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Anthropic report: AI work hours are already 6 times those of humans, junior programmer positions have plummeted, and revenue per employee is…

IT Home, news of 10/17: AI company Anthropic released a report yesterday (10/16) stating that, roughly 5 years after the company's founding, its revenue per employee has reached 2 to 4 times that of Meta Platforms and…

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Thanks to IT之家 netizen South China Wu Yanzu for the tip!

IT之家 October 17 news: artificial intelligence company Anthropic released a report yesterday (October 16) stating that, about 5 years after the company's founding,its revenue per employee has reached 2 to 4 times that of Meta Platforms and Google during their respective high-growth periods.

This data is based on Anthropic's internal financial and headcount records as of 4/2026, and was compared, after inflation adjustment, with public financial data from Meta and Google at the five-year mark after their founding.

The report shows that the share of junior employees in Anthropic's technical departments has fallen from 21% in early 2025 to 14%, and the share of junior technical position hiring has plunged even more sharply from 27% to 9%. About one third of machine learning managers and one fifth of software engineering managers said they reduced hiring because of the emergence of AI. Meanwhile, the company as a whole is still expanding, with positions in sales, finance, and recruiting growing faster.

Agent work hours exceed human work hours. Note: We consider only employee-led interactive sessions and the sub-agent pool. Work hours refers to agent runtime, including reasoning and tool use, but excludes waits exceeding 30 minutes. Human work hours are calculated by headcount, assuming 40 hours per week.

AI brings not only job contraction but also a leap in efficiency. After adopting coding agents, engineers' code commits per person reached 5 times the level of 6 months earlier; lawyers process more contracts, finance processes more invoices, and salespeople close more deals. The report tracked 192 engineers who adopted coding agents and found that their code output rose markedly after adoption, and the proportion of code later deleted or rolled back showed no deterioration.

The report states that by 8/2026, the working hours of interactive AI agents deployed by employees had reached 6 times those of human employees; as early as in month 3, total agent working hours across the company exceeded human working hours for the first time. IT Home attaches the relevant images below:

Productivity surges across functional departments. Note: A Loess smoothing method was used to fit the underlying indexed output data.

But "human-machine collaboration" also brings new burdens. The report says that even non-technical employees may spend up to half a work week reading the full output of their Claude agents; employees are shifting from "executors" to "agent managers," responsible for writing instructions, building monitoring dashboards, and reviewing AI output. In spring 2026, this kind of "meta-work" already accounted for 22% of employees' interactive Claude sessions, up from 10% the previous year.

Estimates of productivity gains based on individuals' gradual AI adoption. Note: Coefficients compare users who adopted coding agents with non-adopters, controlling for two-way fixed effects of users and calendar months. Treatment time is based on the month in which a user first completed at least 5 agent sessions. Bars represent 95% confidence intervals based on standard errors clustered by user. The quality panel compares code written directly by users with code written by the same user using coding agents. Quality metrics include: the share of lines of code deleted within 90 days for any reason; the share of lines of code deleted specifically for bug fixes; whether an entire commit was explicitly rolled back; whether linter suppression comments were added; whether comments requiring fixes were added; and whether tests were marked as skipped, retried, or allowed to fail.

Hiring standards have changed accordingly: managers value candidates' autonomy, judgment, and creative use of AI more than narrow domain expertise and specific execution skills. Anthropic has also established a job risk early-warning mechanism and prioritizes reassigning affected employees internally.

Growth in junior employment by complexity of Claude usage. Note: the chart uses jobs as the unit. Growth rates compare employment in 1/2026 and 7/2026. AI complexity is based on automated coding of agent logs (10 to 12/2025, before the decline in employment), converted to percentiles. The points in the chart are scaled by each job's employment in 1/2026; the regression line is fitted to the weighted points.

However, revenue per employee is not the only measure of a company's health. External research firm Epoch AI previously estimated that Anthropic's annualized revenue per employee in April 2026 was about $9 million, clearly higher than Meta's roughly $2.55 million and Google's roughly $2.11 million; but the firm also cautioned that the headcount and revenue figures were not disclosed for the same period, so the estimates carry uncertainty.

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