LLM costs are rising as teams maximize token usage, but not every prompt needs a frontier model. Model routing — directing prompts to the most cost-appropriate model based on task complexity — is emerging as the next abstraction layer for managing AI spend. Tools like Claude Code Router already enable this, and organizations like Coinbase report cutting AI spend in half while increasing token usage. The next evolution will combine prompt preprocessing (AI improving your prompts before routing) with intelligent model selection, shifting focus from hand-crafting prompts for specific models to specifying intent and letting routers handle the rest.
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