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Build a content creation team with specialized researchers and writers that collaborate to produce high-quality articles. This example demonstrates team coordination where agents work together on complex tasks.

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What You’ll Learn

By building this team, you’ll understand:
  • How to create specialized agents with distinct roles and capabilities
  • How teams coordinate multiple agents using the coordinate mode
  • How to combine web search tools with writing expertise for content creation
  • How to structure team instructions for collaborative workflows

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Use Cases

Build content creation platforms, automated journalism systems, research report generators, or marketing content pipelines.

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How It Works

The team uses coordinate mode to manage collaboration between specialized agents:
  1. Research: Researcher agent searches the web using DuckDuckGo for relevant information
  2. Coordinate: Team leader coordinates task distribution between members
  3. Write: Writer agent crafts clear, engaging content based on research findings
  4. Integrate: Team combines research and writing into cohesive articles
The team leader manages the workflow and ensures both agents contribute their expertise.

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Code

content_team.py
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.team import Team
from agno.tools.duckduckgo import DuckDuckGoTools

# Create individual specialized agents
researcher = Agent(
    name="Researcher",
    role="Expert at finding information",
    tools=[DuckDuckGoTools()],
    model=OpenAIChat(id="gpt-4o"),
)

writer = Agent(
    name="Writer",
    role="Expert at writing clear, engaging content",
    model=OpenAIChat(id="gpt-4o"),
)

# Create a team with these agents
content_team = Team(
    name="Content Team",
    members=[researcher, writer],
    instructions="You are a team of researchers and writers that work together to create high-quality content.",
    model=OpenAIChat(id="gpt-4o"),
    show_members_responses=True,
)

# Run the team with a task
content_team.print_response("Create a short article about quantum computing")

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What to Expect

The team will create an article by first researching the topic through web search, then writing content based on the findings. The researcher finds relevant information and sources, while the writer transforms this into engaging prose. The output shows responses from both team members so you can see how they collaborate. The final article combines accurate research with clear, professional writing.

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Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
2

Set your API key

export OPENAI_API_KEY=xxx
3

Install libraries

pip install -U agno openai ddgs
4

Run Team

python content_team.py

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Next Steps

  • Modify the task in print_response() to create different types of content
  • Add more specialized agents like editors or fact-checkers to the team
  • Adjust show_members_responses to control visibility of individual agent outputs
  • Explore Teams for advanced collaboration patterns