New items don't have to wait for their first clicks before entering recommendations. Modern recommender systems generate neural embeddings from item text and images, which allow a new product to be positioned relative to existing catalog items based on content similarity alone. A product with a complete description and quality images can be surfaced to relevant users from the moment it is added. The practical implication is that metadata quality and completeness at upload time directly determines how quickly new products reach the right audience.