AI is making your team faster. Investment Profile shows whether that speed delivers roadmap commitments or gets absorbed by bugs, unplanned work, and unapproved scope, sprint by sprint.

Every sprint hides a ratio. Roadmap stories, bugs, and ad-hoc tasks fight for the same capacity. Investment Profile breaks it down by issue type so you see what's consuming the team, not just ticket count.

An Epic that gets two sprints of focus then quietly drops off never shows up in velocity reports. Investment Profile tracks story points by Epic, sprint by sprint, before commitments slip.

Map Jira labels to product areas once. Investment Profile shows the split across Platform, Payments, Internal Tools, updated every sprint. Every leadership review has a real answer to "where did engineering invest this quarter?"

Say-Do Ratio tracks delivery on sprint-start commitments. Delivery Rate tracks total work completed, planned and unplanned. When Delivery Rate is high but Say-Do is low, the team is shipping. Just not the roadmap.

Which issue types (stories, bugs, tasks) consume sprint capacity. See the ratio per sprint, drill to individual Jira tickets.
Story points by Epic, sprint by sprint. See which Epics get consistent investment and which get crowded out by ops work.
Engineering effort split across product lines via Jira labels. See whether investment matches business priorities and which products are under-resourced.
Say-Do Ratio and Delivery Rate per sprint. Together they reveal whether sprints break in planning or execution.
Hivel measures AI-generated code that survives review and reaches production. LinearB relies on surveys and surface signals, which are outdated and cannot confirm how much AI code actually ships.
Hivel measures AI-generated code that survives review and reaches production. LinearB relies on surveys and surface signals, which are outdated and cannot confirm how much AI code actually ships.
Hivel measures AI-generated code that survives review and reaches production. LinearB relies on surveys and surface signals, which are outdated and cannot confirm how much AI code actually ships.


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