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Modern software development is complex. Our projects have hundreds of files, intricate dependencies, and carefully thought-out architectural decisions.

The Problem

Anyone who’s used AI coding assistants has experienced this: you ask for help with a feature, and the AI generates code that completely ignores your existing patterns. Or worse, it breaks your carefully planned architecture.

After experiencing this frustration firsthand, I started building Giga—a different kind of AI coding assistant that maintains deep, persistent understanding of your entire codebase.

How Giga Works

The core innovation in Giga is what I call the “project brain”—a smart context management system that:

  • Automatically analyzes your project structure, dependencies, and architectural patterns
  • Maintains a living SPEC.md file that captures your project’s technical decisions and constraints
  • Integrates with git to track meaningful changes and evolve its understanding
  • Uses this persistent context to ensure AI suggestions align perfectly with your existing architecture

Early Results

The initial beta testing has been enlightening. Developers report that Giga:

  • Eliminates the need to repeatedly explain project structure to AI
  • Significantly reduces instances of AI suggestions breaking existing architecture
  • Maintains consistent understanding even as codebases grow