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& AI Infrastructure
Intelligence for engineers building and operating AI infrastructure at scale. LLMOps, FinOps, Kubernetes, and the tools that keep production AI running.
Deep Technical Guides
Benchmarks run on real infrastructure. Config files you can copy-paste. No vendor fluff.
Cost Optimization Playbooks
Datadog to Grafana migrations. GPU budget triage. Reserved instance strategy. Real savings.
Production Incident Frameworks
Postmortem templates for AI failures. Runbooks your on-call team will actually use.
Latest Articles
View all →Probabilistic Observability 2026: A New AI Debugging Discipline
The 4 primitives for debugging non-deterministic AI: output distributions, semantic traces, statistical regression, hallucination-as-metric. OTel + Grafana.
AI Cost by Workflow 2026: The Tokenmaxxing Layer
Per-workflow token attribution: tag every LLM call with workflow_id, build per-business-process cost dashboards, route workflows to cheaper models.
Agentic Ops Platform 2026: Enterprise Reference Architecture
Enterprise architecture for 200+ internal AI agents: per-agent RBAC, audit logs, sandboxed tools, prompt-injection defense, and the Kubernetes operator pattern.
Inference API Gateways 2026: LiteLLM vs BentoML vs Ray Serve
A practitioner's comparison of three inference gateway and serving stacks — LiteLLM, BentoML, and Ray Serve — when to use each, and the limits.
AI Coding Agent FinOps 2026: Copilot, Cursor, Devin Cost
Per-engineer token costs, per-LOC and per-PR attribution, anomaly detection, and enterprise policy for AI coding agents: Copilot, Cursor, Devin.
The Google Remy Leak: AI Agent Stack Risk in 2026
Google's Gemini Workspace agent stack leaked via OAuth over-scoping, calendar side-channels, and draft-state recovery — a pattern, not a single CVE.
Stay ahead of the stack.
Weekly intelligence on LLMOps, FinOps, and AI infrastructure. No fluff, no vendor pitches. Written by practitioners, for practitioners.