🔍 Read the full analysis: Mapping Jobs To The Field, Factory, And Office on ThorstenMeyerAI.com
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TL;DR
ThorstenMeyerAI.com has launched “Work After Work,” a 60-episode series about economic change and work. Its opening installment uses the three-sector model—primary, secondary and tertiary—to describe the long shift from farming toward manufacturing and services, while presenting automation as a future thesis, not an established fourth sector.
ThorstenMeyerAI.com published the first installment of “Work After Work,” a planned 60-episode series on how economies and jobs change, opening with the three-sector model that groups work into activities tied to natural resources, production and services. The article uses historical employment estimates to chart the decline in farming’s share of work and says its proposed future “automation sector” is a thesis to be tested, not a confirmed development.
The opening episode maps the economy into the primary sector, which takes resources from nature; the secondary sector, which makes goods and includes construction and energy; and the tertiary sector, which covers services such as trade, transport, health, education and government. The source uses the shorthand “field, factory and office,” while acknowledging that the categories can be blunt: a software engineer at a car company, for example, may be classified differently across statistical systems.
The article reports that US farming accounted for 73.7% of the labor force in 1800 in estimates by economic historian Stanley Lebergott, compared with a modelled International Labour Organization estimate of 1.5% in 2025. Those figures come from different sources and periods, so they describe a long-term change rather than a single consistent statistical series. The article also says services have employed more people worldwide than farming since 2001, based on ILO modelled estimates.
For the planned series, the publisher says later episodes will examine how work has moved and which tasks may remain human as machines take on more activity. The first installment points to a possible automation sector that could perform up to 90% of work within a decade or several decades. It labels that forecast the author’s own thesis and says episode 48 will examine it; the material provided does not establish that outcome as fact.
Why the Three-Sector Map Matters
The model gives readers a simple way to track structural economic change: workers may move from extracting resources to making goods and then toward services as productivity and demand change. That perspective matters to current debates about automation because job losses in one activity do not, by themselves, show what happens to employment across the whole economy. The article frames the series around that question, rather than treating a machine’s ability to perform a task as proof that all affected workers will find new jobs.
The distinction between historical evidence and forecasts is especially relevant. The decline in agriculture’s employment share is supported in the article by historical and modelled estimates. By contrast, the claim that automation may become a distinct sector performing as much as 90% of work is a speculative thesis. The series’ stated aim is to test that idea over time; readers should not interpret it as a settled economic prediction.
The sector categories also shape how national economies are described. A large services share does not mean a country has stopped producing goods, and the way industries are classified can affect comparisons. The article says US factory employment is about 35% below its June 1979 peak, while real manufacturing output in 2025 was about 1.9 times its 1979 level. Those figures, as presented by the source, illustrate why employment and output are not interchangeable measures.
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How Economists Built the Map
The three-sector framework developed over several decades. ThorstenMeyerAI.com attributes the term “tertiary” to New Zealand economist Allan G. B. Fisher, who wrote about it in a book drafted in 1934 and published in 1935. The article says the terms “primary” and “secondary” were already used in Australia and New Zealand to distinguish resource-based industries from manufacturing.
Colin Clark brought employment comparisons across countries into the discussion in The Conditions of Economic Progress, published in 1940. He described workers moving from agriculture to manufacturing and then to commerce and services as an important companion to economic progress, while observing that industry’s share of employment can rise and later fall. French economist Jean Fourastié argued in 1949 that services could absorb workers displaced as technology raised productivity elsewhere. The current article presents that argument as part of the model’s history, not as proof that every displaced worker will find equivalent work.
The US figures cited from Lebergott concern the labor force aged 10 and older and use historical estimates published in a 1975 US Census Bureau volume. The 2025 figure for farming is an ILO modelled estimate. Different methods and time spans mean the figures are useful for showing broad direction, but should not be treated as a single uninterrupted series without qualification.
Limits of the Employment Comparisons
The source material gives headline historical figures but does not provide the full underlying tables or methodological notes for every comparison. The US estimate for 1800 and the ILO modelled estimate for 2025 come from different sources and statistical approaches. The article also supplies no detailed series behind its statement that services overtook farming worldwide in 2001, so the exact measure and classification choices are not available here.
It is also unclear how the proposed “automation sector” would be defined or measured, what counts as work performed without a human hand, and what evidence would support the suggested up-to-90% figure. The source labels the idea as a thesis and points to a future episode, rather than reporting a measured present-day share. Its manufacturing comparison is similarly presented without the underlying dataset or a discussion of how output and factory-job categories are defined.
Episodes Will Test the Automation Thesis
ThorstenMeyerAI.com says “Work After Work” will run for 60 episodes, with the opening installment establishing the sector framework for later discussions of technology and employment. The article specifically identifies episode 48 as the point when the author’s automation-sector thesis will be examined. No publication schedule beyond the series being described as daily is included in the supplied material, and no further episode dates or guest contributors are specified.
As the series proceeds, the key question will be whether its later reporting distinguishes clearly between tasks that machines can perform, jobs that may change, and the broader employment shifts measured across sectors. Until the proposed thesis is tested with definitions and evidence, the source’s historical figures support a description of past changes in work—not a definitive forecast of the scale or timing of automation’s future effects.
Key Questions
What is the three-sector model?
It groups economic activity into primary work that draws on natural resources, secondary work that makes goods, and tertiary work that provides services. The article uses “field, factory and office” as a shorthand.
What did ThorstenMeyerAI.com announce?
It published the first episode of “Work After Work,” a planned 60-episode series about how economies are built, how jobs move between sectors and how technology may affect work.
Does the article prove automation will replace 90% of work?
No. The source identifies the figure as the author’s thesis about a possible future automation sector, not a confirmed measurement or established forecast. It says episode 48 will examine the claim.
Why do the farming figures use different sources?
The 1800 figure is attributed to historical estimates by Stanley Lebergott, while the 2025 figure is an ILO modelled estimate. They indicate a broad decline in farming’s share of employment, but are not presented as one consistent series using the same method.
Source: ThorstenMeyerAI.com
