This fragmentation hurts portability. Code that performs well on one runtime may behave differently (or poorly) on another, even though it's using "standard" APIs. The complexity burden on runtime implementers is substantial, and the subtle behavioral differences create friction for developers trying to write cross-runtime code, particularly those maintaining frameworks that must be able to run efficiently across many runtime environments.
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This creates both an opportunity and a maintenance requirement. The opportunity is that regularly updating content can improve AI citation rates even if the core information hasn't changed dramatically. The requirement is that high-performing content needs periodic refreshes to maintain its competitive position as newer articles on the same topics emerge.
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