Notes from the field, not the podium

Most writing about data and AI describes how things should work. This is where I write about how they actually do: the decisions made under production pressure, the gap between what vendors promise and what deployments look like, and the things organisations tend to share only once trust is established.

Why Arkham

The name comes from Lovecraft's New England. In those stories, Arkham is where familiar certainties stop holding and something older and more demanding takes their place. That felt accurate for what is happening in technology right now.

Data architectures considered solid three years ago are being replaced. Agentic AI, software that does not just execute instructions but plans and acts, is compressing timelines that once spanned quarters into weeks. Organisations are governing platforms whose capabilities outpaced the policies written to contain them before those policies were finished. The map runs out.

What This Publication Is

Arkham Times is not a product blog or vendor newsletter. It is field notes from active advisory practice: observations from real client work, architectural decisions made under pressure, and honest accounts of deploying AI at enterprise scale.

The topics are data platform architecture, AI strategy and agentic systems, digital transformation, and the organisational dynamics that determine whether complex work actually lands. The aim is to say something specific, not just something safe.

Arkham Advisory

The advisory practice works with a small number of organisations going through genuine transformation, not just adopting technology but changing how they make decisions around it. The work covers data infrastructure and platform architecture, AI strategy and agentic system development, technology due diligence, and senior counsel on transformation programmes.

No large delivery teams. No recycled frameworks. The advice is direct because the problems usually are.

If the work resonates, the conversation is worth having.