This guide covers extracting publicly accessible data. Always review a site's robots.txt and Terms of Service before scraping. Building an automated pipeline to extract LinkedIn data requires resilient infrastructure and a modern approach to parsing. When dealing with unstructured public web data, standard HTTP requests and regular expression matching quickly break down. Target platforms continuously iterate on their UI, run complex A/B tests, and heavily obfuscate their CSS classes. A data API approach solves this inherent fragility. Instead of writing and maintaining hundreds of fragile selectors, you convert raw HTML into strictly typed JSON using an LLM-powered extraction layer. This post covers how to build a scalable, compliant integration for LinkedIn JSON extraction. By defining a structured schema, you can ensure your downstream databases and AI applications receive clean, validated data directly from the edge.…