Track AI Tool Adoption
Coderbuds automatically tracks AI coding tool usage across your team, helping you understand adoption trends, tool standardization, and productivity patterns. No manual tracking required.
Detected AI Tools
We automatically detect when pull requests were created using:
How Detection Works
We use a two-tier detection approach to accurately identify AI tool usage:
AI tool attributions in PR descriptions, commit authors, branch naming patterns, and tool-specific footers. When these markers are found, we can definitively identify the tool used.
AI-powered analysis of commit patterns, code structure, and PR formatting when no explicit markers are found. This helps identify AI usage even when developers don't explicitly tag it.
Team Metrics
Percentage of active developers using AI tools
Percentage of pull requests created with AI assistance
Which AI tools your team is using most
These metrics help you understand adoption trends, identify standardization opportunities, and measure the impact of AI tools on your development workflow.
Common Use Cases
Tool Standardization
Identify which AI tools your team is using and make informed decisions about standardizing on specific tools.
Adoption Tracking
Monitor how AI tool adoption grows over time and identify developers who might benefit from training or support.
ROI Analysis
Understand how AI tool usage correlates with productivity metrics like PR velocity and deployment frequency.
Trend Analysis
Track adoption trends over time and see how new tools gain traction within your organization.
Accessing AI Metrics
Navigate to Team Insights
Go to your team dashboard and click on the "Team Insights" tab to see AI adoption metrics.
View Overall Adoption
See your team's overall AI adoption rate and how many PRs are being created with AI assistance.
Explore Tool Breakdown
View detailed charts showing which AI tools are most popular on your team and how usage has changed over time.
About Detection Accuracy
AI usage detection is approximately 80-90% accurate. We prioritize avoiding false positives—when uncertain, we assume code is human-written. Metrics are designed for trend analysis, not precise attribution. Some AI usage (especially copy-paste from ChatGPT without explicit markers) may not be detected.