Discover Top Learning Resources & Instantly Receive Curated Recommendations
Generate a curated list of learning resources from HackerNews comments in under 2 minutes, saving hours of manual research and analysis.
Manual searching for reliable learning resources on platforms like HackerNews is time-consuming and often yields unorganized information. This workflow leverages AI to automatically scrape HackerNews, extract top learning resources, categorize them by type and difficulty, and deliver a curated, publication-ready list directly to your inbox.
Documentation
AI-Powered HackerNews Learning Resource Curator
This workflow is designed to streamline the process of discovering high-quality learning resources directly from HackerNews discussions. It's perfect for anyone looking to quickly identify top books, courses, articles, and videos recommended by the community, categorized by type and difficulty, without sifting through countless comments.
Key Features
- Automates scraping of HackerNews "Ask HN" threads for relevant discussions.
- Utilizes Google Gemini and LangChain to intelligently extract, categorize, and rank learning resources from comments.
- Categorizes resources by type (e.g., course, book, video) and estimated difficulty (beginner, advanced).
- Performs sentiment analysis on comments to identify the most positively recommended resources.
- Delivers a professionally formatted, hyperlinked list of top recommendations directly to your email inbox.
How It Works
Users initiate the workflow by submitting a learning topic and their email address via a simple n8n form. The workflow then searches HackerNews for relevant "Ask HN" posts and their associated comments. These comments are aggregated and fed into a Google Gemini AI model via LangChain, which processes the text to identify, categorize, and rank the best learning resources. Finally, the AI-generated markdown list is converted to HTML and emailed to the user, providing an efficient way to discover community-vetted educational content.