Which working habits will your teams keep, and which will you need to unlearn as language models get more capable? Early LLMs helped developers with trivial autocomplete. Then they began to write …
2026 is the Year AI Becomes an Operating Model
The honeymoon phase of the AI revolution is officially over. Boards and leadership teams are no longer satisfied with flashy proofs-of-concept or agents that "experiment" in safe, isolated …
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The Invisible Web: Why Distinctiveness is the Only Antidote to the AI Squeeze
For more than twenty-five years, I’ve watched technology cycles move from the "magic" phase to the "utility" phase, and finally, to what Cory Doctorow famously termed "enshittification." We saw it …
From Pilot to Product: How Product Leaders Turn AI Experiments into Durable Services
Too many AI pilots end up as well-intentioned slides or dusty prototypes. The technology gets praised, the metrics glow in a lab environment, and then the organisation asks the familiar question: why …
How to Run Fast, Safe AI Experiments — A Playbook for Product Leaders
Many product teams rush to build with AI because it is available, not because they understand what problem it actually solves. The result is neat demos, noisy Slack channels, and — sometimes — …
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How to Build Responsible, Scalable AI Tutors: A Practical Playbook for Product Leaders
Can AI tutors scale across millions of learners without eroding trust or quality? That’s the question keeping product leaders awake. AI in education promises personalised learning at unprecedented …