Giga AI

About Giga AI

Stop fighting with your AI and start building your business. Giga AI is the revolutionary app-building tool that gives your AI a "project brain," transforming it from a frustrating, error-prone assistant into a focused, intelligent partner. It's designed for first-time builders, solo hackers, and engineering teams who are tired of AI hallucinations, context loss, and endless debugging. Giga AI installs directly into your existing workflow—compatible with Cursor, VS Code, Claude Code, and more—to automatically analyze your codebase and generate intelligent "rules." These rules ensure your AI always understands your project's unique structure, goals, and preferences, leading to code that works right the first time. The result? A staggering 72% reduction in bugs and errors, with over 10,000 builders reporting they save an average of 20 hours per month. Giga AI's core value proposition is simple: no more re-prompting, no more confusion, just faster, higher-quality code generation that is perfectly aligned with your vision, letting you spend your time building your MVP instead of fixing AI mistakes.

Features of Giga AI

Giga Memory

Giga Memory is your AI's long-term memory. It learns and remembers your past decisions, coding preferences, and project-specific patterns. This means your AI assistant won't make the same suggestion you rejected yesterday or forget the architectural style you've been using. It builds upon your history, creating a smarter, more personalized coding experience that improves with every interaction, ensuring consistency and saving you from repetitive corrections.

Giga Context

This is the powerhouse feature that eliminates AI confusion and hallucinations. Giga Context automatically manages and understands the context across your entire project and all its integrations. It generates detailed rules files that analyze your codebase from multiple angles, giving your AI a deep, structural understanding. With this context, your AI never gets "lost," stops inventing non-existent functions, and stays perfectly aligned with your actual code, dramatically improving output quality.

Giga Planner

Before you write a single line of code, Giga Planner helps you architect your vision. It guides you through planning your application and Minimum Viable Product (MVP), helping to break down complex ideas into actionable, buildable steps. This feature ensures your AI development work is strategic and goal-oriented from the very start, preventing wasted effort on features that don't align with your core business objectives.

Giga Build

Giga Build is the intuitive, vibe-coding interface crafted specifically for first-time builders and developers who think in terms of goals, not just syntax. It translates your high-level instructions and project plans into precise, context-aware actions for your AI. This interface makes commanding your AI feel natural and powerful, turning abstract ideas into functional code without requiring you to be an expert prompt engineer.

Use Cases of Giga AI

The Solo Founder Building an MVP

A non-technical or solo technical founder can use Giga AI to systematically build their app from scratch. With Giga Planner to structure the vision and Giga Context to keep the AI on track, they can develop a working prototype without getting bogged down by complex debugging or AI misunderstandings, turning their idea into a shippable product in record time.

The Developer Enhancing an Existing Codebase

Developers working on large, complex existing projects use Giga AI to integrate new features safely. Giga Memory and Giga Context ensure the AI fully understands the legacy code, patterns, and libraries in use, allowing it to generate new code that fits seamlessly without breaking existing functionality or hallucinating incorrect APIs.

The Team Lead Standardizing Code Quality

Engineering team leads can implement Giga AI to ensure consistent code generation across their team. By establishing shared context and memory rules, every team member's AI assistant adheres to the same project standards and best practices, reducing review cycles and elevating overall code quality and cohesion.

The Freelancer Managing Tight Client Deadlines

Freelancers and consultants use Giga AI to accelerate development for client projects. By eliminating hours spent on debugging AI errors and re-prompting, they can solve complex problems (like authentication or integrations) faster, meet aggressive deadlines reliably, and deliver higher-quality work, leading to more satisfied clients and the ability to take on more projects.

Frequently Asked Questions

How does Giga AI integrate with my current setup?

Giga AI is designed for seamless integration. You can install it as an extension or companion tool in popular code editors and AI assistants like Cursor, Visual Studio Code (VS Code), and Claude Code in a matter of seconds. It works alongside you, analyzing your code as you write without disrupting your existing workflow.

Is my code safe and private with Giga AI?

Absolutely. Giga AI prioritizes your privacy and security. Your code is never stored on their servers for long-term training purposes, nor is it used to train public AI models. The analysis happens to provide you with context, and your intellectual property remains yours. They also offer clear guarantees like a money-back policy to ensure trust.

I'm a beginner. Is Giga AI too complex for me?

Not at all! Giga AI is built specifically with first-time builders in mind. Features like Giga Planner and the intuitive Giga Build interface are designed to guide you through the process. It helps you plan your app and translates your goals into actions, making AI-powered development accessible even if you're not an expert programmer.

What if Giga AI doesn't work well with my project?

Giga AI offers a risk-free trial with a money-back guarantee, allowing you to test it thoroughly with your specific codebase and workflow. The tool is trusted by over 10,000 builders across diverse projects, and its automatic context analysis is designed to adapt to a wide variety of project structures and tech stacks.