CrewAI

CrewAI is a framework for building multi-agent AI systems where each agent has a defined role, goal, backstory, and set of tools, collaborating to complete complex tasks autonomously. It brings a role-playing paradigm to agentic AI.

Key use cases include:

• Research automation — teams of agents that search, analyze, and synthesize information
• Content pipelines — writer, editor, and fact-checker agents collaborating on content
• Business process automation — agents handling customer support, data entry, or lead qualification
• Code review workflows — agents that write, review, and test code
• Sales and marketing — agents for lead enrichment, email drafting, and campaign planning

CrewAI is popular with developers building practical AI automation for business workflows. Its role-based paradigm is intuitive — you describe each agent as you would a team member (role, goals, constraints), and the framework handles inter-agent communication and task delegation.

The framework includes CrewAI Tools (web search, file I/O, scraping) and integrates with LangChain tools for extended capabilities.

1. Install CrewAI:

   pip install crewai crewai-tools

2. Set your LLM provider key:

   export OPENAI_API_KEY='sk-...'

3. Build your first crew:

   from crewai import Agent, Task, Crew
   
   researcher = Agent(
       role='Researcher',
       goal='Find accurate information',
       backstory='Expert research analyst'
   )
   task = Task(
       description='Research the latest AI trends',
       agent=researcher,
       expected_output='A summary of key AI trends'
   )
   crew = Crew(agents=[researcher], tasks=[task])
   result = crew.kickoff()

4. Explore docs.crewai.com for advanced patterns like hierarchical crews and custom tools.

Pricing: CrewAI is free and open source. CrewAI Enterprise offers hosted deployment, monitoring, and team features. You pay only for the underlying LLM API calls your agents consume.