Multi-Agent AI Systems: Complete Beginner's Tutorial
Category: AI Coding Difficulty: Intermediate Updated: 2026-05-28
Complete beginner's guide to building multi-agent AI systems. Learn agent roles, task delegation, tool use, and build a working multi-agent research team with CrewAI.
What Are Multi-Agent Systems?
Multi-agent systems coordinate multiple AI agents to solve complex tasks. Each agent has a specialized role (researcher, writer, reviewer), uses specific tools, and collaborates to produce results no single agent could achieve alone. Think of it as a team of AI specialists working together.
Core Concepts
| Concept | Description | Example |
|---|---|---|
| Agent | An AI with a specific role and goal | ResearchAgent, WriterAgent |
| Task | A unit of work assigned to an agent | "Find latest AI news" |
| Tool | Capability an agent can use | Web search, calculator, code executor |
| Crew | Group of agents working together | Research team with 3 agents |
| Process | How agents collaborate (sequential/hierarchical) | Research → Write → Review |
Building a Research Team with CrewAI
pip install crewai crewai-tools
from crewai import Agent, Task, Crew, Process
from crewai_tools import SerperDevTool
# Define tools
search_tool = SerperDevTool()
# Define agents
researcher = Agent(
role="Senior Research Analyst",
goal="Find the latest developments in AI",
backstory="You are an expert researcher at a top tech firm",
tools=[search_tool],
verbose=True
)
writer = Agent(
role="Technical Writer",
goal="Create clear, engaging summaries of research findings",
backstory="You are a tech journalist who explains complex topics simply",
verbose=True
)
# Define tasks
research_task = Task(
description="Research the top 3 AI breakthroughs this month. Find specific companies, dates, and impact.",
expected_output="A detailed report with 3 breakthroughs, each with 3 bullet points of key details",
agent=researcher
)
writing_task = Task(
description="Turn the research into a 500-word blog post. Use simple language, add headings, and include a TL;DR.",
expected_output="A polished blog post in markdown format",
agent=writer
)
# Create the crew
crew = Crew(
agents=[researcher, writer],
tasks=[research_task, writing_task],
process=Process.sequential # Research first, then write
)
# Execute
result = crew.kickoff()
print(result) Popular Multi-Agent Frameworks
- CrewAI: Most beginner-friendly. Simple role/task/crew model. Great for getting started.
- AutoGen: Microsoft's framework. Powerful but more complex. Good for advanced patterns.
- LangGraph: LangChain's agent orchestration. Most flexible. Best for custom workflows.
- OpenAI Swarm: Lightweight experimental framework. Good for simple agent handoffs.