Eval-driven development: Build better AI faster

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Introduces eval-driven development as a new testing paradigm for AI and probabilistic systems, detailing code-based, human, and LLM-based grading methods. Explains the shift from deterministic to probabilistic systems and the AI-native flywheel. Uses Vercel's v0 as a practical example, highlighting its eval strategy including refusal and safety evals, and code-based quality checks.