The latest developments, explained simply.
The past few months I have been rethinking how self-reflection should actually work in an app. Not more features. More meaning.
Read briefing →The repetitive work that used to take days is being done in minutes. Faster, often better. But that isn’t the most interesting part yet. The point is what it leaves to us. The work that can’t be described in a prompt.
Read briefing →Most organisations have run an AI pilot by now. The technology works, the business case is clear, yet the gap between a successful experiment and an organisational capability remains stubbornly wide. The missing element is not technical. It is trust.
Read briefing →Every wellness app I tried felt like it was designed to keep me using it rather than help me feel better. One is my attempt to build something different.
Read briefing →Every conversation with an AI begins in the same place: nowhere. Memory — the ability to accumulate context over time — is the single largest gap between current AI and the kind of intelligence we intuitively expect.
Read briefing →We have arrived at the point many predicted but few prepared for: when AI-generated output is good enough that the question of origin becomes genuinely difficult to answer. This raises questions that reach far beyond technology.
Read briefing →The qualities that defined strong leadership five years ago — decisiveness, delegation, pattern recognition — still matter. But they are no longer sufficient.
Read briefing →While the “same with less” view dominates fears of job displacement, emerging evidence suggests that augmentation (“more with the same”) is the dominant reality.
Read briefing →Measuring AI’s true value means tracking its impact on people and organisational health, not just output numbers.
Read briefing →Effective autonomy is built, not switched on. How to secure immediate wins today that pave the way for the complex agents of tomorrow.
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