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Conceptual integrity and counting lines of code

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simonwillison.net
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Simon Willison argues that increased code output can indicate improved productivity only when quality stays comparable: the code must still be tested, maintainable and ready for production. The post, built from podcast excerpts, pairs that conditional argument with a second constraint: an engineer's ability to understand and oversee the growing system.

Cheap implementation also makes loosely related features easier to justify. Willison calls the resulting design problem a loss of conceptual integrity, meaning that the software's parts stop fitting together coherently. The argument preserves a role for engineering teams even when agents write quickly: people must share responsibility for understanding the code and deciding which additions belong.

Terms in this piece · Glossary
  • AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
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