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Vertex Agility

May 20, 2026

The Agentic AI Advantage: How Token Economics Separates the Programmes That Scale From the Ones That Stall

Google now processes 3.2 quadrillion tokens a month, up from 480 trillion a year ago. While vendors compete on per-token prices, the organisations pulling ahead on AI are the ones tracking a different metric entirely: tokens per business outcome. This article explains why per-token price is the wrong number to optimise, introduces tokens per resolved outcome as the unit that makes agentic AI economics legible, and sets out the three architectural patterns – task decomposition, context discipline, and evaluation-driven model selection – that create durable cost and performance advantages in agentic AI programmes.
May 6, 2026

You’re Budgeting for Infinite AI Compute. The Grid Has Other Plans.

AI data centres are projected to consume more energy than Germany and France combined by 2030, yet most enterprise AI strategies are still built on the assumption that compute is cheap and limitless. This article examines the energy and infrastructure constraints that are closing the brute-force compute era, and sets out the practical architecture shifts – task decomposition, context discipline, evaluation-driven model selection – that organisations need to make now.