This n8n Automation Will 10X Your Income (Fully Free Of Cost!)

Overview

The video demonstrates an n8n workflow that turns a LinkedIn topic and target audience into a researched post, generates an accompanying image, and publishes both to LinkedIn. The presenter frames it as a way to save time and a possible freelance service; the video does not establish that it will increase income by a specific amount.

Workflow and Tools

1. Choose how to run n8n: The presenter describes a 14-day n8n trial, hosting through Render, or installing n8n on a personal server.
2. Collect post details: An n8n On Form Submission trigger presents two text fields: Post Topic and Target Audience.
3. Research and draft the post: An AI Agent uses Google Gemini 2.0 Flash as its language model. The workflow connects to Tavily through an HTTP Request to gather current information, then uses a system prompt to guide research and writing. The form’s topic and audience are passed into the agent using n8n expressions.
4. Create an image prompt: A second AI Agent takes the drafted post and produces a prompt for an image.
5. Generate the image: An HTTP POST request sends that prompt to a Hugging Face FLUX model. The tutorial covers setting up an access token and configuring the request and response fields. It stresses that the generated image field name must match the one used later in the workflow.
6. Publish on LinkedIn: The presenter explains creating a LinkedIn developer app, requesting the relevant sharing and sign-in permissions, and connecting it to n8n with the app credentials and redirect URL. The workflow maps the research agent’s output to the post text and the generated image to the image attachment.

Demonstration and Practical Notes

The presenter tests the workflow with a topic about making money using AI and an audience of 19–25-year-olds. The workflow reports successful execution, and the presenter shows the post on LinkedIn.

The tutorial’s main configuration techniques include importing request details from Tavily’s documentation to avoid entering HTTP parameters manually, using expression mode to pass data between nodes, and checking each stage with test executions.

The presenter describes the tools and models as free options, though the subtitles do not establish that every hosting or API use is free under all circumstances.

Main speaker/source: Zeeshan Shaikh, the video’s presenter. The workflow uses n8n, Google AI Studio/Gemini, Tavily, Hugging Face, and LinkedIn.