This article discusses how Cursor's agent uses semantic search to improve code retrieval and accuracy when responding to natural language queries. It highlights the advantages over traditional search methods like grep, including better code retention and reduced user corrections. The piece also details the development of a custom embedding model that enhances search effectiveness.