Tray IDE Review: AI Coding Tool Better Than Cursor or VS Code? A Comprehensive Test

The revolution of Artificial Intelligence in software development is no longer a futuristic promise; it is the current reality. Tools like Cursor and Windsurf have already changed how we interact with code, transforming natural language prompts into complex functionalities. Recently, a new player entered the ring, promising to raise the bar even higher: the Tray IDE. Rumors link it to the creators of TikTok, bringing with it a clean interface and a complete focus on generating applications based purely on natural language input.

In this detailed article, we will dive into the Tray IDE, testing its capabilities in real-time. We will go beyond simple “Hello World” examples, challenging the tool with a functional application—the Task Tracker—adding iterative complexity, and evaluating whether this new Chinese IDE truly has the power to dethrone established giants in AI-assisted development. If you are looking to maximize your productivity or are a beginner wanting to build your first app without diving into the complexities of VS Code, this guide is essential.

Getting Started with Tray IDE: Installation and Interface

The installation process for Tray IDE is surprisingly simple and straightforward, following the standard procedure for modern software on Windows or other platforms. After downloading the installer from the official website and logging in, the user is greeted by an interface that, at first glance, stands out from its more technically focused competitors.

User-Friendly Design vs. The Complexity of VS Code

While Cursor and Windsurf tend to replicate the robust, dense aesthetic of VS Code—which can be intimidating for those without prior programming experience—Tray IDE adopts a more minimalist approach. Its initial screen is clean and invites the user to start coding immediately. This design choice is crucial, as it lowers the barrier to entry for new developers or professionals from other fields who want to prototype quickly.

Tray divides its core functionality into two distinct environments, essential for efficient interaction with the AI:

• Chat: Dedicated to conversation with the AI. Here, the user can ask for suggestions, discuss application architecture, or request code tips. It is the ideal environment for planning and textual debugging.
• Builder: The heart of the IDE. This is where prompts are executed, and code is generated, edited, and previewed.

A highlight of Tray is its selection of language models. It offers immediate access to state-of-the-art models, such as Cloud 3.5 Sonnet and GPT-4o (the full version, not the mini). The inclusion of Cloud, renowned for its excellence in reasoning and complex coding, suggests that Tray is focused on delivering high-quality results, surpassing tools that might be limited to older or less capable models.

The Fire Test: Building a Simple Task Tracker

To test Tray’s foundational capabilities, we defined a simple yet functional prompt:

Create an application called Task Tracker that allows the user to add and remove tasks from a list. The app should be built using JavaScript with React.

Executing this prompt demonstrated the efficiency of the IDE’s workflow. After selecting a project folder, Tray takes control, automating steps that would be manual in a traditional environment:

1. Creating the Folder Structure (Based on Vite/React setup).
2. Installing Dependencies (npm install).
3. Generating the Initial Code (Components and State Logic).

The tool takes a few minutes to process and install the necessary packages, but the result is a functional Task Tracker, ready for use. What is truly impressive is the Integrated Preview functionality. Unlike many IDEs where you must run npm run dev and open localhost in an external browser, Tray displays the running application INSIDE its own interface. This drastically accelerates the feedback loop, allowing the developer to see changes in real-time without switching windows.

Practical Example of the Initial Result:

The generated application allowed us to successfully add tasks (“Take out the trash,” “Watch the SPFC game”) and remove them, confirming that the AI understood and executed the base prompt flawlessly.

Iteration and Refinement: Adding Complexity

The true test of an AI IDE is not its ability to create an application from scratch, but its capacity to iterate and refine existing code. Real-world applications are rarely built with a single prompt; they evolve. We therefore decided to add a crucial feature:

Implementing Task Completion Functionality

The new prompt requested the addition of a completion function, allowing users to mark tasks as done (in addition to just removing them). Using the Cloud model, in this case, was essential, as it handles the modification and integration of new logic into an established codebase better.

Tray’s AI processed the request and began rewriting or modifying the necessary components (likely changing the task object state to include an isCompleted boolean and applying visual styles, such as strikethrough text).

The Advantage of Tray’s Intelligent Debugging

During the implementation of the second feature, the generated application initially resulted in a “blank screen”—a common error in React development. This critical moment allowed us to evaluate Tray’s diagnostic capabilities.

Instead of just failing, Tray demonstrated notable superiority over its competitors. Upon informing the AI about the error (“Our application went blank upon loading”), the tool not only attempted to fix the issue but also analyzed the syntax error (identifying an export without the corresponding import) and, crucially, verified that the fix worked in the integrated browser.

Cursor, for instance, often makes an error and insists on it, requiring manual intervention or more specific correction prompts. Tray, by actively verifying functionality after correction, saves valuable developer time. This self-correction and verification capability is a significant differentiator in the workflow.

With the error resolved, the new functionality for marking tasks as complete was seamlessly integrated, proving the AI’s robustness in maintaining and expanding the code.

Raising the Bar: Priority and Date Management

To truly test the limits of the Tray IDE, we needed to introduce a feature requiring more complex data manipulation and advanced component integration. The new requirement was the addition of fields of priority, start date, and end date for each task.

This functionality requires the AI to:

1. Modify the data structure (the task object) to include new fields.
2. Create appropriate form components (priority selectors and date pickers/calendars).
3. Implement state logic to capture and persist this new data.

Tray demonstrated its proficiency by integrating a priority selector and a calendar component in a stylistically cohesive and functional manner. The application began to take shape, transforming from a simple To-Do List into a more robust task manager. The speed with which the AI handles the inclusion of external libraries (like a calendar component) and integrates them into the existing React code is impressive, showing that Tray not only generates code but understands the architecture of a modern application.

The Final Challenge: Design and Routing (Landing Page)

Up to this point, we focused on the internal logic of the Task Tracker. The final challenge was testing Tray’s ability to handle front-end architecture and design: the creation of a separate Landing Page and the implementation of Routing.

The goal was to turn the application into a Single Page Application (SPA) with distinct routes: / for the sales page and /app for the Task Tracker.

The prompt requested the creation of a sales landing page with:

• A Navbar (with a login button).
• Compelling sales copy about the Task Tracker.
• Call-to-action buttons.

For this to work, Tray needed to:

1. Create a new component (and potentially a new folder) for the Landing Page.
2. Identify and install the necessary routing library (react-router-dom).
3. Modify the main application file (usually main.jsx or app.jsx) to configure the routes.

This was the point where the IDE demonstrated the highest technical complexity. The AI recognized the need for react-router-dom, prompted the installation of the dependency, and restructured the application to support multiple routes. Although an initial import error occurred (the infamous fail to resolve Import react router Dom), Tray requested the missing library installation, quickly resolving the issue.

The Final Landing Page

The result was a surprisingly well-designed and sales-focused Landing Page:

Task Tracker: Simplify Your Productivity

With Task Tracker, organize, prioritize, and complete your tasks efficiently. Our intuitive and uncomplicated interface ensures you maintain total control.

• Priorities: Manage tasks with different urgency levels.
• Dates and Deadlines: Keep everything under control with start and end dates.

The page demonstrated that Tray not only generates functional code but is also capable of applying basic UX/UI and copywriting principles to its output.

Conclusion: Is Tray IDE the Future of AI Programming?

The Tray IDE establishes itself as a formidable competitor in the field of AI-assisted IDEs. Its greatest strength lies in combining a user-friendly interface with the power of the best language models (Cloud and GPT-4o).

Tray’s Strengths:

1. Interface and Accessibility: Much less intimidating than VS Code/Cursor, ideal for rapid prototyping and beginners.
2. Integrated Preview: The ability to run localhost within the IDE accelerates the development cycle.
3. Superior Debugging and Auto-Correction: The AI not only corrects errors but actively verifies that the application is running correctly after the fix, a feature that saves hours of work.
4. Iterative Capability: Handles the gradual addition of complexity excellently, from state logic to implementing routing and design.

While still in its early stages (with some delays in package installation and the lack of full translation into certain languages), Tray IDE is a tool that every developer, from junior to senior, should monitor. It proves that it is possible to build complex applications, such as a complete React application with routing and state logic, by prompting feature by feature.

Whether for quickly testing a SaaS idea or assisting in the development of large projects, Tray IDE offers a coding experience that is, in many respects, more fluid and intelligent than its direct competitors.