As React applications grow past a handful of screens, the patterns that worked for a small prototype start to break down. Folder structures become tangled, state is scattered across dozens of components, and every new feature takes longer to ship than the last. Here is how we structure large-scale React apps for our clients.
Feature-Based Folder Structure
Rather than grouping files by type (all components in one folder, all hooks in another), organize by feature. Each feature folder owns its components, hooks, types, and tests. This keeps related code close together and makes it obvious what can be deleted when a feature is removed.
State Management: Match the Tool to the Job
- Local component state for UI-only concerns like toggles and form inputs
- React Query or SWR for anything that comes from a server, including caching and revalidation
- A lightweight global store (Zustand or Context) only for state that is genuinely shared across unrelated parts of the tree
A common mistake is reaching for a heavy global state library for everything. Most "global" state is actually server state in disguise, and dedicated data-fetching libraries handle caching, retries, and stale data far better than hand-rolled reducers.
Performance Optimization That Actually Matters
Memoization has a cost too, so apply it deliberately rather than everywhere. Focus first on code-splitting routes, virtualizing long lists, and lazy-loading below-the-fold content. These three changes typically deliver more perceived speed than micro-optimizing individual components.
Typed From the Ground Up
TypeScript pays for itself many times over in a growing codebase. Defining strict types for API responses, component props, and shared state catches entire classes of bugs before they reach production and makes refactoring safe enough to do often.
