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Multi-Agent Teams

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What is Multi-Agent Team?

In complex projects, a single AI might not handle everything well. Multi-Agent Team lets you create specialized AI agents, each handling different tasks:

Researcher

Responsible for searching and organizing information

Designer

Responsible for visual design and creativity

Developer

Responsible for writing and optimizing code

Tester

Responsible for quality inspection and testing

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Enable Agent Teams

Click the model selector in the bottom-right of the chat input (it shows the current model name, like “Sonnet 4.6”). At the bottom of that menu, toggle Agent teams on. You can also enable it from Settings → Experimental → Agent Teams. Once on, start a conversation and mention that you want a team — Happycapy will set one up.

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How to Use Multi-Agent Teams

Mention in the conversation that you need teamwork, and Happycapy will create and manage an Agent Team: 
I need to build a complete website, including frontend, backend, and database design.
Please assemble a team to complete this project.
Happycapy will:
  1. Create the right Agent roles based on your project needs
  2. Assign tasks to each Agent with clear responsibilities
  3. Coordinate collaboration among agents for efficient teamwork
  4. Integrate all results into a final deliverable

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When to Use Multi-Agent Teams

Multi-Agent Teams work well for complex projects that need diverse expertise:
Projects requiring multiple areas of expertise (frontend, backend, database, DevOps)
Research + Writing + Design workflows
Collection + Cleaning + Analysis + Visualization pipelines
Planning + Design + Copywriting + Execution workflows

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Practical Case: Pomodoro App Development

Execution time: 3-4 minutes | Difficulty: ⭐⭐⭐⭐Before: requirements analysis + UI design + frontend development + testing = a few days of workNow: one conversation, team automatically divides the work, complete application delivered in 4 minutes

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Example Prompt

Please assemble a development team to help me build a Pomodoro app:

Product requirements:
- 25-minute work timer (pause/reset supported)
- 5-minute break reminder (sound + visual cue)
- Count completed Pomodoros for today
- Clean and modern UI design (gradients, modern style)
- Responsive layout (mobile and desktop)
- Local storage (data persists after refresh)

Suggested team roles:
1. Product Manager: define feature logic and user flows
2. UI Designer: design UI and interaction plan
3. Frontend Engineer: implement features (HTML/CSS/JavaScript)
4. QA Engineer: verify functional completeness

Please complete this collaboratively and deliver a ready-to-use web app!

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What Happens

You will see team members working in parallel:
Product Manager
  • Planning features
  • Defining user flows
  • Setting requirements
UI Designer
  • Creating mockups
  • Designing interactions
  • Choosing colors & styles
Frontend Engineer
  • Writing HTML/CSS/JS
  • Implementing features
  • Setting up local storage
QA Engineer
  • Testing functionality
  • Verifying requirements
  • Reporting issues
The whole process looks like real team collaboration, but runs several times faster. Takes only 3-4 minutes.
You’ll get a complete web application ready to use. Complete code, nice interface, smooth animations, reliable functions.

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Advanced Features

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Flexible Model Selection

Different agents in the team can use different models so each one performs best for its role. Available models: Opus 4.6, Sonnet 4.6, Haiku 4.5, MiniMax M2.7.

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Automatic Coordination

Agents automatically:
  • Share information between team members
  • Resolve dependencies and blockers
  • Coordinate timing and sequencing
  • Integrate their work into a cohesive whole

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Cost Considerations

Multi-agent team collaboration is efficient, but uses more tokens.If you use teams frequently, consider the Max subscription for significantly more tokens than Pro, so you can focus on creating without watching usage.

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Tips for Success

Be Specific

Clearly define the project requirements and desired outcomes

Suggest Roles

Recommend team roles based on your project needs

Define Deliverables

Specify what final outputs you expect

Iterate

Review results and ask for refinements if needed

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Next Steps

Try Multi-Agent Teams

Enable experimental features and start building with collaborative AI teams