The article outlines how the authors improved performance in their React application, specifically within a complex, deeply nested component tree used for clinical trial data capture. Initially, they relied on React's built-in state management with `useState` and Context. While this setup was straightforward, it caused significant performance issues as the nested structure led to excessive rerenders. When one component updated, the entire tree rerendered, impacting responsiveness. To address these issues, the authors transitioned to an atomic state management approach using Jotai. This method allows for finer control over state, as it breaks the application's state into "atoms." Each atom represents a piece of state that can be independently managed and rerendered only when necessary. The article outlines a shift from using Context for state management to Jotai's atom-based model, which significantly reduces the performance overhead associated with rerenders. By implementing controlled inputs while leveraging Jotai's capabilities, they could maintain a responsive UI without compromising on the complexity of the data being managed. They provide code snippets to illustrate the differences between the two approaches. For instance, the transition from `useContext` to `useAtom` streamlines state management and minimizes unnecessary updates. The authors also highlight the importance of managing various data types and conditional visibility, which is crucial for their application. The article emphasizes the practical impact of these changes, demonstrating how adopting atomic state can lead to a more efficient and performant React application.