CrewAI / AutoGen – Multi-Agent Systems in Python (2026)

Build intelligent AI teams that collaborate, research, write, and execute tasks — using CrewAI or AutoGen.

CrewAI vs AutoGen – Quick Comparison (2026)

CrewAI – Simple Multi-Agent Team

from crewai import Agent, Task, Crew

# Define agents
researcher = Agent(
    role='Senior Researcher',
    goal='Find latest AI trends 2026',
    backstory='Expert in emerging tech',
    verbose=True,
    allow_delegation=False
)

writer = Agent(
    role='Content Writer',
    goal='Write engaging articles',
    backstory='Tech journalist',
    verbose=True
)

# Tasks
research_task = Task(
    description='Research AI agents in 2026',
    agent=researcher
)

write_task = Task(
    description='Write 1000-word article based on research',
    agent=writer
)

# Create crew
crew = Crew(
    agents=[researcher, writer],
    tasks=[research_task, write_task],
    verbose=2
)

result = crew.kickoff()
print(result)
        

AutoGen – Conversational Multi-Agent

from autogen import AssistantAgent, UserProxyAgent

config_list = [{"model": "gpt-4o", "api_key": "your_openai_key"}]

user_proxy = UserProxyAgent(
    name="User",
    human_input_mode="NEVER",
    max_consecutive_auto_reply=10
)

assistant = AssistantAgent(
    name="Assistant",
    llm_config={"config_list": config_list}
)

user_proxy.initiate_chat(
    assistant,
    message="Write a short story about AI in 2026"
)
        

When to Choose CrewAI vs AutoGen

• CrewAI: Quick task automation, hierarchical teams, simple setup
• AutoGen: Complex conversations, group chat, research-grade agents