LLM Development: Write Evals Before Prompts for Reliable Features

Developing LLM features can be improved by adopting a test-driven approach, similar to traditional software engineering. This involves creating an "eval" set of inputs with expected outcomes before writing the prompt. This eval set should be built from real-world failures and corrections, rather than imagined scenarios, to accurately reflect production issues. By running the prompt against this comprehensive eval set, developers can identify regressions and reliably improve LLM performance. AI

IMPACT Adopting a test-driven approach with comprehensive eval sets can lead to more reliable and robust LLM feature development.

RANK_REASON The item discusses a methodology for LLM development, not a specific release or event.

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