The Context Challenge: Why AI Coding Competition Isn't About Code Quality Anymore

As AI coding projects scale beyond a few dozen files, the real differentiator shifts from raw code generation to sophisticated context management across repositories. This insight fundamentally changes how developers should evaluate AI tools—moving away from benchmark scores toward practical metrics like long-session stability and architecture consistency. The future of AI coding success lies not in writing individual lines faster, but in orchestrating complex multi-file workflows while preserving system-wide integrity.