Fully Automated Tech News Publishing Pipeline with n8n, OpenAI, Google Workspace & Slack

Content creators face a relentless challenge. You need to publish regularly, maintain quality, avoid duplicates, and somehow find time to actually create original work. Manual content curation eats hours of your day. You're copying from RSS feeds, reformatting text, searching for images, creating documents, and juggling approval processes across multiple tools.

What if you could automate the entire pipeline? This n8n workflow does exactly that. It monitors tech news sources, generates polished articles with AI, creates custom images, builds formatted Google Docs, and routes everything through a Slack approval system before final publication. All while you sleep.

What You'll Need to Get Started

Before diving into the workflow automation, make sure you have access to these services and APIs. Most offer free tiers that work perfectly for getting started.

Required APIs and Accounts

• n8n: Your workflow automation platform (self-hosted or cloud)
• OpenAI API: For content generation using GPT-4.1-mini
• Google Gemini API: For AI image prompt creation
• Google Workspace: Access to Docs, Drive, and Sheets APIs
• Slack: For notification and approval workflows
• Gmail: For email delivery of approved content
• Pollinations.ai: Free AI image generation (no API key needed)

Key n8n Components Used

This workflow leverages several powerful n8n nodes that work together seamlessly:

• Schedule Trigger for automated execution
• RSS Feed Read nodes for content sourcing
• LangChain integration for AI content generation
• Google Docs and Drive nodes for document management
• Google Sheets for duplicate tracking
• Slack nodes with approval workflows
• HTTP Request for image downloading
• Custom Code nodes for data transformation

Building Your Automated Publishing Pipeline

Let's break down how to construct this workflow step by step. Each stage builds on the previous one, creating a seamless content automation system.

Step 1: Set Up Multi-Source Content Monitoring

The workflow starts with a Schedule Trigger that runs every six hours. This trigger activates three RSS Feed Read nodes simultaneously, pulling fresh articles from TechCrunch, The Verge, and Ars Technica.

Here's the clever part: the workflow doesn't just grab any article. It connects to a Google Sheets tracking document that logs every article you've already processed. The Merge node combines RSS feed data with your spreadsheet records, and a custom Code node filters out duplicates by comparing URLs.

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The result? Only genuinely new content makes it through. A final Code node randomly selects one article from the fresh batch, ensuring variety in your content pipeline without manual intervention.

Step 2: Transform Raw Content with AI

Once an article is selected, the real magic begins. The workflow uses a LangChain node connected to OpenAI's GPT-4.1-mini model. This isn't just simple text copying. The AI receives specific instructions to act as a professional tech blogger, transforming RSS snippets into comprehensive Medium-style articles.

The prompt engineering here is crucial. The system takes the article title, content snippet, and original link, then generates a complete blog post with proper introduction, body sections, and conclusion. The AI maintains an informative yet accessible tone, perfect for Medium's audience.

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Meanwhile, a parallel branch uses Google Gemini to analyze the article content and generate a detailed image prompt. This prompt follows professional standards for AI image generation, specifying style, mood, setting, and artistic direction.

Step 3: Generate and Store Visual Assets

The image prompt flows into a Code node that constructs a Pollinations.ai URL. This free service generates high-quality images based on text prompts without requiring API authentication. The workflow specifies dimensions (1024x800), adds a random seed for uniqueness, and requests the flux model with no watermark.

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Once the URL is ready, an HTTP Request node downloads the generated image as binary data. The workflow then uploads this image directly to a specific Google Drive folder using the Google Drive node. You get a shareable link that's stored with the article metadata.

This entire image generation and storage process happens automatically while the article content is being prepared.

Step 4: Create Formatted Documents

Now the workflow brings everything together. It creates a new Google Doc with the article title in a designated folder. After a brief wait (to ensure the document is ready), multiple data streams merge: the document ID, the formatted article text, and the image URL.

A series of Code nodes handle the formatting. They extract the title, remove duplicate headings, strip unnecessary tags, and compose a clean final version with the image placeholder, publication date, and properly structured content.

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The Update Doc node then inserts this formatted content into the Google Doc, creating a publication-ready article complete with all metadata.

Step 5: Route Through Approval Workflow

Before anything goes live, the workflow implements a human approval gate. A Slack message gets sent to your designated channel with a preview of the article and a direct link to the Google Doc for review.

The workflow then pauses, waiting for a response. When someone replies with "APPROVE ARTICLE," the Check Approval Status node evaluates the response. Approved articles trigger an email to your specified address (in this case, an iCloud email) containing the full formatted content. The workflow also logs the approved article to your Google Sheets tracker, updating the title, creator, description, and image URL.

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If the article gets rejected, a different Slack notification confirms the rejection, and the workflow ends without sending or logging anything.

Why This Workflow Changes Everything

This automated content publishing system solves multiple pain points simultaneously. You're no longer manually checking RSS feeds or copying and pasting content. The AI transformation ensures every article matches your brand voice and Medium's style guidelines.

The duplicate prevention system saves you from embarrassing republications. The approval workflow maintains quality control without requiring you to monitor the system constantly. And the Google Sheets tracking creates a searchable archive of everything you've published.

Real-World Applications

Content marketing teams can use this to maintain consistent publishing schedules across multiple blogs. Tech newsletters can aggregate and summarize daily news without manual curation. Corporate communications departments can monitor industry publications and create internal briefings automatically.

Solo creators benefit too. You can run this workflow while focusing on original content creation, letting automation handle the content curation side of your publishing strategy.

The Bottom Line

Building an automated content publishing system with n8n isn't just about saving time. It's about creating a reliable, scalable process that maintains quality while eliminating repetitive work. This workflow demonstrates how combining multiple APIs, AI models, and approval systems can transform content operations from manual drudgery into an efficient automated pipeline.

The best part? Once you set it up, it runs continuously. Every six hours, fresh content possibilities appear in your Slack channel, ready for quick review and publication. That's the power of workflow automation done right.