AI Should Assist OS Schedulers, Not Replace Them, Argues Developer

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A developer essay argues that embedding individual AI models in every application for resource management adds computational overhead without improving system-wide efficiency. The operating system already has a holistic view of memory, CPU scheduling, and process contention that no single application-level model can replicate. However, the author notes that the OS has a blind spot: it can observe resource demand but cannot fully infer user intent or priority. The essay proposes a limited role for AI — handling ambiguous, multi-signal situations where deterministic rules fall short — while keeping the OS as the final authority over resource decisions. It also recommends that any AI-influenced optimization must have a pre-defined deterministic rollback condition, so recovery never depends on the same model that made the original call.

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