Cursor at Grab: Adoption and impact

This post details the adoption and impact of the AI coding assistant Cursor at Grab. It highlights a multi-tool strategy for AI coding assistants, with Cursor achieving 98% monthly active users and a 50% suggestion acceptance rate. Key utilization patterns include unit test generation, code refactoring, cross-repository navigation, and bug fixing. Custom tooling was developed for monorepo indexing and Grab-specific coding conventions. The post also touches on the expansion of AI-assisted development to non-engineering roles and the observed productivity gains.