Inference Routing Is Becoming an Infrastructure Placement Problem

<p>80% of engineering teams miss their AI infrastructure cost forecasts by more than 25% — not because they're spending wrong, but because they're managing three fundamentally

<p><a class="article-body-image-wrapper"

<p>Shadow IT used to mean a SaaS subscription purchased outside the approval process. The fix was a procurement policy and a software catalog. It was an application-layer problem

<p>Vertex AI has been Google Cloud's AI development platform since 2021. On April 22, 2026, at Google Cloud Next in Las Vegas, Google retired it — not with a deprecation notice,

<p>What three independent research groups concluded in early 2026 — and what it means for anyone building agent pipelines today</p> <p>In the first quarter of 2026, at least three

<p>How it works:</p> <p>Request arrives at an OpenAI-compatible endpoint<br /> Classifier detects task type + complexity<br /> Adaptive router picks the highest-scoring model for

<h1> Local Models vs Cloud Models — The AI Advantage Is Moving From Access to Infrastructure </h1> <h2> Core thesis </h2> <p>AI is no longer new.</p> <p>The question isn't

<h1> Complete Guide to llm-d CNCF Sandbox — Kubernetes-Native Distributed LLM Inference Framework </h1> <p>At KubeCon Europe 2026 in Amsterdam, IBM Research, Red Hat, and Google