Quality assurance · Production
Yum! automates 35.8% of PRs and saves 321 dev hours/month with LinearB
The problem
Yum!'s engineering teams lacked data-backed visibility into where time was being spent; meetings dominated schedules leaving little room for coding, PR reviews were inconsistent, and engineers spent too much time on administrative tasks rather than coding.
Workflow diagram · grounded in source
1
Adopt LinearB for visibility
trigger
“Alex actively sought out tools like LinearB to enhance visibility and streamline processes”
2
Track planning and capacity metrics
integration
“By tracking these key indicators, Yum! gained real-time insights into team performance, allowing them to spot inefficiencies and take corrective action before their sprints got derailed”
3
Data-driven sprint conversations
output
“LinearB helps provide a common, data-backed language that my Product Manager, Tech Lead, and I use to improve how we conduct our sprints and planning”
4
Route PRs to code experts
routing
“Code Experts: Ensuring PRs are automatically routed to and reviewed by engineers with the most knowledge on the core platform code”
5
AI sprint summary generation
ai_action
“AI-generated retrospectives analyze past sprints and provide automated insights into team performance, like carryover items and major accomplishments”
6
AI summaries drive process improvements
feedback_loop
“We started comparing the AI-generated summaries to our actual sprint progress, and it made us look deeper. We'd spot differences and ask: Why is this blocked? Could we have done something differently at the start of the sprint?”
Reported outcome
LinearB enabled Yum! to automate 35.8% of all PRs saving 321 developer hours per month, while AI-powered sprint summaries improved retrospectives and data-backed planning metrics improved cross-team communication.
Reported metrics
PRs automated (percentage)35.8%
PRs merged per month1793
PRs automated per month (count)642
Minutes saved per PR30 minutes
Show all 6 reported metrics
PRs automated (percentage)35.8%
PRs merged per month1793
PRs automated per month (count)642
Minutes saved per PR30 minutes
Total dev hours automated per month321 hours
overall cycle timereduce their overall cycle time
Reported stack
LinearBWorkerBgitStream
Frequently asked questions
What did this team achieve with this AI workflow?
LinearB enabled Yum!
What tools did this team use?
LinearB, WorkerB, gitStream.
What results were reported?
PRs automated (percentage): 35.8%; PRs merged per month: 1793; PRs automated per month (count): 642; Minutes saved per PR: 30 minutes (source-reported, not independently verified).
How is this quality assurance AI workflow structured?
Adopt LinearB for visibility → Track planning and capacity metrics → Data-driven sprint conversations → Route PRs to code experts → AI sprint summary generation → AI summaries drive process improvements.