Build AI Agents with CrewAI: Complete Guide

In this video, Maya Akim demonstrates how to use CrewAI to build a team of AI agents that can analyze and refine business ideas, access real-world data, and perform tasks using local models. Maya explains the concepts of system one and system two thinking, highlighting the limitations of current large language models (LLMs) and how CrewAI can simulate rational thinking through agent collaboration. The video provides a step-by-step guide to setting up a virtual environment, installing CrewAI, and defining agents and tasks. Maya showcases two examples: a startup analysis with three agents (marketer, technologist, and business development expert) and a detailed report generation using LangChain tools and custom tools for accessing real-world data like Google searches and Reddit. The video also covers the use of local models to avoid API costs and maintain privacy, testing 13 open-source models and identifying the best-performing ones. Maya emphasizes the importance of choosing the right models and provides insights into the performance of various local models. The video concludes with an invitation to explore CrewAI and share experiences.