My Journey to Automating a RAG Daily Report with n8n

Why am I doing this?

Because most AI digests talk about model releases or flashy tools—zero focus on real-world RAG use cases. I wanted a daily workflow that curates “industry RAG best practices, practical tips, and fresh case studies,” so I built one with n8n.

Where I’m at:

1、Tool Hunt: Zapier—too rigid; Make—friendly UI but no self‐host; pure Python—freedom at the cost of maintenance. Winner: n8n (open‐source, extensible, steeper UI learning curve).

2、Workflow Highlights:

• Schedule Trigger → NewsAPI fetch for “RAG” → AI Agent (OpenRouter free model) summarizes & rewrites

• JavaScript node for formatting → push via Enterprise WeChat bot → manual copy to personal group (Yes, WeChat automation is a headache, so I opted for a semi‐automated approach)

• Backup entries to Google Sheets for analytics and future reuse

Status: Live in my member group for a week—daily updates are stable-ish, though I’ve hit random crashes at 2 AM (don’t ask how I know 😂).

3、Next Steps:

• Expand signal sources and refine AI summarization

• Turn six months of case studies into short videos

• Launch limited beta in a paid community

Real talk: over‐engineering can become a trap—tools are means, not ends. I’d love to hear your thoughts: What pitfalls did I miss? How would you improve this? Drop a comment or DM—let’s co-create a better RAG daily report!