Most organisations are asking how AI can improve their existing product. That is a reasonable question and rarely the most useful one. These articles treat AI as a structural change in the economics of knowledge work, and ask what that implies for products, business models, and the cost of judgement.
Two threads run through them. The first is evaluative: AI output is optimised for coherence rather than truth, which shifts effort from drafting to verification and makes the fluency of an answer a poor guide to its accuracy. The second is strategic: when something becomes abundant, value migrates elsewhere — so the interesting question is what stays scarce.
Articles in this guide
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AI and Yes Minister
Sir Humphrey never lied outright either. Why fluent, confident AI output moves the cost from drafting to judgement.
Interactive simulation: The Humphrey Trap — Modelling Fluency Against Accuracy in AI Output →
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Fernand Braudel and Why Product Managers Focus on the Wrong Things
What product managers can learn from Fernand Braudel about events, trends, structures, AI, and long-term product strategy.
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Schumpeter, AI, and the Art of Creative Destruction
Why artificial intelligence is not just coming for jobs, but for business models, value chains, and product assumptions.
Where this gets applied
AI Specification Assistant is a working attempt to use AI where the judgement stays with the product manager.