The original title is "Stop Guessing – Use Golden Datasets for Prompt Evals"

Short summary

Golden datasets are curated test cases that serve as quality baselines for prompt engineering, allowing you to measure whether changes actually improve performance rather than guessing. Start with 20–50 representative examples covering common cases and edge cases, then integrate evals into CI/CD to catch regressions before users do. This approach moves from 'I think this prompt is better' to data-driven decisions like 'pass rate improved from 80% to 95%'.

• •Use curated test datasets (golden datasets) as baselines for prompt changes to catch regressions
• •Start with 20-50 high-quality examples covering edge cases and common failures
• •Integrate prompt evals into CI/CD for automated quality checks before shipping

Generated with AI, which can make mistakes.