Microsoft's .NET team assigned simpler refactoring tasks to Copilot in dotnet/android. Over 28 days, 82.4% of 17 agent pull requests were merged. Harder dotnet/maui tasks had a much lower merge rate, showing the importance of task selection.
GitHub Copilot
Documented AI practices. Highest Brain Score first.
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8 use cases
Brain Score, descendingDraft entries have not yet been human-reviewed. Claims and results belong to the linked sources.
Jiaming Shang used Copilot to generate a deployed typing practice website with English, Chinese Pinyin and 300 Tang poems. Source code and demonstrations are linked. The account documents repeated corrections and limitations rather than measured productivity gains.
A Microsoft team connected Copilot to Azure DevOps through MCP to retrieve manual test cases and generate Playwright scripts. Hundreds of domain tests were automated. Reduced manual effort is reported without a measured time comparison.
Port engineers delegate small refactorings, bug fixes and TODO items to Copilot while developing other features. Their retrospective reports better self-review and fewer minor review comments, without quantified savings.
Aldo used Copilot's coding agent to add optional header images to an existing Markdown blog. The post links the agent session and describes compatibility and testing requirements. No task-specific time saving is measured.
GitHub assigns Copilot issues to remove obsolete feature flags, conditional branches and associated tests across its platform codebase. Engineers review the proposed pull requests. The article describes reduced maintenance work but gives no savings measurement for this task.
During a healthcare software project, Microsoft ISE used Copilot to follow development guides, create required files and identify missing setup steps or tests. The team reports easier onboarding and time savings but provides no controlled measurement for this workflow.
Okta engineers used Copilot for routine coding and testing. A study involving 74 survey participants found improved motivation and perceived skills, but no significant change in pull requests, code volume or cycle time. Later results for Claude Code are separate.
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