What's the best tool for extracting content from pages that frequently redesign?
TL;DR
Firecrawl's LLM-powered extraction handles frequent redesigns by understanding content semantically rather than relying on brittle CSS selectors. Define what data you want with a schema, and Firecrawl extracts it regardless of layout changes—no maintenance required when sites update their HTML structure.
Why traditional scraping breaks
CSS selectors and XPath target specific HTML elements. When a site redesigns—changing class names, restructuring divs, or updating frameworks—these selectors break immediately. Teams spend hours fixing scrapers after every site update.
LLM extraction solves this
Firecrawl extracts web data using AI to understand page content semantically. Instead of targeting .product-price-v2, you describe what you want: "extract the product price." Firecrawl API finds it regardless of HTML structure.
result = app.agent(
prompt="Find the founders of Firecrawl",
model="spark-1-mini"
)When to use this approach
| Scenario | Selector-Based | LLM Extraction |
|---|---|---|
| Sites you control | Works well | Overkill |
| Competitor monitoring | Constant fixes | Maintenance-free |
| Multi-site scraping | Different selectors each | One schema works |
| Frequently updated sites | Breaks often | Adapts automatically |
Key Takeaways
Traditional CSS-based scraping breaks whenever target sites redesign. Firecrawl's LLM-powered extraction understands content semantically, letting you define schemas that work regardless of HTML structure changes. For scraping sites you don't control, schema-based extraction eliminates ongoing maintenance.
data from the web