Tyler Richards

The Snowflake product team is sharing their framework and scorecard for AI readiness to help others assess and improve their own AI data posture. The session will cover the importance of reliable, well-structured data, clean semantics, governance and security. Data structure, health and performance: Learn how to address "not-ready" signals like long-running queries and missing data tests. Focus on transforming data into performant, well-structured models that reflect key business concepts. Semantic layering: Get your data AI-legible by encapsulating its meaning in a high-quality semantic layer. We highlight how each component unlocks more power from AI and democratizes data across your organization.

Your enterprise data already holds the answers. The challenge is getting AI to understand it and act on it securely. In this session, our head of AI product shares Snowflake's vision for the agentic enterprise: where every user has a personal work agent that builds context from your data automatically, works across structured and unstructured sources, and operates within full governance. See how customers build sales call analyzers, automate financial reporting and deploy customer-facing agents in minutes. Whether you're building agents with Snowflake CoCo or using them through Snowflake CoWork, you'll leave knowing how to put governed, model-agnostic AI to work.

Join this session to learn best practices and tips from an avid Streamlit app developer since 2019. Let's take a journey through all the mistakes I've made building dozens of productions dashboards used by thousands of people hundreds of thousands of times over the years, using everything from dynamic tables to Snowflake Cortex, with a ton of live coding in between.