A Generative AI Engineer is preparing a corpus of long-form product manuals (avg 40 pages each) for a RAG application. They plan to use an embedding model with a maximum input context of 512 tokens. During testing, they notice that chunks frequently exceed this limit and are silently truncated, causing the tail of each chunk's content to be excluded from the embedding. What is the most appropriate action to ensure complete content is represented in the vector index?