AI agents are often celebrated for one-shotting entire applications, but this framing misses what matters for long-lived software projects. Good software architecture becomes more important, not less, when using AI — clean component boundaries reduce the AI's context window noise just as they reduce human cognitive load. The real shift is from writing code to reviewing it, and at high AI output volumes, codebases can escape human comprehension entirely. Delegating oversight to other AI agents (as Amazon and Microsoft have experienced) leads to production failures. The practical takeaway: treat AI as a tool under human control, maintain proper architecture, and rely on existing trust-generating processes like CI/CD, testing, and code review.
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Code quality only matters in the long runSoftware architecture as context management for AITurtles all the way downWhat should you do about it?Sort: