AG-2 in Practice #4 – Using Patterns to Structure Multi-Agent Workflows

Welcome back!

By now, you've created a multi-agent system where a Researcher passes info to a Writer. But what if you want to reuse that structure, or build more complex workflows with built-in logic?

That’s where AG-2 Patterns come in.

In this lesson, we’ll explore:

• What AG-2 Patterns are
• How to use a built-in pattern (TaskWithQA)
• How to create your own custom pattern

Let’s go!

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What Are Patterns?

Patterns are reusable orchestration templates. Instead of manually defining from → to rules between agents every time, you can:

• Use pre-built flows (like “Agent + Reviewer”)
• Create modular, readable code
• Focus on agent roles instead of plumbing

Think of Patterns as conversation blueprints.

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Step 1: Use a Built-in Pattern – TaskWithQA

This pattern follows a simple structure:

1. Agent A completes a task
2. Agent B (reviewer) checks the result
3. Optionally loops back if something needs to be redone

Let’s implement it.

from ag2 import Agent, Pattern, Conversation
import os

os.environ["OPENAI_API_KEY"] = "your-api-key-here"

# Task agent
writer = Agent(
    name="writer",
    llm="openai/gpt-4",
    system_message="Write a response based on the given prompt.",
)

# QA agent (Reviewer)
reviewer = Agent(
    name="reviewer",
    llm="openai/gpt-4",
    system_message="Review the response and provide feedback if needed. If it's good, approve it.",
)

# Use the built-in TaskWithQA pattern
pattern = Pattern.TaskWithQA(task_agent=writer, qa_agent=reviewer)

# Create a conversation using the pattern
conv = Conversation(pattern=pattern)
conv.send("Write a brief description of how photosynthesis works.")

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Step 2: Run It

python task_with_qa.py

Expected flow:

1. Writer generates a description
2. Reviewer reads and critiques (or approves)
3. Conversation ends or loops with edits if necessary

Simple, powerful, and structured!

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Step 3: Custom Patterns (Optional Preview)

You can also define your own custom pattern using Python classes, giving you full control over how agents interact — conditionally, sequentially, even with retries or external triggers.

We’ll cover that in detail in the next lesson.

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What’s Next?

In the next post, we’ll:

• Build a custom Pattern class
• Explore conditional logic, like “if reviewer rejects, retry”
• Use Tools + Patterns for real automation pipelines

Keep coding :)