Augment Code
FreemiumAI software agent platform with deep codebase understanding, working across IDE, CLI, code review, and Slack to accelerate engineering at scale.
What is Augment Code?
Augment Code is a professional AI coding platform designed for engineering teams and organizations that need AI to truly understand their entire codebase, not just the currently open file. Its Context Engine indexes your real codebase, dependencies, documentation, style guides, and recent changes, then surfaces curated, relevant context to AI agents working across your IDE, CLI, code review, and Slack. Augment agents can write and review code, manage pull requests, run intent-based automation, and integrate into any development workflow. With enterprise-grade security, a Trust Center, and support for VS Code and JetBrains, Augment is built for teams who need AI that thinks like a senior engineer familiar with their entire system.
Key Features
How to Use Augment Code
✅ Best For
- Professional software engineers working on large, complex codebases
- Engineering teams wanting AI that understands their full system architecture
- Organizations needing enterprise-grade AI coding with security and compliance
- Developers working across IDE, terminal, and code review workflows
- Teams wanting AI assistance integrated into existing PR review processes
- Companies looking to accelerate development velocity without compromising code quality
❌ Not For
- Individual hobbyists or students needing a simple code completion tool
- Teams without an established codebase for the Context Engine to index
- Developers needing a visual design-to-code workflow
- Users wanting a fully autonomous zero-oversight AI code builder
Reviews
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Pricing
- ✓VS Code and JetBrains install
- ✓basic completions
- ✓standard context
- ✓Full agent access
- ✓Context Engine
- ✓IDE and CLI agents
- ✓credit-based usage
- ✓Team collaboration
- ✓code review agent
- ✓Slack integration
- ✓admin controls
- ✓Full platform
- ✓SSO
- ✓audit logs
- ✓dedicated support
- ✓custom SLA
Prompts to Try
Analyze the entire payment module and identify any functions that don't follow our error handling patterns defined in the style guide
Implement a feature for user notification preferences, following the same patterns used in the email preferences module
Review this pull request and flag any violations of our architectural principles or performance anti-patterns