Master 50+ principles of AI-native coding. Each principle is battle-tested and designed to make you a more effective developer.
Showing 12 of 12 principles
Prompt Architecture
Define scope, stack, and file roles before generation.
Design Patterns
Design the API surface before writing the implementation.
Development Process
Iterate in small, testable increments rather than big rewrites.
Debugging
Ask the AI to explain its reasoning and identify potential issues.
Quality Assurance
Write tests first, then implement to satisfy the tests.
Robustness
Implement consistent error handling and recovery strategies.
Architecture
Structure code with clear separation of concerns and logical grouping.
Efficiency
Identify and resolve performance bottlenecks systematically.
Code Quality
Use descriptive, intention-revealing names for variables and functions.
Design Patterns
Inject dependencies rather than hard-coding them.
Documentation
Keep documentation close to code and update it together.
Development Process
Add complexity gradually, testing each increment thoroughly.
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