The practical challenge is balancing the benefit of updates against the time investment required. You can't refresh every piece of content constantly, so prioritize based on importance and competitive pressure. Content that generates significant traffic or ranks well in AI responses deserves regular attention to maintain those positions. Content about rapidly changing topics needs more frequent updates than evergreen material. Content facing new competition from recently published articles needs refreshing to remain competitive.
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TransformStream creates a readable/writable pair with processing logic in between. The transform() function executes on write, not on read. Processing of the transform happens eagerly as data arrives, regardless of whether any consumer is ready. This causes unnecessary work when consumers are slow, and the backpressure signaling between the two sides has gaps that can cause unbounded buffering under load. The expectation in the spec is that the producer of the data being transformed is paying attention to the writer.ready signal on the writable side of the transform but quite often producers just simply ignore it.