The same principle applies to any factual claim. When discussing market trends, cite specific growth percentages and time periods. When mentioning company performance, include actual revenue figures or user counts. When describing product features, provide concrete specifications rather than abstract descriptions. Each piece of specific data you add increases the likelihood that AI models will view your content as authoritative and citation-worthy.
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It is also necessary to emphasize that many optimizations are only possible in parts of the spec that are unobservable to user code. The alternative, like Bun "Direct Streams", is to intentionally diverge from the spec-defined observable behaviors. This means optimizations often feel "incomplete". They work in some scenarios but not in others, in some runtimes but not others, etc. Every such case adds to the overall unsustainable complexity of the Web streams approach which is why most runtime implementers rarely put significant effort into further improvements to their streams implementations once the conformance tests are passing.
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