Field notes.
Short, sharp notes from 18 years of regulated delivery — and from inside a running AI factory. The politics, the method, the regulatory reality and the AI transition, as they actually look. No thought-leadership fluff.
Looking for the longer, practical pieces on AI governance, the EU AI Act and Danish public-sector adoption? Those live in Insights →
Leading extremely clever children with enormous power
They don’t lack ethics. They have too much of the wrong kind — and it hides in the work they quietly don’t do.
When AI fabricates your control evidence
In a GxP, NIS2 or DORA environment, a hallucination isn’t a wrong answer. It’s an audit finding with a delay on it — and most organisations can’t answer the auditor’s first question.
Why your AI pilot is lying to you
Not maliciously. Structurally. An agent sounds equally confident when it has read the source and when it has invented one — and your pilot can’t tell the difference.
“Done” is the most dangerous word in AI
A green test is not done. A merge is not done. A convincing explanation is nothing at all. Why AI inflates “done” — and the mechanical cure.
One agent, seven hats — why your AI needs an org chart
The biggest AI failure in my factory wasn’t a hallucination. It was an org-design error — mine. Segregation of duties, applied to machines.
Why your SteerCo is lying to you
Not maliciously. Structurally. Amber is a negotiated colour — and you can’t recover a programme that’s officially fine.
The first 7 days of a red programme
Before the plan, before the Gantt. Week one is not about the schedule — it’s about the truth and the map.
NIS2: nobody’s neck is on the line — and that’s the problem
Denmark left personal management liability out of its transposition. Everyone read that as relief. It’s actually why the controls stay on paper.
A note, now and then. Nothing else.
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