Return on token spend

Return on token spend is Weave's measure of what AI spend buys: units of engineering output produced per dollar of AI tool spend, per month.

Unlike the cost and output series above, this one is computed only over engineers who have both attributed AI spend and merged code output in the same month. An engineer who shows no spend is usually one whose organization has not connected billing telemetry, and an engineer who shows no output may work in repositories Weave does not see. Requiring both signals means the ratio only counts people for whom the dollars in and the work out are both observed, rather than treating unreported telemetry as zero. The cohort was 2,799 engineers in January 2026 and 7,020 in August 2026.

For that cohort, total output is divided by total AI spend. Output is Weave's standard unit for engineering work, the time an expert engineer would need to complete each merged pull request, with ignored PRs excluded. Spend comes from tool billing and usage telemetry, normalized into dollars; spend that cannot be attributed to a person, such as organization-level overage charges, is excluded. The series begins in January 2026, when attributed spend telemetry became broad enough to average.

Sample and interpretation

The matched cohort included 2,799 engineers in January 2026 and 7,020 in August 2026. Monthly counts between those dates are not included in the public snapshot.

These are aggregate observations from Weave customer telemetry, not a controlled experiment or a representative sample of every engineering team. Changes in the observed cohort and connected telemetry can affect the series. The data alone does not establish that AI caused a change in output.

Estimated expert hours are a modeled measure of engineering output, not recorded working hours, hours saved, or a direct measure of business revenue.

For the wider measurement framework, read how to calculate AI coding ROI, including cost attribution, quality, and baseline comparisons.