7 Habits of Highly Effective Generative AI Evaluations
summary
Claims that evaluations are the missing piece to scale with a concrete customer story: a document‑processing workload goes from 22% to 92% accuracy after adding an evaluation framework, built via 100 test cases, prompt decomposition and semantic routing. Evaluations run fast (target 30 seconds), use generative AI judges plus Python for numeric checks, attach per‑step metrics to a gold standard, and surface exact failure modes so fixes are straightforward and reproducible.
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chapters (11)
- 0:00Introduction
- 1:14Biggest challenge in scaling generative AI
- 4:01What are evaluations
- 5:20Why evaluations are important
- 9:40Customer use case
- 15:48Pace of innovation
- 18:17Quantifiable
- 21:23Individual Evaluation
- 22:09Diverse Evaluation
- 22:30Traditional Evaluations
- 23:25Example
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