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Ten Simple Rules for AI-assisted Coding in Science
Introduction
Introduction
Background concepts and vocabulary
The Rules
1. Preparation & Understanding
1.1. Rule 1: Gather Domain Knowledge Before Implementation
1.2. Rule 2: Distinguish Problem Framing from Coding
1.3. Rule 3: Choose Appropriate AI Interaction Models
2. Context Engineering & Interaction
2.1. Rule 4: Start by Thinking Through a Potential Solution
2.2. Rule 5: Manage Context Strategically
3. Testing & Validation
3.1. Rule 6: Implement Test-Driven Development with AI
3.2. Rule 7: Leverage AI for Test Planning and Refinement
4. Code Quality
4.1. Rule 8: Monitor Progress and Know When to Restart
4.2. Rule 9: Critically Review Generated Code
4.3. Rule 10: Refine Code Incrementally with Focused Objectives
Conclusion
Conclusion
Repository
Open issue
Index
