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How Good Abstraction Boundaries Determine If a New AI Model Needs Code Changes

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Most AI model announcements require no code changes at all, provided a codebase has well-defined abstraction boundaries. Only four things can meaningfully differ in a new model release: pricing and metadata, the model identifier, the request or response surface, and output behaviour. Pricing and identifiers are almost always configuration updates, while changes to the request or response surface are the only category that reliably demands new code. Behavioural shifts — such as different verbosity or refusal thresholds — require evaluation rather than development, yet are the most dangerous because they arrive silently. Key risks include SDK upgrades that quietly change defaults, deprecation dates buried in documents, and new capabilities that existing provider-neutral interfaces cannot accommodate without architectural trade-offs.

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How Good Abstraction Boundaries Determine If a New AI Model Needs Code Changes · ShortSingh