Building Multi-Agent Systems with Claude: Making AI Collaborate

A single AI Agent can only do so much—write articles, tweak code. But when it comes to complex tasks, one Agent just can't handle it. So, can we get multiple AI Agents to work together like a team, each with their own role?

💡 What You Will Learn

A single AI Agent can only do so much—write articles, tweak code. But when it comes to complex tasks, one Agent just can't handle it. So, can we get multiple AI Agents to work together like a team, ea

import json
from anthropic import Anthropic

client = Anthropic(api_key="sk-ant-")

class Agent:
    def __init__(self, name, system_prompt, tools=None):
        self.name = name
        self.system_prompt = system_prompt
        self.tools = tools or []

    def run(self, task):
        response = client.messages.create(
            model="claude-sonnet-4-20250514",
            max_tokens=4096,
            system=self.system_prompt,
            messages=[{"role": "user", "content": task}],
            tools=self.tools if self.tools else None
        )
        return response.content[0].text

# DefineAgent
researcher = Agent(
    name="Researcher",
    system_prompt="Researcher"
)

writer = Agent(
    name="Writer",
    system_prompt="WriterResearcher"
)

reviewer = Agent(
    name="",
    system_prompt="Error"
)

# Workflow
research_result = researcher.run("20265AI Agent")
draft = writer.run(f"800{research_result}")
review = reviewer.run(f"{draft}")

print(f"Researcher{research_result[:100]}...")
print(f"{draft[:100]}...")
print(f"{review}")

def agent_conversation(agents, initial_task):
    context = initial_task
    for agent in agents:
        result = agent.run(context)
        context += f"\n\n{agent.name}\n{result}"
    return context

Summary