How Rippling Went AI-Native Across Every Product in 6 Months with Deep Agents and LangSmith

Rippling has developed a sophisticated AI-powered workforce management platform to handle its extensive data model spanning HR, IT, finance, and global operations. The AI layer, built on LangChain Deep Agents and LangSmith, facilitates reasoning across thousands of tables and shared concepts that vary by context, overcoming challenges in disambiguation due to overlapping entity names. The multi-agent system includes specialized Deep Agents for querying structured and unstructured data, executing write operations, and a supervisor agent that coordinates tasks. Critical to its success is context engineering, achieved through dynamic skill injection and sandboxed code execution to maintain reliability and audibility. The team implemented a robust evaluation and observability loop using LangSmith for continuous quality improvement, enabling a scalable AI system that serves millions of users globally. Their approach emphasizes building systems familiar to LLMs and creating effective tools for agentic reasoning while maintaining a self-healing evaluation loop to ensure ongoing system health and performance.