Optimizing Jules-Generated Code for Performance

Jules may implement features in a straightforward way that works correctly but is less efficient than what a developer with domain knowledge would choose. Without understanding the data volume or performance requirements, it may choose algorithms or approaches that are correct but not optimally scaled

Include performance requirements in issue descriptions for Jules — specify expected data volumes and latency targets. Review Jules PRs for algorithmic complexity on any code that handles variable-sized data. Add performance tests to CI for critical paths

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 Jules 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.