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Don’t make exceptions

Consistency in software development practices is fundamental for maintaining code quality and scalability. When teams make exceptions to established methodologies, whether in naming conventions, documentation standards, or type systems, they create inconsistencies that compound over time - especially with AI systems.

These inconsistencies not only complicate human understanding but also significantly impact AI systems' ability to accurately interpret and work with the codebase, leading to degraded performance in code generation and analysis tasks.

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While humans might adapt to inconsistent coding patterns, AI systems heavily rely on predictable structures. Inconsistencies in naming, organization, or typing can severely impair AI's ability to understand and generate code accurately.

Recommendation

Establish and strictly enforce development standards across all aspects of the codebase, from naming conventions to file organization. Create automated checks that validate adherence to these standards during the development process. Implement linting rules, code formatters, and pre-commit hooks to ensure consistency. When changes to standards are needed, update them systematically across the entire codebase rather than allowing isolated exceptions.

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