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    <title>code quality on Agile Software Development</title>
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      <title>Technical Debt in the AI Era Is Accumulating at a Different Rate</title>
      <link>https://agilesoftdev.com/technical-debt-in-the-ai-era-is-accumulating-at-a-different-rate/</link>
      <pubDate>Sat, 02 May 2026 00:00:00 +0000</pubDate>
      
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      <description>Technical debt was always a metaphor with a compounding interest rate. Decisions made quickly to ship a feature cost more to address the longer they remained in the codebase. Teams that managed debt well built systems that stayed malleable. Teams that ignored it built systems that eventually could not be changed without risk of collapse.
AI-assisted development has not eliminated this dynamic. It has accelerated the principal. The speed at which code can be generated means that architectural decisions — or the absence of them — propagate through a codebase faster than ever before.</description>
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      <title>Testing AI-Generated Code Requires a Different Default Posture</title>
      <link>https://agilesoftdev.com/testing-ai-generated-code-requires-a-different-default-posture/</link>
      <pubDate>Sat, 02 May 2026 00:00:00 +0000</pubDate>
      
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      <description>Test-driven development was always more useful as a design discipline than a testing strategy. Writing the test first forced clarity about what the code was supposed to do before any implementation decisions were made. The red-green-refactor loop was valuable because it built understanding incrementally.
AI-assisted development has resurfaced this distinction in an unexpected way. When code can be generated quickly from a specification, the temptation is to generate the implementation first and the tests afterward — or to generate both simultaneously and treat passing tests as evidence of correctness.</description>
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