The article argues that code serves two intertwined roles: precise instructions for machines and a shared conceptual model of the problem domain for humans. It emphasizes building a clear domain vocabulary through names, types, and abstractions, noting that programming languages are tools that shape how we think and communicate about systems. As LLMs and agents generate more code, the human role shifts toward defining intent, crafting domain models and specifications, and validating that generated code faithfully represents the real-world concepts—suggesting code’s modeling function will remain essential even if its form changes.

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