On October 16, 2026, four economists from Anthropic's Economics team publish a report on the transformation of work within the company. They treat it as a leading indicator, because the company has rebuilt its workflows around AI. The report draws on internal data (headcount, agent telemetry, output, surveys, calendars, Slack, interview rubrics) and seventeen interviews.
Anthropic is growing fast but hires less per dollar of revenue than Meta or Google did at the same age. Junior technical roles are declining: their share of technical departments drops from 21% to 14% since early 2025, and their share of hires from 27% to 9%. Technical departments carry less weight in headcount, while non-technical staff start coding: their coding-agent sessions rise from 2 to 90 per month. Administrative functions remain lean, and internal mobility increases by half.
Since March 2026, agent hours have exceeded human hours; in August, employees' interactive sessions alone represent six times the human time. Commits per engineer have been multiplied by five in six months, and lawyers, accountants, and sales staff produce more. Comparing 192 engineers who adopt agents to 74 who do not, the authors observe a net increase after adoption, while acknowledging that adoption is not random. Code produced by an agent is neither deleted more nor reverted more often than code hand-written by the same employee.
Human attention becomes the bottleneck. About 80% of agent session time is spent waiting for a response, and reading all of their output would take more than half a week, even for non-technical staff. Employees respond with "meta-work": standing instructions, multi-agent specifications, cross-reviews, dashboards. This share rises from 10% to 22% of sessions. Meeting time increases by 20%, and work must stay visible so agents have context.
In hiring, evaluators mention creative AI use three to four times more often, and value autonomy and judgment more than domain expertise or execution.
The authors identify three levers: employee equity ownership, which shares the gains from adoption; an early-warning system for exposed occupations; and internal redeployment, which pushes toward creating tasks rather than automating at the margin. They acknowledge that none of these protects those who are not hired, and call for public policy on retraining and income support.