N8N LinkedIn Creators Agent: A Workflow for Discovering AI Builders at Scale

A growing number of LinkedIn users share automation workflows and AI agent builds that demonstrate how everyday tasks can be simplified or eliminated. These posts often include screenshots, diagrams, or step-by-step explanations and serve as practical learning resources for builders and practitioners. However, discovering this content consistently is difficult. Manual feed browsing is inefficient, search results are noisy, and valuable posts are often buried beneath unrelated content. This paper presents a modular automation workflow built in n8n that supports the discovery of LinkedIn creators who publicly share workflow-based solutions. The system combines AI-assisted query generation, public Google search, structured result extraction, lightweight email pattern inference, and persistent logging. The project was developed over a period of more than three months with iterative feedback and collaboration involving both undergraduate and graduate students. Rather than acting as a ranking or recommendation system, the workflow functions as a repeatable discovery tool that reduces the time required to find creators whose workflows address common, time-consuming tasks. The results demonstrate that discovery itself can be treated as an automation problem and addressed using transparent, public, and modular systems.