Building Your First Agentic AI Workflow

Step 1: Creating Your N8N Workspace

Log into your N8N account and create a new workflow. You’ll start with an empty canvas that includes a Schedule Trigger node by default.

Setting Up the Manual Trigger:

1. Click the “+” button to add a node
2. Search for and select “Manual Trigger”
3. This allows you to test your workflow by clicking “Execute”

For production use, you can later replace this with a Schedule Trigger to run automatically at defined intervals—hourly for breaking news monitoring or daily for morning news summaries.

 

Step 2: Adding the RSS Reader

The RSS Reader node will fetch news content from your chosen sources. RSS feeds are structured data formats that most news organizations provide, updating automatically as new articles are published.

Configuration Steps:

1. Click “+” after the Manual Trigger
2. Search for and select “RSS Read”
3. Connect the nodes by dragging from the Manual Trigger output to RSS Read input
4. Double-click the RSS Read node to configure it

RSS Feed URLs (tested in the workshop):

For Saudi-focused news:

https://www.saudigazette.com.sa/rss.xml

For Lebanese/regional news:

https://www.lbcgroup.tv/rss

Paste one of these URLs into the RSS Read configuration, press Enter, then click “Execute Step” to test. You should see 20-50 news items loaded successfully.

 

Step 3: Implementing Cost Control with Data Limits

RSS feeds often return 50+ articles, which would be expensive to process through AI models. The Limit node restricts the number of items processed while maintaining workflow functionality.

Adding the Limit Node:

1. Click “+” after the RSS Read node
2. Search for and add “Limit”
3. The node auto-connects to RSS Read
4. Set the default limit to 10 items
5. Click “Execute Step” to verify

The result should show 10 items instead of the original 50+, significantly reducing processing costs while maintaining representative coverage.

 

Step 4: Configuring AI Analysis

This step transforms your workflow from simple data collection to intelligent content analysis. You’ll need two connected nodes: a Basic LLM Chain and an OpenAI Chat Model.

Adding the AI Processing Nodes:

1. Click “+” after the Limit node
2. Search for and add “Basic LLM Chain”
3. Click “+” again and add “OpenAI Chat Model”
4. The OpenAI model connects to provide the AI capabilities for the LLM Chain

 

Step 5: Setting Up OpenAI API Access

This is a critical step that enables your workflow to access AI capabilities. The process requires careful attention to security since API keys provide access to paid services.

Obtaining Your API Key:

1. Navigate to platform.openai.com
2. Click your profile icon in the top right
3. Select “API keys” from the dropdown
4. Click “+ Create new secret key”
5. Name it “N8N Workshop” or similar
6. Critical: Copy the key immediately—it’s shown only once
7. Store it securely until you paste it into N8N

Connecting the API Key in N8N:

1. In the OpenAI Chat Model node, click “Create new credentials”
2. Paste your API key in the credentials field
3. Click “Save”
4. Select your preferred model (GPT-3.5-turbo for cost efficiency, GPT-4 for higher quality)

 

Step 6: Crafting Effective AI Analysis Prompts

The quality of your AI analysis depends heavily on prompt construction. A well-designed prompt provides clear instructions, expected output format, and specific analysis criteria.

Configure the Basic LLM Chain:

1. Double-click the Basic LLM Chain node
2. Set “Prompt Source” to “Define below”
3. Enter this analysis prompt:

Analyze the following news articles and provide structured summaries:

{{$json}}

For each article, provide:
1. Main Topic: One sentence describing the primary subject
2. Key Facts: Specific developments, numbers, or announcements
3. Relevance Score: 1-10 rating for general business/tech interest
4. Impact Assessment: Why this matters for readers
5. One-Line Summary: Concise takeaway for busy professionals

Format the output as clean, scannable text with clear separations between articles.

Click “Execute Step” to test the AI analysis. You should receive structured summaries of your news items.

 

Step 7: Adding Content Formatting and Filtering

Before sending results via email, you’ll want to format the data and potentially filter based on relevance scores.

Add Edit Fields Node:

1. Click “+” after the Basic LLM Chain
2. Search for and add “Edit Fields”
3. Configure it to add metadata:
   • summary: {{$json.response}}
   • timestamp: {{$now}}
   • source: “AI News Monitor”

Optional Conditional Logic: For more advanced filtering, add an “IF” node that checks relevance scores:

• IF relevance score >= 7, proceed to email
• ELSE skip this article

 

Step 8: Email Notification Setup

The final step transforms your analysis into actionable communication. You have two primary options for email integration.

Gmail Integration (Recommended):

1. Click “+” after your formatting node
2. Search for and add “Gmail”
3. Select “Send Email”
4. Follow the Google OAuth authentication process
5. Grant N8N permission to send emails from your account

Email Configuration:

To: your-email@domain.com
Subject: AI News Summary - {{$now.format('YYYY-MM-DD')}}
Body: 
Your daily AI-curated news summary:

{{$json.summary}}

Generated automatically by your AI agent
Timestamp: {{$now}}
Source: {{$json.source}}

Alternative SMTP Setup: If OAuth proves complex, use the “Send Email (SMTP)” node with your email provider’s SMTP settings. This approach is often more reliable for automated workflows.

 

Step 9: Complete Workflow Testing

Execute your entire workflow by clicking “Execute Workflow” at the top of the N8N interface. Watch each node execute in sequence:

1. Manual Trigger activates the workflow
2. RSS Feed loads current news items
3. Limit reduces dataset to manageable size
4. AI analyzes and summarizes content
5. Fields are formatted with metadata
6. Email summary is sent to your inbox

Troubleshooting Common Issues:

RSS Error: Verify URL format and network accessibility. Test URLs directly in your browser.

AI Error: Check OpenAI API key validity and account credit balance. Verify the connection between Basic LLM Chain and OpenAI Chat Model nodes.

Email Error: Confirm authentication permissions and recipient address validity.

Node Connection Issues: Ensure all nodes are properly linked with visible connection lines.

 

Advanced Integrations and Extensions

Multi-Channel Notifications

Expand your workflow’s reach by adding multiple notification channels:

Discord Integration:

1. Add a “Discord” node after AI analysis
2. Create a Discord webhook in your server settings
3. Configure the node with your webhook URL and message content

Slack Integration:

1. Add a “Slack” node
2. Connect your Slack workspace
3. Choose target channels for different types of news

Processing Multiple RSS Sources

Scale your monitoring by processing multiple news sources simultaneously:

Split Workflow Configuration:

1. Add a “Split Out” node after Manual Trigger
2. Configure multiple RSS sources:

json

[
  {"url": "https://www.saudigazette.com.sa/rss.xml", "source": "Saudi Gazette"},
  {"url": "https://www.lbcgroup.tv/rss", "source": "LBC News"},
  {"url": "https://feeds.bbci.co.uk/news/rss.xml", "source": "BBC News"}
]

Each source processes independently, providing comprehensive coverage.

Intelligent Content Filtering

Enhance your AI analysis with sophisticated filtering criteria:

Analyze these news articles and identify only those related to:
- Technology and AI developments
- Regional business and economic news
- Innovation and startup activities
- Government policy affecting business

Assign relevance scores 1-10 for each category.
Return only articles scoring 7+ in any category.
Ignore: Sports, entertainment, routine political coverage.

Articles: {{$json}}

Data Storage and Historical Analysis

Add persistence to your workflow for trend analysis:

Google Sheets Integration:

1. Add a “Google Sheets” node
2. Create a spreadsheet with columns: Date, Source, Title, Summary, Relevance Score
3. Auto-populate with each workflow execution

Database Storage: For larger-scale operations, integrate MySQL or PostgreSQL nodes to store processed articles, enabling historical analysis and trend identification.