Data Collection
We gather insights from the AI developer community through our surveys and by analyzing open-source activity on GitHub.

Open-Source Monitoring
Our analysis focuses on a curated collection of GitHub repositories, identified through various methods to ensure comprehensive coverage of AI-related projects.

LLM Identification
We determine whether repositories utilize large language models (LLMs) or other AI tools by inspecting configuration files

Activity Measurement
Repository activity is evaluated based on the timestamp of the last commit. The more repositories actively using a specific LLM, the higher the recorded usage and activity metrics for that model in the open-source space.

Developer Activity Projection
We project repository activities to individual developers, allowing us to track and analyze AI adoption and usage patterns at the developer level across different projects and timeframes.

Developer Insights
Through our analysis, we collect additional metadata including developer locations, popularity scores, and other interesting metrics that help paint a comprehensive picture of AI tooling adoption and usage in the developer community.