Optimizing GitHub Copilot-Generated Code for Performance

Copilot suggests importing full libraries for single utility functions. It generates synchronous patterns where async would be more appropriate. It sometimes produces unnecessarily complex algorithms when simpler native methods exist

Audit imports — replace full library imports with specific function imports or native alternatives. Profile the application and identify Copilot-generated hot spots. Replace complex implementations with simpler ones where functionality is equivalent

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 GitHub Copilot 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.