Quality assurance · Production

Rabbit Care cuts engineering cycle time by 50% and scales team 10x with LinearB

The problem

Rabbit Care needed to dramatically scale its remote engineering team in a single year while maintaining consistency and transparency, but lacked visibility into delivery timelines, suffered from inconsistent velocity, and was beset by slow code reviews and incorrect reviewer assignments.

Workflow diagram · grounded in source

Monitor DORA metrics and indicators

integration

“Jeremy's team began actively monitoring DORA metrics, as well as their leading indicators (specifically: PR Size and Review Time)”

Retrospective root cause analysis

human_review

“Jeremy and his team conducted a quick analysis of their data from the past few iterations and identified the root cause: slow code reviews. They dug into PRs that had been open for longer than expected and flagged incorrect reviewer assi…”

Auto-assign PRs to Code Experts

routing

“a gitStream rule that takes into account which developers have the most commit activity and knowledge on the files in question, then assigns them to review that PR automatically”

Auto-approve documentation-only PRs

validation

“if a developer decides to modify an internal document (and nothing else), they can go ahead and merge the PR without having to wait for a rubber stamp approval”

Teams self-monitor via dashboards

output

“Jeremy makes sure that his team has access to a trackable dashboard and is able to self-monitor their performance”

Reported outcome

With LinearB, Rabbit Care cut its ideal-to-production cycle time by 50%, is shipping code at twice the speed, can confidently predict project delivery timelines, and has seen a noticeable improvement in developer happiness and cross-departmental communication.

Reported metrics

Code shipping speedtwice the speed

Developer happinessnoticeable improvement

Culture improvementbiggest win

Reported stack

LinearBgitStreamCode Experts

Source

https://linearb.io/case-studies/rabbit-care

Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

With LinearB, Rabbit Care cut its ideal-to-production cycle time by 50%, is shipping code at twice the speed, can confidently predict project delivery timelines, and has seen a noticeable improvement in developer happ…

What tools did this team use?

LinearB, gitStream, Code Experts.

What results were reported?

Code shipping speed: twice the speed; Developer happiness: noticeable improvement; Culture improvement: biggest win (source-reported, not independently verified).

How is this quality assurance AI workflow structured?

Monitor DORA metrics and indicators → Retrospective root cause analysis → Auto-assign PRs to Code Experts → Auto-approve documentation-only PRs → Teams self-monitor via dashboards.