I Ran a 24/7 AI Content Pipeline for 7 Days — Here's the Real Data (Blog Ops #2)

I Ran a 24/7 AI Content Pipeline for 7 Days — Here's the Real Data (Blog Ops #2) Last week I pushed a button and walked away. Seven days later, my blog had published 14 posts, deployed 7 Dev.to articles, and generated $0 in revenue. But that's not the interesting part. The interesting part is what broke , what actually worked, and the specific numbers I measured — because every "I automated my blog" post I've read skips that part entirely. This is Blog Ops #2. In #1 I showed the architecture. Here I'm showing the receipts. The Setup (30 seconds, then I'll get to the numbers) The pipeline runs on OpenClaw with cron jobs triggering Claude Sonnet as the content agent (Atlas). Every post goes through: Topic selection — scans recent HN threads, trending GitHub repos, my idea backlog Draft generation — Claude with a strict BRAND.md constraint file Quality gate — automated checks: word count >1500, code block presence, no "In this article" openers Deployment — Dev.to API + Jekyll blog via git