AI Developer Teams: How Trae Reshapes the Development Workflow

It's no longer unusual for AI to write code for you. But what if AI could help you assemble an efficient development team? Trae, a domestic AI programming tool, aims to do just that. Instead of switching between multiple tools for ideation, prototyping, and initial coding, Trae streamlines the entire process.

Transforming Ideas into Reality with AI Agents

Product Manager Agent: Defining Requirements

With Trae, a preliminary idea can be given to a Product Manager agent. This agent quickly understands the concept and generates a well-structured product requirements document (PRD) containing user stories and core functionalities. This document serves as a solid foundation for subsequent tasks.

UI/UX Agent: Designing the User Experience

The PRD automatically becomes the context for the UI/UX agent. With simple instructions, this agent can rapidly create interface layouts and core interaction flows. It outputs an interactive, high-fidelity prototype for clear visualization of the design.

Mobile Agent: Building the Application

The Mobile agent receives the prototype along with the defined design direction. It then builds a robust and scalable core code framework, allowing developers to quickly dive into detailed development.

The Power of AI Team Collaboration

This streamlined process demonstrates a seamless flow where different AI agents work together. Information is transferred efficiently, and developers can focus on guidance and decision-making. Trae's mechanism potentially allows one person to accomplish the work of an entire team, eliminating the chaos of switching between tools and synchronizing information. This fundamentally changes how developers work.

Understanding Trae's Architecture

Trae's Interface and Similarities to Cursor

Trae's client interface is clean and simple, sharing similarities with Cursor. It incorporates many of Cursor's strengths, such as deeply integrated AI capabilities, perfect compatibility with the VS Code ecosystem, and easy one-click configuration import. Trae stands on the shoulders of giants in AI-assisted coding.

Trae's Core Difference: The Agent Mechanism

Trae's true potential lies beyond being a mere Cursor upgrade. It's more accurately understood as Cursor plus an Agent mechanism. This Agent mechanism is its core weapon, distinguishing it from Cursor and other AI programming tools. This powerful, customizable, and manageable Agent system evolves Trae from a top-tier AI copilot into a platform for building, managing, and directing an AI development team. This is the underlying logic that enables the AI team collaboration scenario.

The Inner Workings of the Agent System

The "Brain" of the Agents: Access to Top-Tier Models

Trae's Agent system has access to leading programming models, including:

• Claude 3.5 Sonnet

• Claude 3.7 Sonnet

• Gemini 2.5 Pro

• GPT-4o

• GPT-4.1

• DeepSeek V3 and R1

It also supports adding custom large model APIs, such as OpenRouter, for greater flexibility.

Structuring and Utilizing Models: Encapsulation into Specialized Agents

Trae effectively organizes and utilizes these models by encapsulating them into agents with specific capabilities.

Defining an Agent's Capabilities

Think of an Agent in Trae as a person:

• The large model is its brain, responsible for thinking and analyzing.

• Context acts as its eyes and ears, helping it understand the needs.

• Built-in tools (MCP tools) are its hands and feet, enabling it to execute tasks, manipulate files, and call APIs.

• Specific Instructions defined in prompts are its soul. This determines the agent's identity, capabilities, behavior, and how it uses its tools.

The prompt allows a generic large model to be tuned into a domain expert, whether it's a product manager or a front-end engineer.

Creation, Storage, and Management of Agents

Trae enables you to create, save, and manage the agents you've personally trained. It's like having a library of experts that you can instantly call upon by using the @ symbol followed by the agent's name. This define-save-manage-@call loop is the cornerstone of Trae's efficient AI development team collaboration.

Simulating a Product Development Workflow with Trae

To illustrate how Trae's Agent teams work, let's simulate developing a mobile app to manage daily tasks for busy professionals. The roles are divided as follows:

• Director: guiding the process and making critical decisions.

• PM agent: Product Manager.

• UI/UX agent: Designer.

• Mobile agent: App developer.

Defining the Agents

First, the agents need to be defined. In the Trae client, you can define each agent with:

1. Name: A descriptive name for the agent.
2. Avatar: An optional image for visual identification.
3. Prompt: The core instruction defining the agent's role, tasks, workflow, and deliverables.
4. Tools: Selection of built-in or custom tools to enable the agent to perform its tasks.

Running the Product Development Workflow

1. Invoke the PM agent by typing @ followed by the agent's name.
2. Provide the initial product idea.
3. The PM agent analyzes the idea and creates a set of structured documents including the product requirements document, product roadmap, user story map, and product assessment framework.
4. The UI/UX agent is then invoked and provided with the PRD and user story map.
5. The UI/UX agent designs an interactive, high-fidelity prototype, generates the necessary HTML, CSS, and JS files, and starts a local server.
6. The Mobile agent is called upon with the prototype and begins implementing the app interface.
7. It creates the project structure, implements the interfaces, and ensures that the design specifications are followed.

Considerations for Effective AI Collaboration

Even with these advancements, human oversight remains critical.

Trae's Potential to Reshape Development

Trae isn't just an AI-powered code editor; it's a platform designed to enable users to define, manage, and direct teams of AI Agents. This role-based, collaboration-driven approach has the potential to revolutionize software development. It allows developers to shift their focus from tedious details to architecture, workflow guidance, and final decision-making, effectively becoming directors of their projects.