Deep Dive into Trae: Can ByteDance's Free AI Coding IDE Replace Cursor?

What Is Trae: ByteDance's AI Coding IDE

ByteDance has launched an AI coding tool called Trae, built on the VS Code core, positioning it similarly to the well-known Cursor. Trae integrates AI capabilities such as intelligent Q&A, code completion, and code error correction. It supports switching between multiple large language models and is currently available for macOS and Windows (a Linux version is under development).

Technical Background: The VS Code Core and the Rise of AI IDEs

VS Code (Visual Studio Code) is an open-source code editor released by Microsoft in 2015, built on the Electron framework and developed in TypeScript. Its core strengths lie in its open extension API ecosystem and LSP (Language Server Protocol) standard, which enable third-party developers to build fully featured IDE products on top of it. AI coding tools like Cursor, Trae, and Windsurf all adopt a "Fork VS Code" strategy — directly reusing VS Code's editor core, plugin ecosystem, and UI framework, then layering AI capabilities on top. The benefits are obvious: development teams don't need to build editor infrastructure from scratch, and users get a familiar experience with full plugin ecosystem compatibility.

For developers in China, Trae's biggest appeal is that it's completely free and doesn't require a VPN, making it the lowest-barrier option for experiencing AI-assisted programming.

Industry Context: Cursor and the AI IDE Race

Cursor was launched by Anysphere in 2023 and quickly became the benchmark product in the AI coding tool space. Its core innovation lies in deeply integrating large language models into the code editing workflow, offering features like Copilot++ (intelligent completion), Chat (conversational coding), and Composer (multi-file editing). Cursor's paid subscription model (Pro version at approximately $20/month) and support for top-tier models like Claude and GPT-4 have helped it build a large user base among professional developers. The AI IDE market is currently highly competitive — besides Cursor, products like GitHub Copilot, JetBrains AI Assistant, and Windsurf (formerly Codeium) are all vying for market share. ByteDance's launch of Trae is essentially a play to capture the domestic developer market in this fast-growing space with a "free + locally accessible" strategy.

Installation and Configuration Guide

Download and Install

Visit the Trae official website and click the "Download Now" button on the right to get the installer. The installation process is the same as any standard software — a desktop shortcut will be created once installation is complete. The domestic version is called Trae-CN (Chinese version).

Initial Configuration Steps

The following steps need to be completed on first launch:

1. Log in: Enter your phone number and receive a verification code to log in
2. Choose a theme and language: Supports dark, light, deep blue, and other themes, which can be changed anytime via "File → Preferences → Settings"
3. Import settings: Supports importing existing configurations from VS Code or Cursor, making migration virtually effortless
4. Add command line: After installing the CLI tool, you can launch Trae directly from the terminal

If you've been using VS Code or Cursor, importing your configuration allows for a nearly seamless switch — plugins, keyboard shortcuts, and theme settings are all preserved.

Core Features Explained

Interface Layout

Trae's interface layout is highly consistent with VS Code, so existing users can get started with zero learning curve:

• Left sidebar: File explorer, search, source control (Git), WebView browser, debugging tools, extension marketplace
• Right sidebar: AI assistant panel with Chat and Builder modes
• Bottom panel: Terminal, output, problems, and other standard panels

The extension marketplace is compatible with the VS Code ecosystem, allowing you to install language plugins for Go, Java, and other languages, as well as utility tools like Code Runner.

Chat Mode: Conversational Coding Assistance

Chat mode is a conversational approach to coding assistance. You can ask questions or give instructions to the AI in natural language — for example, typing "write me a Go hello world" — and the AI will generate code through a chat interface.

The generated code is not automatically applied to your files. You need to manually click the "Apply" button, then choose "Accept All" or "Reject All." This mode is suitable for the following scenarios:

• When you need to verify code logic step by step
• When you want to selectively adopt AI suggestions
• When learning and understanding code implementation principles

Builder Mode: Automated Project Scaffolding

Builder mode is more automated. If you type "write me a Go hello world, name it hello.go," the AI will directly create the file in the left-side file tree and write the code — no extra apply button needed.

Technical Principles: The AI Agent Hierarchy Behind Chat and Builder

The fundamental difference between Chat mode and Builder mode reflects different levels of AI Agent autonomy. Chat mode follows a "human-AI collaboration" paradigm where the AI is only responsible for generating content, and all file system operations require manual user confirmation — adhering to the "Human-in-the-loop" design principle and reducing the risk of AI errors. Builder mode introduces a higher level of AI Agent capability — the model can not only generate code but also directly operate the file system through Tool Use / Function Calling, autonomously completing tasks such as creating files, writing content, and organizing directory structures. This Agent mode relies on the model's tool-calling capabilities, requiring the model to understand task objectives, plan execution steps, invoke appropriate tools, and handle execution results — representing a key direction in the evolution of AI coding tools.

This mode is ideal for quickly scaffolding project structures from scratch. The AI automatically creates files and organizes code; developers only need to confirm acceptance. It's highly efficient for prototyping and rapidly validating ideas.

Code Completion and Intelligent Error Correction

Trae offers completion features similar to Cursor Tab — the most frequently used capability in daily development:

• Real-time code suggestions: While writing code, the AI automatically provides completion suggestions; press Tab or Ctrl + → to accept
• Code snippet generation: Describe what you need in natural language (e.g., "write me a sum function"), and the AI automatically generates complete code snippets
• Intelligent error correction: When code errors are detected, the AI automatically provides fix suggestions — click apply to resolve

Technical Evolution: The History of AI Code Completion

AI code completion technology has evolved through three generations: rule engines, statistical language models, and large language models. Early IntelliSense (Microsoft) relied on AST (Abstract Syntax Tree) analysis and static type inference. GitHub Copilot introduced Transformer-based large models into the code completion scenario in 2021, pioneering the "Fill-in-the-Middle" approach.