Leadership teams run prioritisation exercises regularly during a quarter. RICE scores, updated inputs, a fresh workshop each time. The output barely moved: the same three items land near the top, in …
Cognitive Coverage: The Real Job After AI Writes the Code
Satya Nadella admitted something uncomfortable on a podcast in June: he's a token-maxer too. Reaching for the most powerful model available, for tasks that didn't need it, because it's addictive. His …
Continue Reading about Cognitive Coverage: The Real Job After AI Writes the Code →
The Four Archetypes of the AI-Split Workforce
Most AI adoption programmes are built for a population of two: people who are on board, and people who need convincing. Noam Segal and Lenny Rachitsky's annual sentiment survey, now in its second year …
Continue Reading about The Four Archetypes of the AI-Split Workforce →
From Prompting to Loop Engineering
Boris Cherny, who built Claude Code, described the shift plainly, in a piece Gergely Orosz collected the reaction to: "I don't prompt Claude anymore. I have loops running that prompt Claude and …
The Integration Tax of AI Speed
AI has made every individual step of building a product faster: research, requirements, documentation, prototyping. It has not yet made the product faster to build. The gap between those two facts is …
23 Million Horses Lost Their Jobs at the Peak of Demand
Every time someone worries AI will shrink their industry, someone else reaches for Jevons paradox. The argument: when something gets more efficient, people don't use less of it, they use more. Cheaper …
Continue Reading about 23 Million Horses Lost Their Jobs at the Peak of Demand →