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Every individual thing the AI writes can be correct and the codebase can still rot. Because the model has no memory of the decisions it made three sessions ago, each new session re-derives conventions from whatever fragment of the code it happens to read, and small divergences compound into a system with four error-handling styles, three config patterns, and two competing data models. This episode is about why coherence, not correctness, is the thing that decays in AI-built systems, and what a builder has to externalize to stop it.

 Produced by VoxCrea.AI

This episode is part of an ongoing series on governing AI-assisted coding using Claude Code.

👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way.
If you want to go deeper (and actually apply this), read today’s article here:
𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬

 At aijoe.ai, we build AI-powered systems like the ones discussed in this series.
If you’re ready to turn an idea into a working application, we’d be glad to help.