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Agentic AI Has a Control Plane Problem — Because It Became the Control Plane
Agentic AI control plane governance is the architecture problem most teams are not modeling — and the one that will produce the most expensive failures in 2026. The control plane became the most sensitive layer in modern infrastructure. So we locked it down. Kubernetes gave us control plane isolation — the API server, etcd, and…
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Inference Observability: Why You Don’t See the Cost Spike Until It’s Too Late
The bill arrives before the alert does. Because the system that creates the cost isn’t the system you’re monitoring. Inference observability isn’t a tooling problem — it’s a layer problem. Your APM stack tracks latency. Your infrastructure monitoring tracks GPU utilization. Neither one tracks the routing decision that sent a thousand requests to your most…
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Cost-Aware Model Routing in Production: Why Every Request Shouldn’t Hit Your Best Model
Your system isn’t expensive because your models are expensive. It’s expensive because every request defaults to the most capable model you have. That’s not a cost problem. That’s a routing problem. And most systems don’t have a routing layer at all. Part 1 established why inference cost emerges from behavior, not provisioning. Part 2 explained…
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Autonomous Systems Don’t Fail. They Drift Until They Break.
Autonomous systems drift before they fail. Software fails loudly. A service crashes. An API returns 500. A pod restarts. The alert fires. You respond. Autonomous systems don’t work that way. They degrade quietly. They drift. They accumulate small deviations — a few extra tokens here, one more model call there, a retry loop that fires…
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LLM Ops vs. DevOps: Managing the Lifecycle of Generative Models in Production
The incident ticket looked fine. For years, every dashboard told us the same thing: the system was flawless. But the support queue told a different story. Suddenly, the chatbot was handing out 90% discounts that didn’t even exist. No crashes, no slowdowns, and no error messages. It was just… wrong. We checked everything. The model…
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Stop Renting Intelligence: The Architect’s Case for On-Prem DSLMs
The new center of gravity. Visualizing the shift from massive public cloud “Brain” models to distributed, highly specialized on-prem “Neural Nodes.” AI repatriation isn’t a trend anymore — it’s an architectural reckoning. For the last two years, enterprises treated AI like a utility bill: swipe the corporate card, send data to an API endpoint, pay…
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