The Content RAG Agent Playbook

May 15, 2026

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A workflow that feeds data into a database, connects it to a RAG agent built in n8n, and automatically produces content and video drafts from your knowledge base.

Angelee Carandang

How it works

Step 1: Collect knowledge base content

Gather all internal content into one structured folder.

Pull LinkedIn posts from target creators using Apify.
Include internal sources:
- SOPs, playbooks, and copywriting
- Blogs, podcasts, previous posts
- Sales call recordings via Ergo
Save all files to a Google Drive folder.

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Step 2: Set up the vector database

Create the Pinecone database that stores your knowledge as embeddings.

Log in to Pinecone and create a new index.
Set embedding model to OpenAI text-embedding-3-small.

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Step 3: Build the data ingestion pipeline

Automate the flow from Google Drive into Pinecone using n8n.

Set up two Google Drive Trigger nodes watching your folder:
- One for File Created, one for File Updated.
Add a Code node to extract and clean text from binary files.
Add a Recursive Text Splitter:
- Chunk size: 1000 characters, overlap: 200 characters.
Connect to a Pinecone Vector Store node set to Insert Documents.
Log every ingested file to a Google Sheets tracking sheet.

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Step 4: Configure the RAG agent

Build the agent that reads your knowledge base and generates content.

Add an AI Agent node in n8n with Claude or OpenAI.
Set temperature to 0.3.
Connect Pinecone Vector Store as a tool in Retrieve Documents mode.
Add a Simple Memory node set to 5 conversation window.
Write the system message defining the agent's role and instructing it to call the vector store on every query.

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Step 5: Connect social listening signals

Feed the agent real-time niche content alongside the knowledge base.

Monitor LinkedIn via Jungler AI and X.com via Tweet Hunter.
Pull signals from YouTube, View Stats, Reddit, and Clay.
Route incoming posts into the agent's context as live input.

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Step 6: Connect Slack as the front end

Replace the test chat trigger with a live Slack integration.

Create a Slack app at api.slack.com/apps.
Add bot token scopes: app_mentions:read, chat:write, channels:history.
Replace the Chat Trigger in n8n with a Slack Trigger node.
Add a Slack Response node to post replies to your dedicated channel.

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Step 7: Generate content drafts

Use the agent to produce written content from the knowledge base.

Route output to a Writer and a Designer.
Distribute across:
- LinkedIn via Ordinal
- X.com via Tweet Hunter
- Newsletter via Beehiiv

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Step 8: Generate video drafts

Use the agent to produce video scripts alongside written content.

Route output to a Script Writer for refinement.
Record and send to a Video Editor.
Publish to YouTube.

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Step 9: Track performance

Measure what lands and feed learnings back into the knowledge base.

Track via Hyperfury, Shield, and YouTube Studio.
Add high-performing content back into Google Drive as new SOPs.

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