Worked on the google-gemini/gemini-cli repository to deliver Gemini 3.1 model configurations, introducing both aliases and thinking levels to enhance content generation workflows. Focused on AI model development and model configuration using TypeScript, the work enabled granular control over output quality and consistency by allowing defined thinking levels for each model variant. The technical approach involved implementing core configuration fixes that reduce misconfiguration risk and support scalable deployment of Gemini-3.1 variants. This foundation streamlines experimentation and per-model routing, aligning with business goals for higher quality outputs and faster iteration cycles while improving reliability across diverse use cases.