Async AI Job Queues with Gemini API and Cloud Tasks — Production Patterns for Timeouts, Retries, and Rate Limits
Migrate synchronous Cloud Run + Gemini calls to a Cloud Tasks async job queue. Covers retries, DLQ, idempotent workers, and cost modeling with working code.
When the Gemini API Quietly Gets Worse in Production: Detecting Output Quality Drift
Right after launch, your Gemini-powered product feels sharp. A few weeks in, something feels a little off, but you cannot put a number on it. This is the lightweight production monitoring setup I actually use to turn that 'feels off' into data, and to decide when to act.
Gemma 4 on MLX in Production: Quantization, Context Management, and Reasoning Fallbacks
Production-grade tuning for Gemma 4 on MLX: quantization choices, context strategies, and how to recover the Reasoning capability via hybrid Gemini API routing.
Rendering Gemini's Thought Summaries in a Next.js UI — A Production Pattern for Explainable AI
A production walkthrough for surfacing Gemini 2.5 / 3 thought summaries in a Next.js UI. Covers the SDK configuration, Server-Sent Events, a React collapsible component, observability, and the UX judgement calls you face when you decide how much of the AI's reasoning to show.
Type-Safe Structured Output with Gemini API and Pydantic v2: A Complete Production Guide
Learn how to combine Gemini API's response_schema with Pydantic v2 for type-safe LLM output processing. Covers validation, retry logic on failure, streaming integration, and a real-world product review analysis pipeline.
to Production Architecture for Gemini API 2026— Design Patterns for Building Scalable, Reliable AI Systems
A comprehensive guide to production-grade design patterns for Gemini API. Covers resilient API clients, multi-layer caching, multi-tenant design, observability, and cost control with complete code examples.
Gemini API Python: Works Locally But Fails on Server — Deployment Troubleshooting Guide
Gemini API Python SDK works fine locally but breaks on your production server? This guide covers the most common causes: missing environment variables, asyncio conflicts, timeout issues, Docker SSL errors, and serverless gotchas.
Building a RAG System With the Gemini API: From Embeddings to Production Deployment
A complete implementation guide for RAG systems using the Gemini Embedding API and Gemini 2.5 Pro. Covers chunk strategy, vector store setup, query expansion, reranking, hallucination mitigation, async optimization, and evaluation.
Build a Personalized Recommendation System with Gemini Embedding API — Real-Time Content Recommendations from User Behavior
Learn how to build a real-time personalized recommendation system using Gemini Embedding API. Covers system design, user profile modeling, cosine similarity ranking, caching, and production scaling — with complete Python code.
Running Gemini 2.5 Pro in Production: A Practical Implementation Guide
A production-focused guide to Gemini 2.5 Pro: streaming API, Context Caching for 75% cost reduction, Thinking budget control, multi-turn conversation management, and complete error handling patterns.
Gemini API Caching in Production — Operational Notes from an Indie Mobile Developer
Field notes on running Gemini API's Context Caching and Implicit Caching together inside indie mobile apps. Includes working Python code, six months of measured costs from AdMob-funded apps, and seven non-obvious operational pitfalls.
Gemini 2.5 Pro Thinking Mode Masterclass: Code, Debug, and Architecture in Practice
A practical masterclass on Gemini 2.5 Pro thinking mode for code generation, bug diagnosis, and architecture review. Budget optimization, output patterns, cost management.