Scrape Tech Discussions → Summarize with AI → Create Knowledge Base
Automatically collect valuable technical discussions from forums and social media, generate AI summaries, and build a searchable knowledge base for your development team.
Workflow Steps
PhantomBuster
Scrape discussion threads
Set up phantoms to scrape relevant technical discussions from Reddit (r/MachineLearning, r/programming), Hacker News, and LinkedIn posts. Configure to run daily and extract thread titles, content, comments, and engagement metrics.
Make (Integromat)
Process scraped data
Create a scenario that triggers when PhantomBuster completes scraping. Filter discussions by engagement level (upvotes, comments) and relevance keywords. Clean and structure the data for AI processing.
OpenAI GPT-4 (via Make)
Generate structured summaries
Send discussion content to GPT-4 with a prompt to create: executive summary, key technical points, actionable insights, and relevant tags. Request output in a structured format with consistent headings and bullet points.
Notion
Create searchable database entries
Automatically create new pages in a Notion database with the AI summary, original discussion link, tags, date, and source platform. Set up properties for easy filtering by technology, difficulty level, and relevance score.
Workflow Flow
Step 1
PhantomBuster
Scrape discussion threads
Step 2
Make (Integromat)
Process scraped data
Step 3
OpenAI GPT-4 (via Make)
Generate structured summaries
Step 4
Notion
Create searchable database entries
Why This Works
Transforms scattered online discussions into organized, searchable knowledge while AI summaries make technical content quickly digestible for busy developers.
Best For
Development teams and tech companies building internal knowledge repositories from community discussions
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