Measuring AI: engineering a process to save costs
AI is not magic: it is a software component with a precise cost.
Many initiatives fail for lack of sizing: a REST call to the biggest LLM for every task. The cost-per-call formula adds embedding, vector database, firewall, input and output tokens, and infrastructure. With a router, caching, structured outputs and an 80/20 cascade between cheap and frontier models the cost drops sharply, while people stay at the center: the AI pre-fills and the operator validates.
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