karpathy-principles
SolidBehavioral guidelines to reduce common LLM coding mistakes — Think Before Coding, Simplicity First, Surgical Changes, Goal-Driven Execution.
AI & Automation 94 stars
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# Karpathy Coding Principles
Derived from [Andrej Karpathy's observations](https://x.com/karpathy/status/2015883857489522876) on LLM coding pitfalls.
**Tradeoff:** These guidelines bias toward caution over speed. For trivial tasks, use judgment.
## When to Apply
- **Classification**: quick-win, feature, architecture-change, hotfix
- **Phase**: /plan (assumption surfacing), /implement (simplicity + surgical), /review (scope audit)
- **Trigger**: All non-trivial coding tasks — this is a behavioral baseline, not a domain skill
## 1. Think Before Coding
**Don't assume. Don't hide confusion. Surface tradeoffs.**
Before implementing:
- State your assumptions explicitly. If uncertain, ask.
- If multiple interpretations exist, present them ��� don't pick silently.
- If a simpler approach exists, say so. Push back when warranted.
- If something is unclear, stop. Name what's confusing. Ask.
## 2. Simplicity First
**Minimum code that solves the problem. Nothing speculative.**
- No features beyond what was asked.
- No abstractions for single-use code.
- No "flexibility" or "configurability" that wasn't requested.
- No error handling for impossible scenarios.
- If you write 200 lines and it could be 50, rewrite it.
Self-check: "Would a senior engineer say this is overcomplicated?" If yes, simplify.
## 3. Surgical Changes
**Touch only what you must. Clean up only your own mess.**
When editing existing code:
- Don't "improve" adjacent code, comments, or formatting.
- Don't ref...
Details
- Author
- KbWen
- Repository
- KbWen/agentic-os
- Created
- 5 months ago
- Last Updated
- 1 months ago
- Language
- Python
- License
- MIT
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