Multi AI Agent Systems with crewAI

Learn key principles of designing effective AI agents, and organizing a team of AI agents to perform complex, multi-step tasks. Apply these concepts to automate 6 common business processes. Learn from João Moura, founder and CEO of crewAI, and explore key components of multi-agent systems: 1. Role-playing: Assign specialized roles to agents 2. Memory: Provide agents with short-term, long-term, and shared memory 3. Tools: Assign pre-built and custom tools to each agent (e.g. for web search) 4. Focus: Break down the tasks, goals, and tools and assign to multiple AI agents for better performance 5. Guardrails: Effectively handle errors, hallucinations, and infinite loops 6. Cooperation: Perform tasks in series, in parallel, and hierarchically Throughout the course, you’ll work with crewAI, an open source library designed for building multi-agent systems. You’ll learn to build agent crews that execute common business processes, such as: 1. Tailor resumes and interview prep for job applications 2. Research, write and edit technical articles 3. Automate customer support inquiries 4. Conduct customer outreach campaigns 5. Plan and execute events 6. Perform financial analysis By the end of the course, you will have designed several multi-agent systems to assist you in common business processes, and also studied the key principles of AI agent systems.