from one prompt, thumbnails and titles, auto-upload via the YouTube API.
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.