Optimizing Lovable-Generated Code for Performance

Lovable apps load all data on page mount without pagination, which works fine with 10 rows but crawls with 1,000+. Images are loaded at full resolution without optimization. The component tree is deeply nested with many wrapper components that add DOM elements but no functionality. Supabase queries often fetch all columns when only a few are needed

Add pagination or infinite scroll for data-heavy views. Implement image optimization with a CDN or compression pipeline. Flatten the component tree by removing unnecessary wrapper divs. Select only needed columns in Supabase queries. Add database indexes on columns used for filtering and sorting. Implement SWR or React Query for client-side caching of Supabase data

Before optimizing, measure. Use your browser's Lighthouse audit to get a baseline score. Check Core Web Vitals (LCP, FID, CLS) — these directly affect your Google ranking. Use the Performance tab in DevTools to identify which components take the longest to render. For server-side performance, add timing logs to API routes to find slow endpoints.

The fastest way to improve performance: optimize and lazy-load images, enable compression on your server, remove unused CSS and JavaScript, implement code splitting so users only download code for the page they're viewing, and add proper caching headers for static assets. These changes alone can cut load times significantly.

If your Lovable app uses a database, slow queries are often the biggest performance bottleneck. Add indexes on columns you filter or sort by. Use SELECT to fetch only the columns you need instead of SELECT *. Implement pagination for lists — loading 10,000 rows at once will always be slow. Consider adding a caching layer for data that doesn't change frequently.