AI Strategy tracks AI Transformation of Business Departments. Browse the hub for AI operating model, aimed at CTOs and delivery teams putting AI into real work.
AI operating model
The cut was supposed to prove AI was working. The quiet rehiring is the proof that something else was. AI takes the task; it does not inherit the judgment, ownership, and review standard the seat also held.
AI transformation
An AI agent is not a smarter chatbot. It is a new reader of your system of record, and it can only read what you have made authoritative, current, and governed. The Klarna case is the warning: govern the substrate before you scale the reader.
AI Strategy
MCP is dead. A2A is the future. Everything should be a workflow. Most of these debates are category errors. The tools are not competing. They manage different constraints, and the real decision is which trade-offs your organization can afford.
AI operating model
Five briefings, five departments, five vendor decks. By the fourth one I stopped writing notes. Every deck framed the work as that department's AI strategy. The question underneath was the same in every room, and nobody was asking it.
AI Strategy
The eval set is not a quality artifact. It is the operative specification of an AI product. Whoever curates the failure cases makes the product decisions, regardless of what the PRD says.
AI Strategy
The demo works and the eval suite passes. Then production is always one more sprint away - because every AI fix breaks something else. That pattern has structure, and it is not about the model.
AI Strategy
Cost becomes a product problem before most teams notice the shift. By the time someone runs the unit economics on an AI feature, the design decisions that drove them are already shipped.
AI Strategy
Every prototype demoed beautifully. Six months later nothing has shipped, and "our AI strategy is basically a list of pilots" stops being a confession and starts being a diagnosis. Here are the eight stages that move a prototype into production.
Quality Harness Engineering
Quality Harness Engineering: The Emerging Stack for Reliable AI Systems
AI Adoption
Eighteen months in, the licenses are paid and the dashboards haven't moved. AI adoption fails as procurement and succeeds as role redesign. Five issues that compound in this exact order.
AI Security
Most AI rollouts ship the tool before the policy. By Q3 the org has the habits the policy was meant to prevent. Ship policy first - in days, not quarters.
AI Adoption
The 4-Level AI Adoption Evaluation Model: How to Tell What Your Delivery Team Has Actually Changed