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Developers argue AI coding quality depends on quality management systems, not AI capability

Iouri Khramtsov argued in a Substack post that falling code quality in AI-assisted development stems from inadequate quality management practices rather than inherent AI limitations. Khramtsov described a layered defensive approach combining spec-driven development, review processes, and testing that maintains or reduces bug rates while increasing output 2-2x. The argument frames AI coding productivity as compatible with quality when paired with structured governance rather than blind PR merging.

read1 min views1 publishedSep 21, 2026
Developers argue AI coding quality depends on quality management systems, not AI capability
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According to a Substack post by Iouri Khramtsov, the core issue when AI-assisted code lowers quality is inadequate quality management practices, not inherent AI limitations. Khramtsov describes a layered defensive approach combining spec-driven development, review processes, and testing that maintains or reduces bug rates while increasing output 2-2x. The argument frames AI coding productivity as compatible with quality when paired with structured governance rather than blind PR merging.

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