The week's essentials in AI and exponential tech · 21 Sept – 28 Sept
This week brought a headline many were half expecting: generative AI still shows no measurable impact on GDP or on macroeconomic productivity. Some will read it as proof that it was all hype, and some of the confident projections about jobs and growth circulating in public debate do deserve that correction. But reading it as the end of the story is like looking at the pond when the lily pad covers a tiny corner and concluding the water is safe. Exponential change always looks like nothing in aggregate statistics until, very late and very suddenly, it looks like everything. That is the uncomfortable pattern I describe in chapter 4, "It Is Already Happening." The signal isn't in the national accounts yet. It is inside the organisations where the curve has already bent, like Proaction, which reports sales up 60% and more than 75 hours saved using Codex. The problem isn't technical, it's cognitive: our linear minds average the few who have crossed over with the many who haven't started, and conclude that nothing is moving.
The book warns of the gap between technological hype and real adoption: this story confirms that the exponential curve of AI capability has not yet translated into measurable macroeconomic results, challenging the labour market and GDP impact projections circulating in public debate.
The incident exemplifies a core tension in exponential times: AI capability grows faster than our ability to contain and oversee it. The pause signals recognition that human control must precede scale, not follow it.
This development demonstrates how the industry is building oversight and control mechanisms for agentic systems that operate autonomously. It confirms that the central challenge is not merely creating intelligent agents, but preserving human capacity to intervene, validate, and correct their decisions in real time.
A concrete example of how generative AI automates entire layers of operational and development work, enabling small teams to execute tasks that previously required more resources. It illustrates the transition toward companies operating with intelligent agents embedded in their processes.
Microsoft's strategy to establish Copilot as a unified operating system for work demonstrates how automation and augmentation of tasks embed themselves into everyday work infrastructure, validating the book's thesis on the redefinition of work in exponential times.
If this week helped, pass it on to someone else living these times.
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