About Course
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:
- Role-playing: Assign specialized roles to agents
- Memory: Provide agents with short-term, long-term, and shared memory
- Tools: Assign pre-built and custom tools to each agent (e.g. for web search)
- Focus: Break down the tasks, goals, and tools and assign to multiple AI agents for better performance
- Guardrails: Effectively handle errors, hallucinations, and infinite loops
- 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:
- Tailor resumes and interview prep for job applications
- Research, write and edit technical articles
- Automate customer support inquiries
- Conduct customer outreach campaigns
- Plan and execute events
- 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.
What Will You Learn?
- Exceed the performance of prompting a single LLM by designing and prompting a team of AI agents through natural language.
- Use an open source library, crewAI, to automate repeatable, multi-step tasks like tailoring a resume to a job description; and automate business processes that are typically done by a group of people, like event planning.
- By creating a team of AI agents, you can define a specific role, goal, and backstory for each agent, which breaks down complex multi-step tasks and assigns them to agents that are customized to perform those tasks.







