GitLab Code Suggestions: Why You Should Not Build Your Own Generative AI Product for Code

GitLab's attempt to develop a competitive generative AI product for code autocomplete, leveraging Google's Codey model, has faced significant challenges, highlighting the difficulties of building a robust code LLM from scratch. Despite being in beta for eight months, GitLab's solution is limited in language support, IDE availability, and integration capabilities, trailing behind established competitors like Codeium and GitHub Copilot. Key issues include poor context integration, inadequate model capabilities such as Fill-in-the-Middle, and subpar output quality, exacerbated by their reliance on third-party models and servers, which contradicts GitLab's core security ethos. The challenges underscore the complexity of developing an effective AI tool for coding, a field that requires specialized expertise and user feedback for continuous improvement. While GitLab's efforts are commendable, their current offering remains uncompetitive, although the rapidly evolving nature of AI in coding suggests potential for future enhancements.