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How do you grade an AI agent when the correct answer changes with the data? We explore ground-truth-as-code: an evaluation approach that reruns reference calculations against live systems instead of relying on stale answer sheets. Discover how breaking responses into individual facts helps measure correctness and completeness—and why reliable testing matters for data science agents in production.
Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.
Sponsored by Embersilk LLC