A detailed breakdown of a React chat interface coding challenge reveals the architectural decisions that enterprise teams wrestle with in production chat applications.
The exercise—build a scrollable message list with jump-to-message links and temporary highlights—forces choices about state management, component structure, and DOM manipulation that parallel real-world implementations. The author advocates for centralized state management (messages, highlightedId, inputValue) over distributed component state, a pattern that scales better in enterprise applications.
The technical requirement that "only one message can be highlighted at a time" exposes a common React pitfall: managing timeouts across component lifecycles. The solution—centralized highlight state with proper cleanup via useEffect—mirrors patterns used in production chat SDKs from Sendbird and Stream, which handle similar state coordination challenges at scale.
The choice to keep everything in a single App component initially, extracting components only when complexity demands it, reflects a pragmatic approach that contrasts with enterprise vendor components. KendoReact, Syncfusion's ej2-react-chat (used in 10,000+ enterprise projects), and similar paid solutions ship with pre-extracted, pre-optimized component structures.
The scroll-to-bottom requirement reveals an implied constraint: the container must have fixed height with overflow-y: auto, a decision that impacts mobile responsiveness and accessibility. The author notes that scrollIntoView({ behavior: "smooth" }) provides visual continuity, though enterprise implementations often make this configurable for accessibility compliance.
What's notable: the exercise uses array indices as message IDs, acceptable for append-only lists but inadequate for production systems with message deletion, reordering, or real-time sync. Enterprise chat systems typically use UUIDs or server-generated identifiers.
The walkthrough demonstrates why chat interfaces remain common in technical interviews—they test state management, side effects, DOM manipulation, and architectural judgment simultaneously. For enterprise teams evaluating custom-built versus vendor chat components, the complexity revealed here explains why the chat SDK market is projected to exceed $5 billion by 2028.