Automated Curated Learning Resources from HackerNews

This workflow enables users to discover top learning resources related to a specific topic by analyzing HackerNews comments and posts. Starting with a webform input, it searches HackerNews for relevant discussions and comments, retrieves detailed information on each comment, and filters out those that provide resources or insights about learning. The workflow employs a language model (Google Gemini) to analyze and synthesize the comments, extracting and categorizing the best resources such as courses, articles, videos, and books, along with their difficulty levels. The curated list is then formatted in Markdown, converted to HTML, and emailed to the user. This automation is highly useful for learners seeking personalized, crowdsourced educational content without manual effort, ensuring they get the most reputable recommendations based on community feedback.