This project explores a structured AI-driven content creation workflow designed for quality control rather than one-click automation. Built with n8n, the system helps create content at scale while keeping review checks at every step.

As an example implementation, I developed an AI Tech Influencer pipeline. The workflow begins by identifying top-performing weekly posts from selected subreddits, ranking them based on engagement signals such as upvotes. A user selects a topic, after which the AI generates structured content that can be reviewed, edited, and refined before moving forward.

The pipeline then progresses to image generation, where users can either upload a reference image or generate multiple AI-driven options based on custom instructions. After selecting the preferred visual direction, the system proceeds to video generation, producing a final content piece ready for Social platforms.

Unlike fully automated avatar systems, this workflow prioritizes controlled progression. Each stage requires user approval before advancing, ensuring content quality, alignment, and creative ownership remain intact.
The result is a scalable AI-assisted influencer system built for meaningful content production rather than automated noise..