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content/blog/part-5-agentic-ai-team-coordination-mode-in-action.md

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+---
+title: "Part 5: Agentic AI: Team coordination mode in action"
+date: 2025-07-21T07:24:24.522Z
+author: Dinesh R Singh
+authorimage: /img/dinesh-192-192.jpg
+disable: false
+tags:
+  - LLM
+  - Generative AI
+  - Agentic AI
+  - AI Agents
+---
+<style>
+li {
+   font-size: 27px;
+   line-height: 33px;
+   max-width: none;
+}
+</style>
+
+One of the most transformative patterns in Agentic AI is team-based orchestration — a collaborative approach where specialized **agents work together to fulfill complex goals**. In this edition, we explore coordinate mode using the AGNO framework — a design where a team manager delegates, supervises, and integrates the contributions of each agent.
+
+[Inspired by my Medium post.](https://dineshr1493.medium.com/all-you-need-to-know-about-the-evolution-of-generative-ai-to-agentic-ai-part-5-agentic-ai-a-2d6651c9cc5c)
+
+<center><img src="/img/screenshot-2025-07-21-at-12.57.22 pm.png" width="600" height="550" alt="LLM Mode" title="LLM Mode"></center>
+
+## What are agentic AI teams?
+
+An agentic team is a structured collection of AI agents, each performing a specific role with autonomy and tool access. Teams can include roles like:
+
+* Researcher: Finds and filters relevant data
+* Writer: Synthesizes content with tone and structure
+* Translator: Converts content across languages
+* Planner: Organizes execution based on goals
+
+### In Coordinate Mode:
+
+* A team manager Agent directs the flow of tasks
+* Individual agents handle sub-tasks independently
+* Final results are reviewed, refined, and unified by the manager
+
+## AGNO Framework: Coordinating a multi-agent content team
+
+Let’s examine a professional-grade configuration of a New York Times-style editorial team, where search, writing, and editorial review are handled by distinct agents.
+
+### Imports
+
+```python
+from agno.agent import Agent
+from agno.models.openai import OpenAIChat
+from agno.team.team import Team
+from agno.tools.search import DuckDuckGoTools
+from agno.tools.read import Newspaper4kTools
+```
+
+### Searcher agent
+
+```python
+searcher = Agent(
+    name="Searcher",
+    role="Searches the top URLs for a topic",
+    instructions=[
+        "Generate 3 search terms for a topic.",
+        "Search the web and return 10 high-quality, relevant URLs.",
+        "Prioritize credible sources, suitable for the New York Times."
+    ],
+    tools=[DuckDuckGoTools()],
+    add_datetime_to_instructions=True,
+)
+```
+
+### Writer agent
+
+```python
+writer = Agent(
+    name="Writer",
+    role="Writes a high-quality article",
+    description="Senior NYT writer tasked with long-form editorial content.",
+    instructions=[
+        "Read all articles using `read_article`.",
+        "Write a structured, engaging article of at least 15 paragraphs.",
+        "Support arguments with factual citations and ensure clarity.",
+        "Never fabricate facts or plagiarize content."
+    ],
+    tools=[Newspaper4kTools()],
+    add_datetime_to_instructions=True,
+)
+```
+
+### Editor team (Manager agent in Coordinate Mode)
+
+```python
+editor = Team(
+    name="Editor",
+    mode="coordinate",
+    model=OpenAIChat("gpt-4o"),
+    members=[searcher, writer],
+    description="You are a senior NYT editor coordinating the team.",
+    instructions=[
+        "Delegate research to the search agent.",
+        "Delegate drafting to the writer.",
+        "Review, proofread, and enhance the final article.",
+        "Maintain NYT-level quality, structure, and tone."
+    ],
+    add_datetime_to_instructions=True,
+    send_team_context_to_members=True,
+    show_members_responses=True,
+    markdown=True,
+)
+```
+
+### Running the team
+
+```python
+Method 1: Print output directly
+editor.print_response("Write an article about latest developments in AI.")
+
+Method 2: Get raw result
+response = editor.run("Write an article about latest developments in AI.")
+```
+
+### Key parameters explained
+
+<table>
+  <thead style="background-color:#f2f2f2">
+    <tr>
+      <th>Parameter</th>
+      <th>Purpose</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td><code>mode="coordinate"</code></td>
+      <td>Enables structured delegation and task flow</td>
+    </tr>
+    <tr>
+      <td><code>members=\\\\\[...]</code></td>
+      <td>Assigns role-specific agents</td>
+    </tr>
+    <tr>
+      <td><code>send_team_context_to_members</code></td>
+      <td>Shares global task context with all agents</td>
+    </tr>
+    <tr>
+      <td><code>show_members_responses=True</code></td>
+      <td>Displays each member's intermediate output</td>
+    </tr>
+    <tr>
+      <td><code>add_datetime_to_instructions</code></td>
+      <td>Contextualizes outputs with current date/time</td>
+    </tr>
+  </tbody>
+</table>
+
+## Pro tip: Define success criteria
+
+Adding success criteria helps agents align their efforts with measurable outcomes.
+
+```python
+strategy_team = Team(
+    members=[market_analyst, competitive_analyst, strategic_planner],
+    mode="coordinate",
+    name="Strategy Team",
+    description="A team that develops strategic recommendations",
+    success_criteria="Produce actionable strategic recommendations supported by market and competitive analysis",
+)
+response = strategy_team.run(
+    "Develop a market entry strategy for our new AI-powered healthcare product"
+)
+```
+
+This ensures agents not only act — but act with strategic purpose and direction.
+
+<center><img src="/img/screenshot-2025-07-21-at-12.57.44 pm.png" width="600" height="550" alt="Agentic AI Parameters" title="Agentic AI Parameters"></center>
+
+## Conclusion
+
+Coordinate Mode in Agentic AI exemplifies intelligent task distribution, where specialized agents work under centralized leadership to deliver complex, high-quality outputs. The AGNO framework simplifies this orchestration through agent roles, tool integration, and goal alignment **—** **enabling scalable, auditable AI workflows.**
+
+From editorial pipelines to business strategy engines, multi-agent coordination is redefining how work gets done **— autonomously, intelligently, and collaboratively.**