Natural language conversation with AI
Augment Code helps engineering teams build software with AI agents that understand entire codebases. Its Context Engine
Pricing
Freemium
Category
AI Coding
Platforms
Web
Languages
EN, CN
Highlights
Augment Code helps engineering teams build software with AI agents that understand entire codebases. Its Context Engine
Natural language conversation with AI
Context-aware intelligent responses
Multi-turn dialogue support
Overview
Augment Code helps engineering teams build software with AI agents that understand entire codebases. Its Context Engine keeps a live view of code, dependencies, documentation, issues, and recent changes, then feeds that into agents across IDEs, the terminal, a Mac desktop workspace called Intent, and GitHub code review. The result is AI support that behaves more like a senior teammate than an autocomplete toy, aimed squarely at professional teams shipping production code.
What is Augment Code? Augment Code helps engineering teams build software with AI agents that understand entire codebases. Its Context Engine keeps a live view of code, dependencies, documentation, issues, and recent changes, then feeds that into agents across IDEs, the terminal, a Mac desktop workspace called Intent, and GitHub code review. The result is AI support that behaves more like a senior teammate than an autocomplete toy, aimed squarely at professional teams shipping production code. Key Features: Context Engine: Continuously indexes repositories, libraries, docs, and history so agents act with project level awareness instead of file level guessing. IDE Agents (VS Code & JetBrains): Turn natural language tasks into edits and pull requests with task lists, multi step workflows, and persistent memories. Intent Workspace: Mac desktop app that coordinates multiple agents around a living spec, keeping implementation aligned with requirements in isolated, reproducible workspaces. Auggie CLI & Slack Integration: Terminal first and chat based agents that share the same context, ideal for shell driven workflows and lightweight collaboration. Pros High quality context: Strong code reuse and architecture awareness compared to typical coding assistants. Multi surface coverage: Works in IDEs, CLI, Slack, and GitHub reviews, all sharing the same understanding of the codebase.
Key Features
Natural language conversation with AI
Context-aware intelligent responses
Multi-turn dialogue support
Customizable conversation style
Real-time interaction capabilities
Screenshots
FAQ
Common questions
Use Cases
User Reviews
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