🔥 Week 2 Bonus Build — Mini LinkedIn RAG System (Pattern → Post → Email)
I spent this Sunday building something interesting outside of the official assignment; a Mini RAG system for LinkedIn content using n8n + Google Sheets + Gemini.
The goal:
👉 Scrape high-performing posts from top AI creators
👉 Extract structural patterns automatically
👉 Generate fresh LinkedIn posts in my voice, based on proven formats
Here’s how it works:
🧩 Workflow A : Pattern Builder
- Fetches raw posts from a Google Sheet (just post URL + content pasted manually
- Loops through each post
- Sends the content to an LLM and returns structured data:
✔️Hook type
✔️Hook example
✔️Post type
✔️Tone style
✔️CTA style
✔️Writing tricks
✔️Key ideas
4. Saves everything into a Pattern Library Sheet
This turns long unstructured posts into a database of writing patterns.
🧩 Workflow B : Post Generator
- I enter simple inputs:
✔️Niche
✔️Target audience
✔️Post type
✔️Topic hint
2. The system:
Reads multiple patterns from the library
Summarizes them into one master pattern prompt
Generates:
✔️ LinkedIn post
✔️ First comment
✔️ One-line summary
Then emails the output to me automatically.
🧪 Status & Screenshots
✔️ The system works end-to-end
✔️ I received my own AI-generated LinkedIn post + comment by email
⚠️ Hit a Gemini API quota after processing several posts (classic 🤣)
No paid tools.
No external scraper APIs.
Just n8n, Google Sheets, and manual LinkedIn/X copy/paste.
🧠 What I learned today:
- Studying real posts beats “write a LinkedIn post like a human” prompts.
- Data beats creativity. I can replicate viral positioning based on structure and data, not luck.
- Workflow chaining in n8n finally clicked today.
📅 Next steps:
- Add batching + retry logic to avoid API limits
- Auto-scrape LinkedIn comments for CTAs and hook variants
- Export pattern library to Airtable or Notion
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🔥 Week 2 Bonus Build — Mini LinkedIn RAG System (Pattern → Post → Email)
