Writing
Essays.
Long-form arguments about AI and digital transformation inside real companies. Most of what I publish is downstream of live work at the LEGO Group and conversations with Nordic and global enterprise leaders.
- № 01 Now everyone's doing ontology. Almost nobody's doing the hard part.
The biggest data platforms are racing to put an ontology under their agents. The word has gone mainstream — but the work that makes it real hasn't. A field guide to the two layers, the semantic layer that enforces them, and why Phase 2 decides how far your agents travel.
- № 02 GEO isn't SEO: what 30 ChatGPT runs revealed about brand visibility
A controlled experiment — 30 cold ChatGPT sessions, Danish IPs, one prompt — and what it taught me about optimizing for AI search. Spoiler: the SEO winners and the ChatGPT winners are two different lists.
- № 03 What a good AI advisor in Denmark actually does
A working definition of the role, written for Nordic enterprise leaders trying to tell signal from noise in the AI advisory market.
- № 04 Past pilot purgatory: why Nordic AI stalls
The pattern that traps most Nordic enterprises in their first wave of AI pilots — and the operating-model changes that distinguish the companies that escape it.
- № 05 The EU AI Act, read as architecture
A working engineer's view of the EU AI Act — not as a compliance burden, but as a set of architectural constraints that, taken seriously, produce better AI products.
- № 06 What a foundational platform for AI actually contains
An opinionated list of the capabilities a Nordic enterprise platform team needs to own to make AI work shippable — and the ones it should rent.
- № 07 NPS-driven engineering: products people love
An engineering leader's account of organising a 100+ enterprise technology organisation around customer love as a primary KPI — what worked, what almost worked, and what it has to do with AI.
- № 08 AI isn't taking jobs — it's inventing them faster
Chief AI Officer, AI Auditor, LLMOps Engineer, Prompt Engineer at $300K. None of these had job descriptions in 2022. The pattern isn't replacement — it's the Jevons Paradox playing out in real time.
- № 09 Every organisation needs a second brain
Building a personal second brain over 728 desktop files surfaced a bigger pattern: most corporate knowledge is locked in formats AI can't reason over. The next platform shift is AI-native knowledge that compounds.
- № 10 Agentic AI governance: platform, not policy
Lock agents down too tight and teams stop experimenting. Let them run too loose and you get the horror stories. The middle path: treat agent configuration like infrastructure, not policy.
- № 11 Beijing is already living with embodied AI
A delivery bot in the hotel, a humanoid making lattes, tenth graders prompt-engineering robots. The gap between talking about AI in the physical world and living with it is wider than I thought.
