CrewAI

CrewAI is a popular framework for multi-agent systems. You define a "crew" of agents, each with a role, tools, and backstory. You give them a task. They collaborate to solve it.

Core concepts

• Agent, a role with goals, backstory, and tools
• Task, a unit of work assigned to agents
• Crew, a group of agents working together
• Process, how tasks are executed (sequential, hierarchical)

When CrewAI shines

• Prototyping multi-agent systems fast
• Role-based agent teams (researcher + writer + reviewer)
• Tasks that benefit from specialization

When it doesn't

• Single-agent tasks (overhead without benefit)
• Production systems needing tight control over cost and latency
• When the role-playing metaphor doesn't fit your problem

The role metaphor

CrewAI's central idea is treating agents as characters with backstories. This can help the LLM produce more in-character outputs, but can also add cost (longer prompts) without clear benefit. Measure impact on your use case.

Production considerations

• Observability is less mature than LangGraph
• Cost can be high with many agents spawned per task
• Good for prototypes; evaluate carefully for production at scale