Never hand Gemini a raw ANR thread dump
An ANR dump came in at 96 threads and 33,616 characters. Keeping only main cuts 98 percent, but it also deletes the thread that caused the block. Here is a lock-chain preprocessor, measured three ways.
Gemini API System Instructions and Prompt Design — Practical Techniques to Dramatically Improve Output Quality
Practical techniques for designing system instructions and prompts that produce stable, high-quality output from the Gemini API. Includes working code examples for format control, few-shot learning, temperature tuning, and error handling.
Gemini Prompt Engineering Guide — System Instructions, Few-shot & Chain-of-Thought
Get stable output from Gemini through prompt design, using three techniques: System Instructions, Few-shot, and Chain-of-Thought. Includes a real pitfall I hit while auto-classifying images for a wallpaper app.
When the Default Model Silently Upgrades: Catching Prompt Regressions in Numbers
Gemini 3.5 Flash is now the default and you can no longer turn it off. Assuming your responses can shift without you touching the prompt, here is how to bundle prompt, model, and sampling into one variant and catch regressions with canaries and an LLM judge — in working code.
Gemini API × Sentry: A Production Pipeline for LLM Error Tracking and Prompt Failure Observability
Pair Sentry's error tracking with Gemini-specific failure modes so you can catch safety filter blocks, recitation rejections, empty completions, and quiet latency drift in production.
Dynamic Few-Shot for Gemini API — A Self-Improving Prompt That Picks Examples by Vector Search
Hand-picked, hard-coded few-shot examples stop scaling once your inputs drift. This guide builds a Gemini Embeddings + vector search pipeline that selects the best 3-5 examples per request and grows them from production feedback, with copy-paste code.
Measuring Classification Confidence with Gemini API Logprobs — A Practical Walkthrough
Use the Gemini API responseLogprobs option to extract per-token confidence scores, then turn them into an auto-vs-review gate for classification — with working Python code and the threshold thinking behind it.
Writing Gemini Gems Custom Instructions That Actually Behave
The way you structure custom instructions for a Gemini Gem changes its behavior dramatically. Here are the patterns I converged on after several Gems and a lot of iteration.
Reading a 200-Page Contract with Gemini 2.5 Pro — Five Techniques That Move Long-Context Analysis to Production Quality
Using Gemini 2.5 Pro's long context for real business work takes more than stuffing the whole document in. Here are the five techniques I found most effective for contracts, meeting minutes, and technical specs.
Gemini × DSPy: Retire from Prompt Craftsmanship — Automated Prompt Optimization
A hands-on implementation guide for combining Stanford's DSPy framework with Gemini to end the era of hand-written prompts. Covers Signatures, Modules, Optimizers, LLM-as-a-Judge metrics, and production pipelines — all with working code.
Don't Let Your Gemini Prompts Silently Rot — A Practical Regression Testing Playbook with Pytest
Ever tweaked a prompt and watched production quality quietly degrade? This article walks through testing Gemini API prompts with Pytest, combining snapshot tests and LLM-as-Judge to catch regressions automatically — all from the perspective of an individual developer running things solo.
Designing a Production Prompt Management System for Gemini API — Versioning, A/B Testing, and Canary Rollouts
A complete implementation guide for solving the prompt versioning, attribution, and safety challenges in production Gemini API deployments — using FastAPI, PostgreSQL, Redis, A/B testing, and canary rollouts.