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

3 hours ago
  • Spec-driven development, with AI reviewing requirements for gaps and edge cases, significantly reduces bugs.
  • AI-assisted test-driven development should prioritize writing test cases before implementation to avoid validating bugs.
  • Manual testing remains essential, as it catches issues automated processes miss and limits productivity gains to 2-3×.
  • Extensive automated end-to-end tests are crucial for verifying core functionality but cannot replace manual testing.
  • AI code quality passes can address security, complexity, and style issues with minimal time investment.
  • Human code reviews are still necessary for complex changes, while AI reviews add complementary oversight.
  • Production monitoring with auto-diagnosis tools can identify and even fix bugs post-deployment.
  • With layered defenses, coding agents can double output without increasing bugs, potentially reducing them.