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TL;DR
ThorstenMeyerAI.com launched “Work After Work,” a 60-episode series, with an opening installment explaining the primary, secondary and tertiary sectors. Its figures trace employment’s shift from farming toward services, while the author labels a possible future automation sector as a thesis, not a fact.
ThorstenMeyerAI.com published the first episode of “Work After Work,” a planned 60-episode series about how economies are built and how work changes as technology advances. The installment explains the three-sector model—primary work drawing on natural resources, secondary work making goods, and tertiary work providing services—and uses historical employment figures to show how workers have moved among those categories.
The article describes the sectors as a practical, if imperfect, way to group jobs. Farming, fishing and forestry are primary activities; mining is often included, although statistical systems do not classify it consistently. Manufacturing, construction and energy fall under the secondary sector. Trade, transport, education, health care, government and office work are among the broad range of services placed in the tertiary sector.
The article attributes the modern three-part framework to economists including Allan G. B. Fisher, who used “tertiary” in work written in 1934 and published in 1935, and Colin Clark, who compared employment patterns across countries in a 1940 book. It also discusses Jean Fourastié’s 1949 argument that services could employ people displaced from more productive industries as machines reduced the labor needed to make goods.
Figures cited in the episode show a long decline in farming’s share of US employment: historian Stanley Lebergott’s estimates put it at 73.7% in 1800, 40.2% in 1900 and 12.0% in 1950. An International Labour Organization modelled estimate puts the US share at 1.5% in 2025. The article also reports that, in the ILO’s modelled estimates, services have employed more people worldwide than farming since 2001.
What the Sector Shift Shows
The model offers readers a straightforward way to understand a major economic change: workers have not simply vanished as farming and manufacturing have required a smaller share of the workforce. Employment has shifted toward other activities, particularly services. The article’s figures make that change visible across long periods and different countries.
The distinction matters when discussions of automation focus on jobs lost in a particular industry. A decline in one sector’s share does not, by itself, show whether total employment fell or where workers went. The series presents that movement as a central question for later episodes, including those on machinery and artificial intelligence. Its opening installment supplies a framework, not a prediction that any specific technology will produce a particular employment outcome.
The article also challenges the claim that the United States no longer makes goods. It 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 measures describe different things: fewer factory jobs can coexist with higher output. The figures are attributed to the source article and do not establish why the changes occurred.
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How Economists Drew Three Boxes
The sector framework developed through economic writing and statistical work in the early and mid-20th century. The source says that “primary” and “secondary” were already used in Australia and New Zealand for activities such as farming, mining and manufacturing. Fisher added the term “tertiary,” and Clark later compared sector employment across countries. Their classifications were not perfectly uniform: mining, for example, is grouped with primary activity in many systems but with secondary activity in Clark’s classification and Japan’s census.
Fourastié gave the framework a theory about technology and employment. He argued that productivity gains could reduce labor needs in some industries while services absorbed workers. A 1949 review of his book described one conclusion as a rejection of fears of lasting technological unemployment. That is a historical argument, not a guarantee about what will happen in current labor markets. The series says future episodes will examine whether that expectation holds as machines take on more tasks.
The opening episode also compares national changes: it reports that China’s primary-sector employment share fell from 83.5% in 1952 to 22.2% in 2024, and that Japan’s fell from 53.8% in 1920 to 3.2% in 2020. These figures are presented as employment shares, not counts of workers, and the source identifies the underlying figures as coming from different statistical series.
““My thesis, not a fact: within a decade or a few decades, automation could become a sector of its own, doing up to 90% of the work with no human hand.””
— Thorsten Meyer, author of the series
Where the Model Has Limits
The three-sector model is a broad classification, and the source acknowledges that the same job can be counted differently across statistical systems. A software engineer working for a car manufacturer, for instance, might be classified as manufacturing or services depending on the method used. Mining is another point of disagreement. These differences limit direct comparisons unless definitions and methods are checked.
The article’s employment figures also come from sources covering different periods and using different methods, including historical estimates, censuses and ILO modelled estimates. The source does not provide enough detail in the supplied material to independently assess every series or reconcile their definitions. Its long-run figures should be read with their stated dates and attribution rather than treated as one uniform dataset.
Most importantly, the possible emergence of automation as a separate sector—and the claim that it might perform up to 90% of work—remains Meyer’s stated thesis. The episode offers no evidence establishing that outcome, its timeframe or how “work” would be measured. Whether services will continue absorbing workers displaced by technology is also an open question, not a settled forecast.
The Series Turns to Automation
“Work After Work” is described as a daily series of 60 episodes about economic structure, changing employment and work that may remain human as machines take on more tasks. The first installment uses the three-sector model as a foundation for those questions. The source says episode 48 will put Meyer’s proposed automation-sector thesis “on trial”; it does not give a publication date for that episode in the supplied material.
Further installments are expected to examine the movement of workers between sectors and the effects of technologies such as tractors and chatbots. The series’ future arguments and evidence have not yet been presented in this opening episode. Readers should distinguish those planned discussions from the historical statistics and economic theories already described.
Key Questions
What are the three economic sectors?
The primary sector takes resources from nature, the secondary sector makes goods, and the tertiary sector provides services. Statistical definitions can vary, particularly for mining and jobs that combine manufacturing with office or technical work.
What is “Work After Work”?
ThorstenMeyerAI.com describes it as a daily, 60-episode series on how economies are built, how work has shifted and which tasks may remain human as machines take on more work. The first episode was published November 2, 2026.
When did services overtake farming worldwide?
According to the source article’s account of ILO modelled estimates, services have employed more people worldwide than farming since 2001. The article does not provide the underlying global employment totals in the supplied material.
Does the article establish that automation will become a separate sector?
No. Meyer calls that possibility his thesis, not a fact, and says a later episode will examine it. The opening installment does not establish that automation will perform up to 90% of work or specify how that claim would be measured.
Source: ThorstenMeyerAI.com
