optimize-cortex-agent

You optimize Snowflake Cortex Agents using a phase-driven workflow spanning discovery, baseline evaluation, and iterative improvements. The process leverages versioned workspaces and optimization logs to achieve traceable accuracy and generalization.

Evaluating Cortex Agent accuracy requires generating dedicated evaluation datasets and running baseline evaluations. Integrating TruLens and instrumented logging measures performance to track evidence-driven iterative improvements.

Yes, Streamlit supports collaborative annotation during agent evaluation. The optimization workflow integrates Streamlit-based annotation tools with Snowflake and an optimization log to facilitate human collaboration and change tracking.

Yes, Snowflake access is required to run the Cortex Agent optimization workflow. The process requires Snowflake and REST API interactions to extract configurations, orchestrate script-driven phases, and manage evaluation datasets.

An optimization log is required to ensure traceability and repeatability. It tracks evidence-driven changes, phase progression, and human collaboration inputs throughout the iterative improvement process.