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Energy calculus reveals that energy optimization can be systematically composed, transforming how we approach energy efficiency in AI systems.
Agentic workloads aren't just long prompts; they're decode-bound beasts with a tool-use personality arc, demanding a rethink of LLM serving infrastructure.
