Linear published usage data on AI adoption from inside its own product, covering January to June 2026. The share of users active on AI features more than doubled in every function: product climbed fastest from 12% to 34%, and go-to-market, the function furthest from the codebase, went from 5% to 18%. Adoption roughly tripled across company sizes, from startups to enterprises, with company size barely registering as a predictor — unusual for new technology.
The most striking cut is seniority. CEOs at companies of 201 or more people went from 9% to 36% in six months, the largest jump in the report, which Linear reads as senior leaders learning the technology by using it rather than reading about it. That inverts the usual adoption curve, where executives sponsor a tool and practitioners use it.
Measuring where the work actually sits, rather than counting tokens, is the same instinct as tracking where judgment becomes the scarce resource in agent workflows and what happened when a three-person team shipping hundreds of pull requests moved the bottleneck into review. The coding agents hub tracks the workflow side of adoption.
Linear is unusually clear about its own limits: this is adoption inside its customer base rather than the market, AI usage outside Linear is invisible to it, roles come from normalised job titles with error at the edges, and the company-size cut relies on third-party enrichment covering fewer workspaces. The condition to watch is whether the next edition reports shipped outcomes alongside activation, because a doubling in users active on AI features is a usage number, not a throughput one.