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Operations

    Unsupervised Producing the work can be handed to a machine. Answering for it cannot. What an organization values when machines do most of the making, what people are for, and four things to try this week. opinion ai strategy Shadow AI Is an Operating Problem, Not a Ban Banning AI tools removes your visibility, not the tools. Make the governed path the fast path and pull usage into the control plane. governance ai security Power Belongs on the AI Roadmap Power, not models or GPUs, is the binding constraint. Treat energy and capacity as roadmap dependencies with real lead times. ai architecture strategy Regulatory Divergence Is a Routing Problem One global AI policy is wrong in every market. Tag requests by jurisdiction, data class, and user type, then route policy like cost and capability. governance ai privacy Reliability Is the Autonomy Ceiling Capability earns the demo; measured reliability earns the autonomy. Budget autonomy by failure cost times failure rate. ai reliability operations Agent Identity Is the New Control Plane An agent that acts needs an identity—scoped, short-lived, attributable, revocable—not a shared API key. ai reliability security Token Prices Fell. AI Bills Did Not. Per-token prices keep falling while bills climb. Manage cost per governed workflow, not price per token. cost ai executive The Benchmark You Didn't Build Public benchmarks are contaminated and gamed. The only eval that matters runs on your traffic, your failure modes, your bar—and you own it. ai reliability metrics Leading Senior Engineers in the AI Era: Autonomy, Standards, and Accountability Leading senior engineers on AI work needs one concrete standard: a definition-of-done built on evals, named failure modes, and escalation triggers. leadership ai teams Agentic Systems at Scale: The New Reliability Contract Agentic systems need SRE-style reliability contracts with explicit blast-radius limits, fallback paths, and kill switches. ai reliability operations The Anti-Fragile AI Organization The best AI organizations do not merely survive model churn and vendor shocks; they convert each one into a capability they keep. teams ai reliability The Executive Case for Local-First AI Infrastructure Local-first AI is not ideology. It is control over placement, margin, latency, and failure modes. ai architecture cost The Post-Prototype AI Org: Operating Models That Survive Year Two Canon post — Year-two AI failure usually comes from org-design mismatch, not model-quality mismatch. The handoffs are where the system slows down. ai teams leadership The Operating Cadence: Turning AI Leadership Interfaces Into Predictable Output Canon post — Interfaces describe who owns what. Cadence is what turns those interfaces into compounding output. leadership ai operations Decision Latency as a P&L Variable: The Leadership Metric Nobody Owns Canon post — Decision latency is measurable and should be treated as a direct cost driver. leadership metrics strategy How Great CTOs Design AI Roadmaps That Survive Contact With Reality Canon post — AI roadmaps fail when they are sequenced around ambition instead of dependency, verification, and rollback cost. strategy ai leadership Hiring for AI Teams: The Operator Profile That Actually Scales The highest-leverage AI hires are operators who can handle ambiguity, systems tradeoffs, and verification pressure. hiring ai leadership Build the System the Model Cannot Break Canon post — A manifesto for building AI-native organizations. Twelve tenets across strategy, architecture, economics, and people — and the only test that matters in year two. opinion ai strategy The Throughput Engineer: Why Headcount Is a Lagging Metric Canon post — Headcount is a lagging metric. The best engineering organizations measure throughput: decision speed, defect containment, and constraint removal. leadership productivity operations SRE Principles Are Great. The Cargo-Culting Is Not. The SRE hype train has everyone copying Google's playbook without asking whether it fits. What actually matters when you're not running at planet scale. reliability devops operations