Building with Snowflake Cortex Analyst — What I Learned About Semantic Layers and Guardrails

When I started working with Snowflake Cortex Analyst, I assumed the hard part would be getting the system to answer questions correctly. It wasn't. The hard part was deciding which questions it shouldn't answer. In this post I want to share two things that took more thought than I expected — verified queries and guardrails. A Quick Overview of Cortex Analyst Snowflake Cortex Analyst lets users ask questions in plain English and get answers from structured data. Under the hood, it uses a semantic model defined in YAML to understand the data and generate SQL responses. There are two ways it can respond: Verified queries — pre-validated question-answer pairs you define LLM-generated SQL — the model generates SQL on its own when no verified query matches The goal of a well-structured semantic model is to maximize verified query hits. The more questions route through verified queries, the more controlled and reliable your output. The Verified Queries Trade-off My first instinct was to add a