Evaluate whether performance optimizations are actually needed based on your specific context, data size, and operation cost. Avoid implementing optimizations that add complexity without meaningful benefit.

For small datasets (< 100 items), techniques like debouncing may be unnecessary unless they prevent expensive operations such as API calls, URL parameter updates, or complex computations. Consider the trade-off between code complexity and actual performance gains.

Example of contextual evaluation:

// Question: Do we need debouncing for 30 items?
const DebouncedSearchInput = ({ onSearch }) => {
  // If onSearch only filters local data: debouncing may be overkill
  // If onSearch triggers URL updates or API calls: debouncing is valuable
  
  useEffect(() => {
    const timer = setTimeout(() => {
      onSearch(searchTerm); // Expensive operation?
    }, 350);
    return () => clearTimeout(timer);
  }, [searchTerm]);
};

Before adding performance optimizations, ask: What specific problem am I solving? Is the current performance actually problematic? Will this optimization provide measurable benefit given my data size and use case?

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