1 link tagged with all of: ai coding + testing + accuracy + andrej karpathy + prompt engineering
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This GitHub repo by Andrej Karpathy outlines four simple rules in 65 lines that boost AI coding accuracy from 65% to 94%. It covers thinking before coding, keeping implementations minimal, making surgical changes, and defining clear success criteria.
- A 65-line CLAUDE.md file allegedly boosted AI coding accuracy from 65% to 94%
- The guide is attributed to Andrej Karpathy and reportedly hit 220,000+ stars on GitHub
- It boils down to four rules: think before coding, keep implementations minimal, make surgical/targeted changes, and define clear testable success criteria upfront