Augment Agent: RIP Cursor! NEW Agentic AI IDE! AI Software Engineer Automates Your Code (Opensource)

Key Concepts

• Augment Agent: An AI pair programmer that understands your codebase and learns as you work.
• Sway Bench: A benchmark for evaluating AI agents on real-world software engineering tasks.
• Persistent Memory: The ability of an AI agent to learn from past coding styles, refactors, and infrastructure conventions.
• mCP Servers: A feature that allows Augment Agent to extend its capabilities by plugging into APIs, SQL, CLI tools, and more.
• Context Limit: The amount of code an AI tool can understand and process at once.
• Indexing: The process of analyzing and organizing a codebase to enable faster and more efficient searching and understanding.

Augment Agent: A Major Upgrade to Augment Code

The video discusses the new release of Augment Agent, a significant upgrade to Augment Code, an AI agent designed for professional software engineers and large codebases. Augment Agent is positioned as a strong open-source competitor to tools like Cursor and Windsurf.

• Key Point: Augment Agent is an AI pair programmer that deeply understands your codebase and learns as you work.
• Comparison: It's similar to Windsurf's Cascade and Cursor's Composer.

Performance and Technology

Augment Agent has achieved top performance on the Sway Bench verifi test, demonstrating its capabilities in real-world software engineering tasks.

• Achievement: Augment Agent hit number one on the Sway Bench verifi test with a 65.4% success rate.
• Technology: It combines the Claude 3.7 Sonic model as the core driver and the OpenAI 01 model for assembling.
• Open Source: The entire Sway Bench pipeline, from dockerized agents to evaluation scripts, has been open-sourced.
• Focus: While Sway Bench focuses on Python bug fixes, Aget is moving towards faster, cheaper, and more scalable agents with fine-tuned models and deep IDE integrations.

Augment Agent in Action: Use Cases and Features

The video showcases Augment Agent's capabilities through various examples and features.

• Autonomous Execution: Augment Agent can autonomously execute commands, such as building applications using mCPs.
• Complex Task Completion: It can complete complex tasks from a single prompt, including planning changes, editing multiple files, running tests, and opening pull requests within the IDE.
• Example: The agent correctly handled the scene data structure with confidence scores on its first try.
• Visual Debugging: Augment Agent supports visual debugging, allowing users to drag in screenshots and have the agent identify UI issues (CSS layouts, logic) and suggest fixes.
• Streamlined Debugging: It streamlines debugging by running only the relevant tests.
• Persistent Memory: Augment Agent learns from your coding style, remembers past refactors, and adapts to your infrastructure and conventions.
• Benefit: The more you use it, the smarter it gets, eliminating the need to start from scratch.

Extending Capabilities with mCP Servers

Augment Agent can extend its capabilities through mCP servers, similar to Cline, Cursor, and Windsurf.

• Functionality: You can plug in APIs, SQL, CLI tools, and more through a simple settings.json file.
• Integration: It works seamlessly with tools like Superbase, Figma, and Cloudflare.

Handling Large Codebases

Augment Agent is capable of working with large codebases, overcoming the context limit limitations of tools like Cursor.

• Limitation of Cursor: Cursor's context limit is around 10K tokens.
• Augment Agent's Advantage: Augment Agent can handle projects with tens of thousands of lines effortlessly due to its fast indexing.

Getting Started with Augment Agent

The video provides a step-by-step guide on how to install and use Augment Agent.

1. Installation: Install the Augment Code extension in your IDE (e.g., Visual Studio Code).
2. Account Creation: Create a free account on the Augment Code website.
3. Extension Download: Download the extension for your IDE.
4. Access: Access the extension on the left-hand panel of your IDE.
5. Project Creation: Create a new project within the IDE.
6. Agent Mode: Select "Agent" in the chat interface.
7. Natural Language Instructions: Provide natural language instructions to the agent (e.g., "create a simple AI editor").
8. Autonomous Execution: The agent will execute terminal-based commands.
9. Context Addition: Add context to specific files or the entire workspace.
10. Approval: Approve the agent's actions (or set to auto-approve with caution).

Demonstration: Creating an AI Code Editor

The video demonstrates Augment Agent's ability to create an AI code editor autonomously.

• Result: Augment Agent created a functional editor capable of running scripts and changing formats.
• Key Factors: This was achieved through Augment Agent's prior context and its ability to autonomously execute commands within its own terminal.

Conclusion

Augment Agent is presented as a powerful and versatile AI pair programmer that offers a compelling alternative to existing tools like Cursor and Windsurf. Its key strengths include its performance on real-world tasks, persistent memory, ability to handle large codebases, and integration with various tools through mCP servers. The video emphasizes the free option and the performance benefits as reasons to try Augment Agent.