Part 4 of 4 of The Narrow Part Is Moving. Each part has its own short video.
The doom maths has Malthus’s shape
There are darker scenarios, too. AI becomes something only a few can afford. Jobs vanish faster than new ones appear. People despair.
In 1798 Thomas Malthus did the arithmetic: population grows geometrically, food arithmetically, therefore catastrophe. It was a clean chart. It was wrong on the total, because the supply line didn’t stay straight. The fixed denominator was the error, and almost every doom chart since has had the same shape.
But I want to be fair to the doom, because the honest version of it is stronger than the dramatic one. Malthus was wrong about the aggregate and right about plenty of people. Famines happened. Jevons tells you that total demand grows; it says nothing about who gets the new work, or how long the gap lasts. The handloom weavers did not become the factory managers. And access to the most capable models is, today, a dependency most of us don’t control: I’ve watched a vendor swap a model underneath a working system and quietly break its guardrails.
So the total isn’t the risk. The speed and the distribution are. That deserves attention, budgets and policy, not dismissal. It doesn’t change the direction of travel.
Where to?
Red Queen and Jevons will keep us moving. Where to, and what other discoveries, opportunities, or even dangers are in front of us? Time will tell.
And maybe AI could too, so I asked it. Before writing this, I ran the storyline through my Writing Lab: a panel of AI-simulated personas, each built on one real thinker’s published work, set up to argue the piece apart. None of them are real people speaking. They are AI-generated perspectives, and the people who inspired them are credited below.
Three things they argued that I hadn’t seen on my own:
- Ezra (constraints theorist, based on Eliyahu Goldratt’s thinking): the biggest risk isn’t the new constraint, it’s inertia. Most of our planning machinery still optimises the old one.
- Vera (AI sceptic, based on Gary Marcus’s thinking): the productivity numbers are soft, so don’t lean on any of them. The argument about the moving constraint works with any speed-up greater than zero.
- Wren (strategic mapper, based on Simon Wardley’s thinking): model access belongs on the map as a dependency you don’t own, not in a disclaimer at the bottom.
Where I disagree with them is the ending. Vera wanted me to cut “maybe AI could too” as a shrug. I think it’s the point. The narrow part is moving to judgment, and judgment gets better when it’s argued with.
So, a question for you: in your organisation, where is the narrow part going? And is anyone standing there yet?
Sources and credits
- Addy Osmani, Shubham Saboo, Sokratis Kartakis, The New SDLC With Vibe Coding: From ad-hoc prompting to Agentic Engineering, Google, May 2026 (p.19, p.22, and Figure 5, p.20). Animation A uses Figure 5’s phases and durations.
- Eliyahu M. Goldratt, The Goal (1984), Theory of Constraints.
- William Stanley Jevons, The Coal Question (1865).
- Thomas Robert Malthus, An Essay on the Principle of Population (1798).
- Leigh Van Valen, “A New Evolutionary Law”, Evolutionary Theory (1973); Lewis Carroll, Through the Looking-Glass (1871).
The Writing Lab panel for this piece was simulated with AI (Claude). Each persona is built on one thinker’s published work; none of them said any of this, so please read the originals:
- Wren (strategic mapper, based on Simon Wardley’s thinking)
- Ezra (constraints theorist, based on Eliyahu M. Goldratt’s thinking)
- Tomas (economic historian, based on William Stanley Jevons’s thinking)
- Lena (evolutionary biologist, based on Leigh Van Valen’s thinking)
- Vera (AI sceptic, based on Gary Marcus’s thinking)
- Iris (editor, based on Ann Handley’s thinking)
- Owen (conversion designer, based on Oli Gardner’s thinking)
- Kaja (brand storyteller, based on Paweł Tkaczyk’s thinking)
How the Writing Lab works: the method, and why the personas carry names and credits: The Voices in the Room.