Automated Resource Recommendations for Learning Topics

This n8n workflow automates the process of gathering, analyzing, and delivering the best learning resources from HackerNews comments about a specified topic. It begins with a user-triggered form where the user inputs what they want to learn and their email address. Once submitted, the workflow searches HackerNews for relevant discussions, retrieves comments, and filters those containing resource recommendations. These comments are then aggregated into a single text block and processed through a language model (Google Gemini Chat) to identify top resources categorized by type and difficulty level. The final step involves sending an email to the user with curated, Markdown-formatted resource recommendations. This workflow is ideal for learners seeking personalized, crowdsourced learning guidance from online discussions.