Hey guys, great job on your work with Dendron! I was first introduced to it over two years ago, but never ventured past basic note taking. Recently, I caught up with your YouTube videos and was happy to see the progress made within the community. Especially the talk by @ScriptAutomate, really got my ideas flowing. It appears that we'll be witnessing more and more vaults (of quite the size) in the near future. Currently, I'm experimenting with LLM's, with a focus on prompt engineering. My goal is to satisfy my immediate need to summarize categories of subscribed-to content by transcribing, summarizing, and organizing it into Dendron. This part is somewhat trivial. The real challenge lies in how to then locate and utilize the readily available content efficiently, and in a way that adapts a reverse model of content consumption (learning on the way in). Do you know if Dendron plans to invest in some form of search capabilities? I believe that would be the icing on the cake in the future. Imagine quickly creating a Dendron vault from a data source containing thousands of books on a particular topic. The classifier would do an excellent job organizing the content in a Dendron-friendly way. However, once the content is organized, the challenge shifts to navigating/absorbing/learning from it. One would highly benefit from some intelligent search techniques (content-aware) to help me navigate the newly acquired knowledge repository. So in other words, we've figured out how to have the AI digest and summarize data. I am not too familiar within the search space, aside from some work on entity resolution.