karpathy-guidelines

To prevent overcomplicating code during refactoring, apply behavioral guidelines that enforce surgical changes, surface hidden assumptions, and maintain simplicity for safer AI-assisted development.

Best practices for AI-assisted code review involve defining verifiable success criteria and focusing on goal-driven execution to identify potential overcomplications and high-risk areas accurately.

You can use these coding guidelines to make LLM debugging safer by emphasizing verification and ensuring the AI focuses only on necessary, surgical changes rather than broad rewrites.

Defining verifiable success criteria for LLM coding tasks requires setting clear, goal-driven rules that ensure the implementation is correct, simple, and safely executed without unnecessary modifications.

LLM-generated code often fails during refactoring because it lacks behavioral constraints, leading to overcomplication and broad changes; applying strict coding rules ensures surgical, goal-driven modifications.