How Grab enabled R8 optimization for its Android app at scale—over 9 million lines of code and 100+ engineers. We achieved 25% Application Not Responding (ANR) reduction, 16% app size decrease, and 27% faster startup through AI-assisted debugging with Model Context Protocol (MCP) tools, pragmatic testing strategies, and optimized feedback loops.

Grab is a leading technology company in Southeast Asia, offering a wide range of services, including ride-hailing, food delivery, and digital payments. Through its platform, Grab provides convenience, accessibility, and reliability to millions of users across the region. From their blog developers can learn from Grab's innovative approach to technology and business, gaining insights into building scalable, customer-centric platforms that address real-world challenges and improve people's lives.

Grab Tech Blog

Grab's Android engineering team shares how they successfully enabled R8 full optimization for their 9M+ line codebase after multiple failed attempts over six years. The key innovations were: (1) AI-assisted debugging using custom MCP server tools to automate APK decompilation, stack trace deobfuscation, and parallel CI branch testing via GitLab CLI; (2) a progressive risk-based testing strategy that leveraged pattern recognition to fix root causes across the codebase rather than exhaustive regression testing; and (3) infrastructure improvements including a targeted Mainframer EC2 setup for local R8 builds and QA/production build configuration alignment. The results after ~10 weeks: 25% ANR reduction, 16% app size decrease (21.6MB), and 27% faster startup time.

Enabling R8 optimization at scale with AI-assisted debugging