AI Doesn't Write Code — Systems Do (And Most People Are Missing This)

This article argues that the common perception of AI writing code is inaccurate. Instead, it's the systems built around AI that are responsible for generating and refining code, not the AI models themselves.

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The article explains that the common perception of 'AI writing code' is a misconception. What's actually happening is that systems built around AI models are responsible for generating and refining code, not the AI models themselves. These systems leverage the predictable nature of software engineering, instant feedback loops, and the need for 'good enough' code to succeed. However, AI has limitations in areas like long-term architecture, state/memory, and debugging complex systems, as these require causal reasoning beyond just pattern matching. The article argues that the real intelligence lies in the feedback loop and iteration engine, not just the AI model. This is leading to a shift in the role of engineers, from writing code to designing systems and orchestrating AI workflows. The article warns that over-reliance on AI can lead to shallow understanding, fragile systems, and hidden technical debt, as engineers may lose their 'code intuition'.