This workflow automates the creation and publication of AI-generated LinkedIn posts tailored for engineering leaders and tech decision-makers. It begins with a scheduled trigger that activates every six hours, initiating a series of AI-driven content processes.

First, the workflow uses Google Gemini Chat Models to generate engaging content topics focused on DevOps, MLOps, and cloud engineering challenges relevant to CTOs, VPs, and founders. These topics are parsed into structured data, including compelling titles, rationales, and hooks.

Next, a content creation node synthesizes detailed LinkedIn posts based on the selected topics, with customizable tone and style settings. Simultaneously, hashtags are generated to enhance post visibility, targeting industry-specific, niche, and audience-related tags.

Additionally, the workflow employs AI to generate relevant images that visually complement the post content, increasing engagement. All components — text, hashtags, and images — are then merged and automatically published to LinkedIn.

This workflow is ideal for continuous content marketing, thought leadership, and personal branding efforts for engineering executives seeking to maintain a consistent online presence driven by AI insights and automation.

Node Count	>20 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.lmChatGoogleGemini, @n8n/n8n-nodes-langchain.openAi, @n8n/n8n-nodes-langchain.outputParserStructured, linkedIn, merge, scheduleTrigger, set, stickyNote