How AI Coding Tools Are Teaching New Lessons About Software Development Principles
By
ashirviskas
Slow-proofed and worth the wait. Worth its weight in flour.
Summary
The article explores how large language models (LLMs) and AI-driven coding workflows are revealing new insights about software development principles, particularly Kernighan's Law about debugging complexity. It discusses how AI tools are teaching developers about language design, code simplicity, and the fundamental relationship between writing and debugging code, suggesting that LLMs are providing a new perspective on established software engineering wisdom.
Key quotes
· 4 pulledDebugging is twice as hard as writing the code in the first place. Therefore, if you write the code as cleverly as possible, you are, by definition, not smart enough to debug it.
I've always understood Kernighan's Law to be about complexity—about keeping the code you write as simple as possible to reason about.
With LLMs now I'm learning it has a lot to do with language design too.
I'm still seeing a decent number of people on Twitter complain occasionally that they've tried AI-driven coding workflows
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