quality_assurance · saas · workflow
Microsoft's AI-powered code review assistant scales to over 90% of PRs and 600K pull requests per month
PR reviews at Microsoft had significant friction: reviewers spent time on low-value feedback while meaningful concerns like architectural decisions and security implications were overlooked, and at scale—thousands of developers and repositories—PRs waited days or weeks before being merged.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · PR creation triggers AI review
Whenever a pull request is created, the AI assistant automatically kicks in as one of the reviewers.
Tools used
AI code reviewerlarge language models
Outcome
The AI reviewer now supports over 90% of PRs across Microsoft, impacting more than 600K pull requests per month, with repositories onboarded to the tool observing 10–20% median PR completion time improvements.
Results
Time saved600K
Volumeover 90%
Grounding & classification
Source type: technical build writeup
23 fields verified against source quotes.
code generationconversational aiquality inspectionsummarizationcode diff prhuman review describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedsoftwareautomation ratecycle time reductionemployee productivitythroughput increasetechnical build writeupquality assuranceai draft human approval