Extractor vs Lovable

“Schema-driven extraction with LLM fallback is exactly right. Traditional scrapers break on every site redesign — Extractor adapts because it understands the content semantically. The TypeScript-first approach with strong typing on outputs is chef's kiss for building data pipelines.”

“Best MVP builder on the market right now. The Supabase integration means you get a real database, not just a frontend. GitHub sync seals the deal.”

“LLM extraction costs add up fast at scale. But for the use cases where you need it — scraping sites with unpredictable layouts, extracting from pages that change frequently — the reliability improvement over CSS selectors easily justifies the token spend.”

“The demos are impressive but dig deeper and you'll find spaghetti code, missing error handling, and no tests. Fine for demos, dangerous for production.”

“I have been using this to pull structured data from competitor landing pages and product directories. The schema definition is intuitive and the extraction quality is surprisingly consistent even across wildly different page designs.”

“I built a client project prototype in under an hour. They were blown away. Even if I rewrite the code later, the speed-to-wow is worth the subscription alone.”