Finding these queries requires a different research approach than traditional keyword research. Rather than using tools that show search volume and competition metrics, you need to understand what questions your target audience actually asks AI models. This means thinking about their problems, concerns, and information needs, then formulating those as conversational queries. Tools like an LLM Query Generator can help by analyzing your content and suggesting relevant questions people might ask to find that information.
But the triumphance of V3 is in the addSourceBuffer hook which solves a subtle problem. In earlier versions, hooking SourceBuffer.prototype.appendBuffer at the prototype level had a vulnerability in that if fermaw’s player cached a direct reference to appendBuffer before the hook was installed (i.e., const myAppend = sourceBuffer.appendBuffer; myAppend.call(sb, data)), the hook would never fire. The player would bypass the prototype entirely and call the original native function through its cached reference.
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