CrewAI for multi-agent teams in Agentic AI

Introduction

CrewAI helps multiple AI agents work together like a team to solve problems faster and better.

When you want different AI agents to share tasks and help each other.

When solving complex problems that need many skills or viewpoints.

When you want to improve AI decision-making by teamwork.

When building AI systems that mimic how people collaborate in groups.

Syntax

Agentic AI

crew = CrewAI(agents=[agent1, agent2, agent3])
crew.assign_task('Collect data')
results = crew.run()
print(results)

Each agent in the crew can have different skills or roles.

The crew manages communication and task sharing automatically.

Examples

Two agents work together: one collects data, the other analyzes it.

Agentic AI

crew = CrewAI(agents=[DataAgent(), AnalysisAgent()])
crew.assign_task('Analyze sales data')
output = crew.run()

Three agents collaborate to plan an event by sharing subtasks.

Agentic AI

crew = CrewAI(agents=[AgentA(), AgentB(), AgentC()])
crew.assign_task('Plan event')
results = crew.run()

Sample Model

This simple example shows two agents in a crew working on the same task and returning their results.

Agentic AI

class Agent:
    def __init__(self, name):
        self.name = name
    def perform(self, task):
        return f'{self.name} completed {task}'

class CrewAI:
    def __init__(self, agents):
        self.agents = agents
        self.task = ''
    def assign_task(self, task):
        self.task = task
    def run(self):
        results = []
        for agent in self.agents:
            result = agent.perform(self.task)
            results.append(result)
        return results

# Create agents
agent1 = Agent('Agent 1')
agent2 = Agent('Agent 2')

# Create crew with agents
crew = CrewAI(agents=[agent1, agent2])

# Assign a task to the crew
crew.assign_task('data collection')

# Run the crew and get results
output = crew.run()

print(output)

Important Notes

CrewAI helps break big tasks into smaller parts shared by agents.

Good communication between agents is key for teamwork success.

You can customize agents with different skills for better results.

Summary

CrewAI lets multiple AI agents work together as a team.

It improves problem-solving by sharing tasks and ideas.

You create a crew, assign tasks, and get combined results.

Practice

1. What is the main purpose of CrewAI in multi-agent teams?

easy

A. To replace human workers completely

B. To train a single AI model faster

C. To let multiple AI agents work together as a team

D. To store large amounts of data

Solution

1. Step 1: Understand CrewAI's role

   CrewAI is designed to enable multiple AI agents to collaborate.

2. Step 2: Compare options

   Only To let multiple AI agents work together as a team correctly describes teamwork among AI agents, while others describe unrelated tasks.

3. Final Answer:

   To let multiple AI agents work together as a team -> Option C

4. Quick Check:

   CrewAI teamwork = To let multiple AI agents work together as a team [OK]

Hint: CrewAI means teamwork among AI agents [OK]

Common Mistakes:

• Thinking CrewAI trains a single model
• Confusing data storage with teamwork
• Assuming CrewAI replaces humans fully

2. Which of the following is the correct way to create a CrewAI team in Python?

easy

A. team = CrewAI.create(['agent1', 'agent2'])

B. crew = create_team(CrewAI, ['agent1', 'agent2'])

C. team = CrewAI(['agent1', 'agent2']).create()

D. crew = CrewAI.create_team(['agent1', 'agent2'])

Solution

1. Step 1: Recall CrewAI team creation syntax

   The correct method is calling create_team on CrewAI with a list of agents.

2. Step 2: Check each option

   Only crew = CrewAI.create_team(['agent1', 'agent2']) matches the correct syntax; others misuse method names or order.

3. Final Answer:

   crew = CrewAI.create_team(['agent1', 'agent2']) -> Option D

4. Quick Check:

   Correct method call = crew = CrewAI.create_team(['agent1', 'agent2']) [OK]

Hint: Use CrewAI.create_team with agent list [OK]

Common Mistakes:

• Swapping method and class names
• Using wrong method like create() or create()
• Passing agents incorrectly

3. Given this code snippet, what will be the output?

crew = CrewAI.create_team(['agentA', 'agentB'])
results = crew.assign_tasks(['task1', 'task2'])
print(results)

medium

A. {'agentA': 'task1 done', 'agentB': 'task2 done'}

B. ['task1 done', 'task2 done']

C. {'task1': 'agentA done', 'task2': 'agentB done'}

D. Error: assign_tasks method not found

Solution

1. Step 1: Understand assign_tasks behavior

   assign_tasks assigns each task to an agent and returns a dictionary mapping agents to task results.

2. Step 2: Match output format

   {'agentA': 'task1 done', 'agentB': 'task2 done'} shows agent-task mapping with completion messages, matching expected output.

3. Final Answer:

   {'agentA': 'task1 done', 'agentB': 'task2 done'} -> Option A

4. Quick Check:

   Agent-task result dict = {'agentA': 'task1 done', 'agentB': 'task2 done'} [OK]

Hint: assign_tasks returns agent-task result dictionary [OK]

Common Mistakes:

• Expecting list instead of dict
• Swapping keys and values in output
• Assuming method does not exist

4. Identify the error in this CrewAI code snippet:

crew = CrewAI.create_team(['agent1', 'agent2'])
results = crew.assign_task(['task1', 'task2'])
print(results)

medium

A. Method name should be assign_tasks, not assign_task

B. Agent list should be a string, not a list

C. create_team does not accept a list argument

D. print cannot display results dictionary

Solution

1. Step 1: Check method names

   The correct method to assign multiple tasks is assign_tasks, not assign_task.

2. Step 2: Validate other parts

   Agent list as a list is correct; create_team accepts list; print can display dict.

3. Final Answer:

   Method name should be assign_tasks, not assign_task -> Option A

4. Quick Check:

   Correct method name = Method name should be assign_tasks, not assign_task [OK]

Hint: Check method names carefully for plurals [OK]

Common Mistakes:

• Using singular assign_task instead of assign_tasks
• Thinking agent list must be string
• Assuming print can't show dict

5. You want to create a CrewAI team where agents share partial results to improve overall problem-solving. Which CrewAI feature should you use?

hard

A. Task delegation without communication

B. Shared memory for agents to exchange information

C. Single-agent mode for faster processing

D. Random task assignment without feedback

Solution

1. Step 1: Understand collaboration needs

   Sharing partial results requires agents to communicate and exchange information.

2. Step 2: Identify CrewAI feature

   Shared memory allows agents to share data and improve teamwork effectively.

3. Step 3: Eliminate wrong options

   Options A, C, and D do not support communication or collaboration.

4. Final Answer:

   Shared memory for agents to exchange information -> Option B

5. Quick Check:

   Agent communication = Shared memory = Shared memory for agents to exchange information [OK]

Hint: Use shared memory for agent collaboration [OK]

Common Mistakes:

• Ignoring communication needs
• Choosing single-agent mode mistakenly
• Assuming random assignment helps collaboration