🔍 Read the full analysis: Field, Factory, Office: See How Jobs Are Grouped on ThorstenMeyerAI.com
Get business pricing on office and shipping supplies
- Business-only prices and quantity discounts
- Tax-exempt purchasing
- Multiple users, one account, clear invoices
TL;DR
ThorstenMeyerAI.com published the first episode of its 60-part Work After Work series on November 2, 2026, explaining how employment is grouped into primary, secondary and tertiary sectors. The episode traces the long-term shift from agriculture toward services and distinguishes employment changes from claims about what automation may do next.
ThorstenMeyerAI.com published the first episode of its planned 60-part series, Work After Work, on November 2, using the familiar field, factory and office categories to explain how employment has shifted over time. The installment says services have employed more people worldwide than farming since 2001, according to the International Labour Organization’s modelled estimates, and sets up a broader series about work and automation.
The episode groups economic activity into three broad sectors: the primary sector, which extracts or grows resources from nature; the secondary sector, which makes goods and builds infrastructure; and the tertiary sector, which provides services. Farming, fishing and forestry are primary activities; manufacturing and construction are secondary; and trade, transport, health care, education and government are among the services counted in the tertiary sector. The article notes that mining is classified differently in some statistical systems.
To illustrate the categories, the episode follows a loaf of bread from wheat farming to milling and baking, then transport and retail. It describes the three-sector map as blunt rather than exact: a software engineer employed by a car manufacturer, for example, may be counted under manufacturing or services depending on the statistical method. The framework is presented as a way to track where people work, not as a perfect description of every job.
The episode cites historical estimates showing a long decline in farming’s share of US employment. In Stanley Lebergott’s series, farming accounted for 73.7% of the US labor force in 1800, 40.2% in 1900 and 12.0% in 1950. The source gives the ILO’s modelled estimate for 2025 as 1.5%. These figures use different historical and statistical sources, and the article identifies the 2025 figure as a modelled estimate rather than a direct count.
The Long Shift Beyond Farming
The sector model matters because it turns a major economic change into a readable question: where do workers go when productivity rises or demand changes in one part of the economy? The episode argues that the shift from farms to factories and then services is central to understanding how economies develop. Its historical figures show that a sharp fall in agriculture’s share of employment has not meant that food production stopped; work and output became organized differently.
The distinction is relevant to current debates over automation. The episode connects past shifts in employment to the possibility that machines will take on more tasks, while making clear that its prediction about a future automation sector is a thesis, not an established outcome. Readers can use the series’ framework to separate observed changes in employment from arguments about what technology may do next.
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. Employment and output measure different things: fewer factory jobs do not, by themselves, show that manufacturing production has disappeared.
Popular right now

Ninja Foodi Air Fryer, 8 Qt DualZone, 6-in-1, Grey, DZ201

Dyson V8 Cyclone Cordless Vacuum

KitchenAid Artisan 5-Quart Tilt-Head Stand Mixer, Almond Cream
As an affiliate, we earn on qualifying purchases.
How Economists Built the Three Sectors
The episode traces the terminology to early 20th-century statistical use of “primary” and “secondary” industry in Australia and New Zealand. New Zealand economist Allan G. B. Fisher added “tertiary” to the framework in a book written in 1934 and published in 1935, according to the source. Colin Clark later compared sectoral employment across countries in The Conditions of Economic Progress, published in 1940, and examined how workers moved from agriculture into manufacturing and services.
French economist Jean Fourastié developed another argument in 1949: because technical progress can raise output quickly in industry but may be harder to apply to some personal services, services could absorb workers no longer needed in other sectors. That was an economic argument, not a guarantee about every worker or period. The series says its later episodes will revisit such claims while examining changes from tractors to chatbots.
The opening episode also gives examples beyond the United States. It reports that China’s primary-sector share of employment fell from 83.5% in 1952 to 22.2% in 2024, and that Japan’s census recorded a fall from 53.8% in 1920 to 3.2% in 2020. These country figures come from different time spans and statistical sources, so they should not be treated as a single standardized comparison.
“a vast miscellaneous residue of activity”
— Allan G. B. Fisher, as quoted in the episode
Limits of the Sector Forecast
The episode’s historical figures combine estimates and censuses made with different definitions and methods. The source itself notes that jobs such as software engineering at a car company may be classified differently, and that mining does not fall into the same sector in every system. The figures therefore show broad patterns, but they do not resolve every comparison between countries or time periods.
The installment forecasts that automation could become a separate sector within a decade or a few decades and might do up to 90% of work without a human hand. That is Meyer’s stated thesis, not an observed fact or a cited consensus forecast. The episode does not establish which jobs, industries or workers would be affected, how quickly such a change might occur, or how “90% of the work” is defined. It also does not provide enough detail in the supplied material to independently assess the methods behind each employment estimate.
The Series’ Automation Test
Work After Work is described by ThorstenMeyerAI.com as a daily series of 60 episodes about how the economy is built, how work has moved, and which work may remain human as machines take on more tasks. The first installment establishes the sector framework and historical shifts that later episodes are expected to examine.
The source says Episode 48 will put Meyer’s automation thesis on trial. It does not give a publication date for that episode or spell out how the forecast will be evaluated. Until then, the series’ historical examples can be distinguished from its forward-looking claims: the employment shifts are presented as estimates and records, while the forecast about automation remains the author’s argument.
Key Questions
What are the three sectors used to group jobs?
The primary sector takes resources from nature, the secondary sector makes goods and builds infrastructure, and the tertiary sector provides services.
What does the episode say about global employment since 2001?
It says that, according to ILO modelled estimates, services have employed more people worldwide than farming since 2001. The statement concerns employment, not the value or volume of production.
Does the episode say the United States no longer manufactures goods?
No. 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. The employment and output figures describe different measures.
Is the prediction about automation a confirmed forecast?
No. Thorsten Meyer labels the idea that automation could become a sector of its own, doing up to 90% of work without a human hand, as his thesis. The episode does not establish that outcome as fact.
Source: ThorstenMeyerAI.com
