When to Hand Conversation State to the Server: previous_interaction_id vs. Pruning History Yourself
With the Interactions API, passing previous_interaction_id lets the server hold conversation state so you stop resending history. But a large tool output that lands mid-conversation can't be pruned afterward, and every later turn drags its weight. Here is a branching design that mixes server-side state with client-side pruning, plus a thin, working Python wrapper.
Controlling thinking_budget in Gemini 2.5 Pro — Cut Costs by 70% Without Sacrificing Reasoning Quality
Leaving thinking_budget unset in Gemini 2.5 Pro leads to unexpected costs. This guide covers task-level budget design, dynamic control, and production monitoring with working Python code.
Why I Always Resize Images With Pillow Before Sending Them to the Gemini API
A practical look at why preprocessing images with Pillow before they reach the Gemini API quietly cuts both latency and token usage. Numbers from a real personal project, plus the helper function I now reuse everywhere.
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 API Semantic Router: Implementation Notes for Splitting Flash and Pro Smartly
Implementation notes for building a production-grade semantic router that automatically dispatches Gemini queries between Flash and Pro. Includes Python and TypeScript working code, a two-stage design pattern, and seven implementation insights from running it inside an indie wallpaper app.
Never Generate the Same Narration Twice: Cache-Key Design and Invalidation for Gemini TTS Output
For apps that replay the same audio over and over—meditation, language learning, storytelling—caching the Gemini TTS output itself drives the variable cost to near zero. This is a working design: how to build a cache key that text alone can't cover, a two-tier server-plus-device cache, and an invalidation policy that survives model shutdowns like the August 17 image-model deprecation.
Ingested but Never Cited: Pruning a File Search Store with Citation Logs and a Quarantine Window
Most documents in a File Search store are never cited, quietly draining both cost and retrieval quality. Learn to log grounding metadata, surface never-cited documents from real usage data, and prune them safely with a quarantine window — with working code.
Routing Between Local Gemma 4 and the Gemini API Cut My Bill from ¥32,000 to ¥9,000 — A Production Hybrid Router Design
How I cut a ¥32,000/month Gemini API bill to the ¥9,000 range with hybrid inference: routing design, a full Python router, production pitfalls, and how Gemma 4 arriving on the Gemini API in July 2026 changes the decision.
After You Improve the Prompt, How Far Back Do You Regenerate? — Designing a Budget-Bounded Backfill
A prompt improvement only helps future output — thousands of old artifacts stay on the previous generation. This piece covers a budget-bounded backfill: selection scoring, edit-detection hashes, a pre-replacement gate, and a resumable cursor, with working code.
Turning Articles into Audio with the Gemini 3.1 Flash TTS Preview: Splitting Long Text, Stitching It Back, and What It Actually Costs
The Gemini 3.1 Flash TTS preview launched today. Here is a single-narrator pipeline that converts a written article into clean audio, including how to split long text, stitch PCM without ugly seams, keep one voice steady, and estimate the real per-article cost.
Before Free Users Quietly Eat Your Margin: Tier Design and Cost Ceilings for Gemini API Apps
Protecting the margin on a Gemini-powered app means designing around a per-user monthly cost ceiling, not request counts. Tier-aware model routing, real-cost metering in KV, and the token-bloat traps that drain profit, with working code.
Structured Product Image Analysis with the Gemini API — A Production Pipeline Built on Thousands of Photos
Turn a one-off image analysis script into a production pipeline that auto-generates tags, descriptions, and categories at scale — covering structured output, resumable batches, measured cost, and model routing learned from real indie-developer operation.