All Articles
When a Deploy Drops the Webhook: Reconciling Gemini Long-Running Operations with a Belt-and-Suspenders Design
Even after you move from polling to Webhooks, events still get dropped during deploys and transient 5xx windows. Here is how I double up Gemini long-running operations with an operation ledger and a low-frequency reconciliation poller so a missing terminal event never goes unnoticed.
Running Gemma 4 Locally on Windows — A Hands-On LLM in Two Commands with Ollama
How to run Google's lightweight open model Gemma 4 locally on a Windows laptop. With Ollama, you go from install to running in effectively two commands. Plus how to split work between the cloud Gemini API and a local Gemma.
When Gemini API Quietly Dies on the Edge from Subrequest Limits — Field Notes on Budgeting What's Left
Running Gemini API on Cloudflare Workers is calm until traffic rises or a tool chain deepens, and then it fails on the subrequest limit. Here are the instrumentation patterns I use to measure per-request consumption and treat it as a budget, drawn from the sites I run as an indie developer.
Stopping Gemini API Function Calling Loops: Why They Happen and How to Break Them
Your tool-calling agent keeps invoking the same function and never finishes. Here is how to diagnose the loop and bake stop conditions into your prompt, code, and tool responses — including catching regressions when the default model changes and detecting result-based stalls.
Your File Search Store Goes Stale in Production — Catalog Sync and Drift Detection That Actually Hold
Load a catalog into File Search once and forget it, and within weeks it starts confidently pointing users at assets you already pulled. Here is the sync pipeline I run: hash-based incremental import, a blue/green rebuild that swallows deletions, and a nightly drift audit.
Integrating Gemini 3.2 Pro Function Calling into iOS/Android Apps: Production Design Patterns
A practical guide to integrating Gemini 3.2 Pro Function Calling into iOS and Android apps. Includes working SwiftUI, Kotlin, and Python code, plus production patterns proven in a real indie wallpaper app — cost, latency, staged rollout, and regression testing.
Your Gemini API Average Latency Looks Great — But Some Users Still Get Stuck. Defending p95/p99
Your average TTFT is fast, yet a fraction of users keep hitting frozen responses. That is a tail-latency problem (p95/p99). From measurement to model routing, streaming budgets, cache accounting, and retry design — here are the defenses that actually held up in production, with code.
Implementing Gemini API Function Calling — Parallel Calls, Tool Chains, and When to Use Managed Agents
Production patterns for Gemini API Function Calling: parallel calls, error handling, and tool chaining, plus when to use Managed Agents and how to pin the tool-selecting model to a GA release.
Generating a Thumbnail From a Video With Nano Banana 2 (gemini-3.1-flash-image)
A hands-on guide to passing a whole video as context to the GA model gemini-3.1-flash-image (Nano Banana 2) and generating a single thumbnail. Covers how it differs from frame extraction, the preview-to-GA migration, and measured cost and time per image.
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.
Putting Gemini image generation to work: from prompt design to thumbnails generated from video
A practical playbook for running Gemini image generation as a repeatable workflow instead of a lucky dip. From decomposing prompts into reproducible parts to the video-to-image automation unlocked by the Nano Banana 2 GA, with working code, a pre-publish quality gate, and a design that survives preview shutdowns.
Gemini API on Google Cloud: Diagnosing Production Errors Layer by Layer
Systematically diagnose Gemini API errors in Google Cloud production environments. Covers IAM permissions, Vertex AI vs AI Studio, VPC Service Controls, quota management, service accounts, and multi-region failover with full code examples.