This n8n workflow automates the entire process of curating, creating, and publishing tech-related content from RSS feeds to Medium, with human review and multimedia generation. It starts by fetching articles from multiple tech RSS feeds like The Verge and TechCrunch, then merges and filters out previously posted content using a Google Sheet as a reference to ensure uniqueness. A random article is selected and processed through AI models (Google Gemini, Groq, and Pollinations) to generate a well-structured article, an engaging cover image, and a formatted summary. The content is uploaded to Google Drive and inserted into a Google Doc for review. The workflow then sends notifications via Slack for manual approval, allowing human reviewers to approve or reject the article. Approved content is simultaneously published to Medium and emailed via Gmail, while rejected articles trigger notification alerts. This automation streamlines content creation, maintains content freshness, prevents duplicates, and integrates AI for content and image generation, making it ideal for tech blogs or media teams aiming for efficient publishing cycles.

Node Count	>20 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.lmChatGoogleGemini, @n8n/n8n-nodes-langchain.lmChatGroq, code, gmail, googleDocs, googleDrive, googleSheets, httpRequest, if, merge, noOp, rssFeedRead, scheduleTrigger, set, slack, splitOut, stickyNote, wait