Why Large Language Models Are Replacing CSS Selectors in Web Scraping

CSS selectors for web scraping are fundamentally fragile—every UI update, A/B test, or dynamic class name breaks extraction pipelines. LLM-powered zero-shot extraction solves this by understanding semantic meaning instead of relying on structural patterns. This shift from structural to semantic mapping could transform data engineering, moving teams from constant maintenance to building scalable, AI-driven data collection pipelines.