API / SDK
Practical guides to the Gemini API and SDKs — quickstarts, Function Calling, structured output, streaming, cost optimization, and troubleshooting.
Gemini Code Execution API: to AI-Generated Code Execution
Master the Gemini Code Execution API. Execute Python code generated by AI in a secure sandbox, perform complex calculations, and automate data analysis tasks.
Gemini 1M Token Long Context Strategies — Production Patterns for Large Document Processing
Master Gemini 2.5 Pro's 1M token context window for production workloads. Covers context caching, chunking strategies, RAG comparison, cost optimization, and real-world codebase + PDF corpus analysis.
Fine-Tuning Gemini: Building Specialized Models for Domain-Specific Applications
Complete guide to fine-tuning Gemini models. Learn dataset preparation, training strategies, evaluation metrics, and production deployment for custom AI.
Reading Gemini API Logs by What Survived — Field Notes on Logging & Datasets
Use the Gemini API logging and datasets tool from a results-first angle — not token counts or latency, but whether each output actually survived to publication. Includes tying log review to spend caps and API key hygiene.
Gemini API Quickstart — Getting Started with Python and TypeScript
Get started with the Gemini API in Python or TypeScript — from API key setup and SDK installation to streaming, safety settings, and practical error handling.