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If AI coding is lowering your code quality, you're not managing quality right

If AI coding is lowering your code quality, you're not managing quality right

Iouri Khramtsov· ·5 min read · 0 reactions · 0 comments · 4 views
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Here’s a defensive setup that I’ve seen successfully used in practice, both on my team and elsewhere.Layer 1: Getting the requirements rightOne of the biggest surprises after I started using spec-driven development was the drop in bugs in the freshly written code. Before spec-driven development, when building, e.g., a new feature, the teams I was on often spent up to a third of the total effort on the post-development “polishing,” i.e., discovering and fixing various bugs. Many of these bugs occurred either because we didn’t foresee certain interactions and edge cases, or because the developer was tired that day and didn’t put in enough thought, or because the designer or PM didn’t think through certain scenarios.

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If AI coding is lowering your code quality, you’re not managing quality rightIouri KhramtsovSep 14, 2026ShareOne common take on the coding agents that I see goes something like this: “Sure, AI helps you output more code, but won’t the quality suffer?”It certainly will if you just blindly merge the PRs and send them off to prod. But if you take a thoughtful, layered approach to managing quality, I find that it’s possible to not just keep the number of bugs stable but actually reduce it—while still increasing the output by 2-2x.Many of these defensive layers are pretty much the same as before Claude/Copilot/Codex/etc. (though they’re made easier now by AI), while others are new.

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