Optimizing Zed AI-Generated Code for Performance

Zed AI may generate Rust code that clones data unnecessarily instead of borrowing, or uses heap allocations where stack allocations are possible. TypeScript code may miss opportunities for efficient data structures. Generated code generally compiles and runs correctly but may not be optimally performant

Profile generated code in performance-sensitive paths. For Rust, review unnecessary clone() calls and prefer references. Use Flamegraph or cargo-criterion to identify generated code that contributes to hot paths. For TypeScript, check for unnecessary object spreading and array copies in tight loops

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 Zed AI 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.