Once you've identified target queries, the automated system tests them periodically—daily, weekly, or on whatever schedule makes sense for your monitoring needs. Each test queries the AI model with your specified prompt, captures the response, parses which sources were cited, and records whether your content appeared. Over time, this builds a database showing your visibility trends, how often competitors appear for the same queries, and which topics you're gaining or losing ground on.
Instead of yielding one chunk per iteration, streams yield Uint8Array[]: arrays of chunks. This amortizes the async overhead across multiple chunks, reducing promise creation and microtask latency in hot paths.
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