Two Weeks Until Google I/O 2026: What Gemini API Developers Should Prepare Right Now
With Google I/O 2026 just around the corner, here's what developers running Gemini API in production should do this week — from pinning model versions and recording baselines to tracking deprecation timelines before the announcements hit.
Cutting Gemini API Costs by 80%: Context Caching and Implicit Caching
A hands-on guide to reducing Gemini API costs by 80% using Context Caching and Implicit Caching. Includes decision frameworks, working code examples, and a troubleshooting checklist for when caching stops working in production.
Judging Gemma 4 and Nemotron 3 Nano Omni on 100 of My Own Images, Not a Benchmark Score
Heron-Bench and JMMMU headline scores are the wrong input for an adoption decision on local Japanese multimodal models. Using a wallpaper classifier as the case, here is how to build a 100-image eval set, weight errors by what they actually cost, and catch regressions when you re-quantize.
Solving Gemini API Cold Starts — Production-Grade Startup Optimization for Cloud Run, Lambda, and Workers
When you put Gemini API on serverless, the first request takes six seconds. This guide breaks down where the time goes and shows concrete startup-optimization patterns for Cloud Run, AWS Lambda, and Cloudflare Workers — with real numbers, runnable code, and cost trade-off advice.
Gemini 3.2 in Production: A Playbook for Model Selection, Cost Optimization, and Implementation Patterns
Gemini 3.2 has plenty of feature coverage, but very little material on actually deploying it to production. This playbook covers model selection (Pro/Flash/Nano), API patterns, cost optimization, competitive comparisons, and operations — from running Gemini across four sites.
7 Design Decisions When Wiring Gemini API Into a Solo App — From Error Design to Quality Monitoring
After embedding Gemini API into several of my own apps, I've collected seven design decisions that come up in production but rarely in tutorials — fallback layering, dynamic model switching, latency UX, and lightweight quality monitoring. This is the playbook I use today.
Building a Fully Edge RAG with Gemini API and Cloudflare Vectorize: A Production Guide for Low Latency, Low Cost, Global Delivery
Combine Gemini Embedding with Cloudflare Vectorize to ship a production RAG that runs entirely inside the Workers runtime — global latency, predictable cost, and a defensive layer covering subrequest limits, retries, and tenant isolation.
Building GraphRAG with the Gemini API — A Complete Production Guide to Hybrid Knowledge Graph + Vector Retrieval
When pure vector search hits a wall on multi-hop, relational, and aggregation queries, GraphRAG fills the gap. This guide walks through a production hybrid GraphRAG architecture powered by Gemini 2.5 Pro and Flash, with working code.
Citation-Grounded RAG with Gemini: Production Patterns for Source Attribution and Hallucination Detection
A practical guide to wiring trustworthy citations into a Gemini-powered RAG pipeline. Covers structured output, post-hoc validation, UI rendering, and a quantitative grounding score you can put on a dashboard.
Vertex AI Agent Engine × Gemini 2.5 Pro — Production Deployment for Managed Agents
Deploy ADK-based agents powered by Gemini 2.5 Pro on Vertex AI Agent Engine. Covers the trade-offs vs Cloud Run, sessions, tool calls, tracing, and a realistic cost model.
Putting an AI That Answers Phones Into Production: Building a Phone Voice Agent With Gemini Live API and Twilio Media Streams
Bridge Twilio Voice and Gemini Live API over WebSocket to build a phone-answering AI agent that holds up in production. Full code, interruption handling, function calling, deployment notes, and per-minute cost math.
A Blueprint for Production-Grade Structured Output with Gemini API
A practical blueprint for running Gemini API's Structured Output reliably in production. Covers schema design, error handling, and performance optimization end-to-end.