// Thinking
What we've learned, at close range.
We've watched enterprise AI succeed and fail up close for a decade. What separates them is rarely the technology. Written by the people doing the work — not a content team.
AI Transformation · Featured
What we learned building GenAI for one of the world's top consulting firms.
The hardest part was never the model. It was the moment the partner realised the tool was changing how their analysts thought about their work — and had to decide whether that was a feature or a risk.
Product Strategy
Why most enterprise AI projects fail before the first line of code.
The strategy-execution gap, from inside it — and the three questions that predict whether a project will ship.
Org Design
The embedded model: neither outsourcing nor fully in-house.
Why the future of AI transformation is a third operating model — and how to run it without losing ownership.
AI Transformation
From demo to production: what it actually takes to ship enterprise GenAI.
A field guide to the last mile — data, governance, and the unglamorous work that separates pilots from products.
Enterprise Architecture
What a good AI technical due diligence actually looks like.
The questions investors and boards should be asking — and the red flags that don't show up in a demo.
Emerging Tech
The cost of moving too slowly on AI — and the cost of moving too fast.
Most teams optimise one and ignore the other. A framework for finding the responsible middle.
Product Strategy
Build the tool your best person would build for themselves.
The single design heuristic that keeps internal AI products from becoming shelfware.
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