2025-04-25 –, Dynamicum
This hands-on tutorial will dive into the fundamentals of building multi-agent systems using the CrewAI Python library. Starting from the basics, we’ll cover key concepts, explore advanced features, and guide you step-by-step through building a complete application from scratch. We’ll discuss implementing guardrails, securing interactions, and preventing query injection vulnerabilities along the way.
Short Abstract
Agentic AI: Build a Multi-Agent Application with CrewAI
In this hands-on tutorial, we’ll dive into the fundamentals of building multi-agent systems using the CrewAI Python library. Starting from the basics, we’ll cover key concepts, explore advanced features, and guide you step-by-step through building a complete application from scratch. Along the way, we’ll discuss implementing guardrails, securing interactions, and preventing query injection vulnerabilities.
Detailed Description
This tutorial introduces Agentic AI—a design approach where multiple agents collaborate to solve complex tasks efficiently. Using the CrewAI Python library, we’ll start with the fundamentals and progressively move towards advanced concepts, focusing on practical implementation.
What We’ll Cover:
- Understanding Agentic AI: Core principles and why multi-agent systems are valuable.
- Getting Started with CrewAI: Setting up the library and creating simple agents.
- Advanced Agent Interactions: Defining workflows, collaboration patterns, and communication protocols.
- Building from Scratch: Step-by-step guide to developing a complete multi-agent application.
- Implementing Guardrails: Techniques to ensure agents operate within defined constraints.
- Preventing Query Injection: Strategies for securing agent queries against malicious inputs.
Why Attend?
By the end of this session, you’ll have hands-on experience building an agent-based application, understand how to implement security measures, and be equipped with best practices for maintaining control over agent behavior. Whether you're new to agentic systems or looking to refine your skills, this tutorial will provide both the theory and the practical insights needed to start building with CrewAI.
Prerequisites: Familiarity with Python and basic AI concepts will help you get the most out of this session.
Novice
Expected audience expertise: Python:Intermediate
Public link to supporting material, e.g. videos, Github, etc.:
Alessandro is a highly experienced data scientist with a Bachelor’s degree in computer science and a Master’s in data science. He has collaborated with various companies and organizations and currently holds the role of senior data scientist at logistics giant Kuehne+Nagel. Alessandro is particularly passionate about statistics and digital experimentation and has a strong track record of applying these skills to solve complex problems. He shares his knowledge regularly, speaking at events like the Data Innovation Summit and ODSC.