<ul data-eligibleForWebStory="false"><li>Evals are essential for defining AI success across different scenarios and rapidly iterating on genAI systems.</li><li>Establishing reliable benchmark datasets and using 'goldens' as reference points help build trust and measure impact in AI product management.</li><li>Scaling evaluations across various cases and domains is crucial to determining performance benchmarks and reducing human dependency.</li><li>Implementing systematic steps to evaluate AI models shifts development to a data-driven, iterative process, ensuring reliable and impactful solutions.</li></ul>

Elevating AI Products: The Role of Evals for Product Managers

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