Gemma 4 Local AI Engineering on Mac

Series Introduction

This series is for developers who can already run LLMs locally at a basic level and want to level up to real engineering: with clear architecture, stable APIs, reliable RAG, quality metrics, and a rollout checklist.

You won't learn through quick demos. Each lesson is anchored to the real-world requirements of a local AI stack used by an internal team.

What You'll Learn

• Design a local-first architecture for AI products
• Build a Gemma 4 stack on Mac to dev team standards
• Create an API gateway, prompt contracts, and output schemas
• Build a Vietnamese-language RAG pipeline from ingestion to hybrid retrieval
• Measure quality with an eval framework and operational observability
• Harden the system before internal deployment

Prerequisites

• Mac with Apple Silicon (M1 or later), 24GB+ RAM recommended
• Basic familiarity with Terminal and Git
• Basic Python or TypeScript knowledge
• Understanding of APIs, JSON, and HTTP

Source Code

All demo code accompanying this series:

xdev-asia-labs/gemma-4-local-ai-engineering-on-mac

Outcome After This Series

After completing this series, you'll be able to build a mini local AI platform for your team:

1. A chat UI for non-technical users
2. An API for internal applications
3. RAG with citations and stable quality
4. Monitoring and a controlled release process