Blog Ops #2: I Analyzed 30 Days of My Content Pipeline — Here's What the Data Actually Said

Blog Ops #2: I Analyzed 30 Days of My Content Pipeline — Here's What the Data Actually Said 30 days in. Real numbers. Some surprises, some embarrassments. When I launched my automated content pipeline last month ( Blog Ops #1 ), I had exactly zero data to back my choices. I was running on gut feeling and Stack Overflow. Now I have 30 days of real pipeline logs, traffic data, and — crucially — a few face-palm moments I want to share. Spoiler : The thing I spent the most time building barely moved the needle. The thing I almost skipped became my highest-traffic driver. Let me show you exactly what happened. The Baseline: What My Pipeline Looked Like on Day 1 Quick recap for context. My setup: Jekyll blog on GitHub Pages Python scripts to cross-post to Dev.to Cron jobs to schedule and automate publishing GitHub Actions for build/deploy Target: 10+ posts/week across blog + Dev.to. Actual output on Day 1: 2 posts published, 3 stuck in draft hell. The Data: 30 Days of Pipeline Logs I instrum