Since July 2026 I've been publishing one long argument in weekly instalments: why the economy changed its question, why 95% of enterprise AI fails by design, what an LLM and an AI agent actually are, and what the enterprise must become. The posts and articles below are that argument in reading order. Start anywhere; the numbering will catch you.
There is a standard recipe for enterprise AI adoption. Your organisation is probably following it right now. Take an existing process. Find the step where a human does something repetitive. Replace that step with an LLM. Congratulations. You've bolted a Ferrari engine onto a horse cart. The recipe preserves every assumption of the legacy process, from the data model to the human role, and delivers a marginally cheaper version of the same capability. The cart doesn't go fa
This week, a board will approve an eight-figure AI budget. The evidence: a vendor deck and a thirty-minute demo. I've watched companies buy AI twice. In the nineties it was called expert systems. Now it's called AI agents. Both times they bought it the way they once bought ERP: an answer, before the question. I remember how the first wave ended. The customer said: "My team of experts keeps to schedule and makes fewer errors without your system than with it." The proje
Threat of IA is overestimated. AI is not developed to be the primary risk yet. There are other more important and urgent risks and threats at the base of the society.