We built Cortex Code to solve the context gap in AI development by engineering the industry's first data-native coding agent that is deeply coupled with the underlying data platform. We architected a system that directly interfaces with Snowflake's metadata, compute, and governance layers, giving the agent real-time environment awareness of table structures, operational semantics, and security.
In this session, we will dive into how we constructed this context-aware reasoning loop, utilized open standards like MCP and agents skills for extensibility, and solved the challenge of delivering an agent that accelerates complex data engineering and ML workflows while remaining secure-by-design. We will also share our experiences with benchmarking and optimizing Cortex Code on public and internal benchmarks.
Umesh Unnikrishnan | Product Leadership | Snowflake
