Self-Healing Architecture for Gemini Computer Use — Production Patterns That Keep Browser Automation Alive Beyond Day Three
Gemini Computer Use looks magical in demos but breaks daily in production: vanishing elements, surprise modals, network jitter, off-by-four-pixel clicks. This guide builds a five-layer self-healing architecture in Python that classifies failures and recovers them automatically, with working code you can drop into your agent loop today.
Gemini API × Stripe — Production Usage-Based Billing for Indie AI SaaS
A complete guide to building a usage-based billing system for your Gemini API SaaS using Stripe Metered Billing and webhooks — production patterns included.
Production-Ready Function Calling with Gemini 2.5 Pro API — Realistic Patterns for Failures, Timeouts, and Hallucinations
Gemini 2.5 Pro's Function Calling is powerful, but it tends to land in 'works, but does odd things sometimes' territory in production. Here are the design patterns I arrived at running search, reservation, and notification agents.
Custom Gemini API Agent Loop Without ADK — A Complete Production Guide to Tool Calling, Memory, and Parallel Execution
Build production-grade AI agents using Gemini API directly without Google ADK. This guide covers custom agent loops, tool calling patterns, sliding window memory, parallel execution, and battle-tested error recovery strategies.
Five Design Decisions to Make Before Putting gemini-2.5-pro-latest in Production
Running gemini-2.5-pro-latest in production is more than picking a fast model. Here are the five design decisions — versioning, retry, cost, fallback, observability — that I now resolve before any new service ships.
Defending Gemini API Responses with Schema Validation — Never Let Unexpected Formats Reach Production
Gemini's structured output is convenient, but in production the day always comes when an unexpected format slips through. This piece walks through layered Zod/Pydantic validation, repair prompts, and graceful degradation — the defense lines I run on my own apps.
Architecting a Multi-Tenant SaaS on Gemini API — Tenant Isolation, Usage Metering, and Runaway Cost Defense in Production
A field-tested blueprint for serving Gemini API to multiple tenants on a single backend — covering tenant isolation choices, per-tenant rate limiting in Redis, request-level usage metering for billing, and runaway-cost defenses.
Tracing Gemini API in Production with OpenTelemetry: See Every Step of a Single Request
After three months of running Gemini API in production, plain logs stop telling you why latency, cost, or failures spike. This guide walks through wrapping Gemini in OpenTelemetry — Python and Node.js code, GenAI semantic conventions, sampling, and Grafana/Datadog wiring — so you can see the full anatomy of every request.
Building Self-Critiquing Agents with Gemini API: A Production-Ready Guide to Reflection and Critic-Refiner Patterns
A production-grade walkthrough of Reflection and Critic-Refiner patterns with Gemini 3 Pro and 3.5 Flash-Lite. Covers implementation, cost guards, over-correction defenses, and monitoring signals from real deployments.
Safely Migrating Gemini Model Versions with Shadow Traffic — A Production Pattern for Measuring Output Drift
Stop treating Gemini model migrations as a coin flip. This guide walks through a production-ready shadow traffic architecture — duplicate real inputs to the new model, quantify output drift, and cut over progressively. Includes Python and Cloud Tasks code you can ship today.
Designing Production-Grade Safety Controls for the Gemini API: A Layered Moderation Architecture That Minimizes False Positives Without Letting Abuse Through
Relying on the Gemini API's Safety Settings alone leads to legitimate questions getting false-blocked or carefully crafted malicious prompts slipping through. This guide shows a four-layer moderation design that stands up in production.
Gemini API × Langfuse — A Production Playbook for LLM Observability
A practical, production-grade guide to wiring Gemini API into Langfuse — tracing architecture, cost attribution, LLM-as-Judge on live traffic, PII masking, and sampling — with runnable code.