AI usage patterns in software teams
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- AI adoption at Linear more than doubled in every function between January and June 2026, with product roles climbing fastest from 12% to 34% and go-to-market from 5% to 18%.
- CEOs at companies of 201 or more employees posted the largest adoption jump of any group, rising from 9% to 36% in six months.
- AI-authored issues in Linear grew from fewer than 1 in 1,000 two years ago to just under half of all issues created today, on pace to soon outnumber human- and integration-authored issues combined.
- Pull requests opened per workspace are up 111% on a June 2024 baseline; coding-agent teams roughly tripled weekly PRs from 21 to 65, while non-agent teams moved only from 8 to 10.
- Non-engineers are shipping more code directly: product managers attaching pull requests rose from 3% to 10% and designers from 1% to 8% over two years.
- Planning time on customer requests, docs, and projects held steady inside Linear — the report concludes AI has changed how teams execute far more than how they decide what to build.
- Total time spent on product development rose rather than fell, as AI conversations and agent sessions added a new layer on top of existing work rather than replacing it — what Linear calls a Jevons paradox beyond token consumption.
Why it matters: For software team leaders, the uncomfortable finding is that 111% more pull requests and doubled adoption have not translated into fewer hours — coordinating and reviewing work is expanding alongside output. Coding agents account for nearly all of the acceleration, meaning the productivity story is now an agent-integration story rather than a seat-count story.
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