Introduction
Evals for the AI product manager
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1. Why AI Products Need Evaluation
What's an AI evaluation—and why is GenAI different?
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The stakes: Trust, safety, and business risk
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2. Designing Your First Eval
Choosing eval approaches across the product lifecycle
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Identify failure modes
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Create an initial dataset for your eval
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3. Building Scalable Evaluation Systems
Manual evals: Human labeling
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Automated evals: Code evaluators and LLM as judge
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Writing effective eval prompts: Common mistakes and best practices
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4. From Metrics to Decisions (Levers as a Product Leader)
How do I know I can launch my feature?
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Have I done enough evaluations to now act as a product leader?
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How do I report evals to leadership?
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How do iterate based on product metrics?
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5. Build Your Eval Plan
Next steps: Implementing and iterating on evals
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Ex_Files_AI_Evaluations_for_Product_Leaders.zip
(20 KB)