Folding a Local Gemma 4 into Daily Work — Practical Notes on the Ollama API and Response Speed
Taking a local Gemma 4 you can now run interactively and folding it into real work: how to hit Ollama's local API from a script, tricks to improve perceived response speed, and a two-tier fallback that automatically routes to the cloud Gemini API — code included.
Finding Every Reference to the Image Preview Models Before They Stop on June 25
gemini-3.1-flash-image-preview and gemini-3-pro-image-preview stop on June 25. Here is a dependency audit for surfacing references buried in rarely-run branches and batches before the cutoff.
Gemini 3.2 vs Claude Sonnet 4.6 vs GPT-4o — An Honest Comparison for Indie Developers (May 2026)
A practical comparison of Gemini 3.2, Claude Sonnet 4.6, and GPT-4o from an indie developer's perspective — covering code generation, writing quality, API costs, latency, and honest weaknesses.
Auto-Generate Narration Videos with Gemini TTS — From Text Input to MP4 Output (2026 Guide)
Build a Python pipeline that converts text into narration videos using Gemini TTS API — generating audio, subtitles, and compositing the final MP4 with FFmpeg. Includes real API cost and timing benchmarks.
Building a B2B Business Automation SaaS with Gemini 2.5 Pro Function Calling — Revenue Blueprint
A complete guide to building and selling B2B business automation SaaS using Gemini 2.5 Pro Function Calling. Covers API architecture, multi-tenant design, pricing strategy, and the sales process that closed first contracts within 3 weeks of demo.
Putting Gemini 2.5 Flash Thinking Mode to Work: Reading the Cost-Accuracy-Speed Tradeoff
After three months of testing Gemini 2.5 Flash's Thinking Mode on real projects, here's what actually works: which tasks benefit, which tasks waste budget, and how to build a cost-aware switching layer.
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.
Gemini 3.2 Developer Monetization Blueprint — Building First-Mover Advantage with the New Model
With Gemini 3.2 reshaping the AI services market, here's how indie developers and small teams can raise client rates, design profitable own-products, and build first-mover positioning in a specific vertical — written from a working operator's perspective.
Migrating to @google/genai: Seven Errors That Will Eat Your Afternoon
A field-tested guide to the seven errors you are most likely to hit when migrating from @google/generative-ai to @google/genai, with copy-paste fixes for Node.js and TypeScript codebases.
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.
Gemini 2.5 Pro vs 2.0 Flash — Picking a Default Model for Solo Development
A hands-on comparison of Gemini 2.5 Pro and 2.0 Flash from a solo developer's view: where accuracy actually diverged on structured extraction, latency and per-request cost, and the Flash-by-default, Pro-where-it-matters routing I settled on.
Building Agentic Systems with Gemma 4: Mastering Function Calling
A practical guide to implementing Function Calling with Gemma 4 for building reliable agentic systems. Learn how Gemma 4 differs from other open models, structured JSON output, and system prompt optimization with code examples.