GitHub's development of a next-generation code search engine, recently launched as a technology preview, aims to enhance code exploration, navigation, and developer productivity. The new search engine addresses challenges such as the need for precise code navigation, handling large corpus sizes with over 200 million repositories, and accommodating frequent updates due to high rates of pull requests. Traditional search techniques, like stemming and tokenization, are ineffective for source code, prompting GitHub to create a bespoke search engine tailored to code-specific requirements. Initially, GitHub employed solutions like Solr and Elasticsearch for code search, but these faced limitations with special characters and indexing efficiency, leading to the now internally developed Blackbird engine. Blackbird, written in Rust, promises exact-match and regex searches with efficient resource usage, leveraging a sharding strategy by Git blob object ID for storage savings and load distribution. It also incorporates code-specific heuristics for scoring and ranking search results, aiming to prioritize relevant and popular repository matches. The ongoing project reflects GitHub's commitment to leveraging open-source contributions and advanced technologies to significantly improve developer workflows.