Eval-driven development: Build better AI faster

Vercel's approach to AI-native software development emphasizes eval-driven development to handle AI's unpredictable nature. Traditional testing methods are ineffective for AI systems, so Vercel uses a new testing paradigm called evals, which include code-based, human, and LLM-based grading to assess AI outputs. This strategy mirrors the shift seen in search engine development and is exemplified in building AI assistants for tasks like generating React components. Evals form the foundation of the AI-native flywheel, driving continuous improvement through data, models, and user feedback.