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EngineeringEnabling R8 optimization at scale with AI-assisted debugging
How Grab enabled R8 optimization for its Android app at scale, over 9 million lines of code and more than engineers. Read how we achieved 25% ANR reduction, 16% app size decrease, and 27% faster startup through AI-assisted debugging with MCP tools, pragmatic testing strategies, and optimized feedback loops
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EngineeringReclaiming Terabytes: Optimizing Android image caching with TLRU
In the quest to optimize app performance, managing the image cache was crucial. This blog takes us on a journey from a traditional Least Recently Used (LRU) cache to a Time-Aware Least Recently Used (TLRU) cache. This innovative approach reclaimed terabytes of storage across millions of devices while maintaining user experience and controlling server costs. Discover how Grab's TLRU implementation cleverly balances storage optimization and performance, offering a glimpse into the future of app development.
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EngineeringCursor at Grab: Adoption and impact
A look inside how we scaled AI-assisted coding across Grab, moving Cursor from pilot to daily use to help us work faster and more reliably. Read what changed in our workflows with Cursor, how we integrated it responsibly, and what’s next for Cursor within Grab's ecosystem.
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EngineeringDocker lazy loading at Grab: Accelerating container startup times
Large container images were causing slow cold starts and poor auto-scaling for Grab's data platforms. This post explores how we implemented Docker image lazy loading with Seekable OCI (SOCI) technology, to achieve faster image pulls and startup times. The blog discusses how lazy loading works, the technology behind SOCI and eStargz, and finally how this configuration delivered a 60% improvement in download times.
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EngineeringFrom deployment slop to production reality: How BriX bridges the gap with enterprise-grade AI infrastructure
Built an AI tool that works locally but can't scale enterprise-wide? Learn how BriX tackles this deployment gap, turning prototypes into governed, production-grade solutions—no engineering team required.
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Engineering · Design · ProductDemystifying user journeys: Revolutionizing troubleshooting with auto tracking
In the dynamic realm of mobile development, understanding user journeys is key to effective troubleshooting. This blog delves into how Grab's innovative AutoTrack SDK has revolutionized session tracking. By addressing the challenges of incomplete user journey data, Grab has significantly reduced downtime, boosted customer satisfaction, and enhanced developer efficiency.
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EngineeringHow Grab is accelerating growth with real-time personalization using Customer Data Platform scenarios
Grab’s Customer Data Platform (CDP) introduces Scenarios, enabling real-time personalization at scale. By leveraging event triggers, geo-fencing, historical data, and predictive models, Grab delivers dynamic user experiences like mall offers, traveler recommendations, and ad retargeting. Proven results include more than a 3% uplift in conversions, driving growth across Southeast Asia.
Engineering
From firefighting to building: How AI agents restored our team’s core productivity
The Analytics Data Warehouse (ADW) team at Grab supports over 1,000 users. These users support an extensive repository of more than 15,000 tables. To alleviate the time-consuming demands of repetitive tasks, the team implemented a multi-agent AI system. This system autonomously handles simpler inquiries and collaborates on more complex requests, reclaiming significant engineering bandwidth and unlocking hundreds of hours of productivity each month.
