Gemini × DSPy: Retire from Prompt Craftsmanship — Automated Prompt Optimization
A hands-on implementation guide for combining Stanford's DSPy framework with Gemini to end the era of hand-written prompts. Covers Signatures, Modules, Optimizers, LLM-as-a-Judge metrics, and production pipelines — all with working code.
Gemini API Production Performance Tuning — A Triple Optimization Strategy for Latency, Throughput, and Cost
Learn how to simultaneously optimize latency, throughput, and cost in production Gemini API deployments. Covers Flex/Priority inference, Context Caching, intelligent model routing, and async batch processing with working code and benchmark results.
Gemini API × PostgreSQL Complete Implementation Guide — Building an AI-Driven Database Optimization System for Production
A complete production-ready guide to automating PostgreSQL optimization with Gemini 2.5 Pro — covering Text-to-SQL generation, EXPLAIN plan analysis, index recommendations, and schema reviews using Python and FastAPI.
Gemini 3.1 Flash High-Speed Inference API: Implementation Techniques for Streaming, Function Calling & Batch Processing
Master the technical architecture of Gemini 3.1 Flash and understand how fast inference works. Learn optimal implementation patterns for streaming, function calling, and batch processing with code examples. Make data-driven model selection decisions by comparing Flash with Pro models.
Estimating Gemini API Costs Before You Send — count_tokens in Practice
Use Gemini's free count_tokens call to measure input tokens and costs before each request, then cut spend with caching and model selection.