Practical advice for implementing Multi Agent / AI Agents

practical skills and tangible tools to accelerate your career immediately

All Lightning Lessons

Practical advice for implementing Multi Agent / AI Agents

Hosted by Raj Singh Rikhy

Tue, Sep 24, 2024

4:00 PM UTC (30 minutes)

Virtual (Zoom)

Free to join

Learn directly from undefined

By continuing, you agree to Maven's Terms and Privacy Policy.

50 signed up

By continuing, you agree to Maven's Terms and Privacy Policy.

Invite your network

Tue, Sep 24, 2024

4:00 PM UTC (30 minutes)

Virtual (Zoom)

Free to join

50 signed up

Invite your network

What you'll learn

Grasp the Fundamentals of Multi-Agent Systems

Participants will understand the basic definition of MAS, how they differ from single-agent AI

Explore Key Design Principles

Students will gain an overview of the most important design considerations for MAS, including agent types and strategies

Get a Taste of Implementation

Attendees will be introduced to the practical steps involved in implementation and how to apply it to their product.

Why this topic matters

Multi-agent systems (MAS) are shaping the future of AI. Understanding them opens doors to cutting-edge careers in AI research, robotics, software engineering, and data science. You'll gain problem-solving skills applicable across fields and make impactful contributions to a technology that's changing the world.

You'll learn from

Raj Singh Rikhy

Principal Product Manager, Microsoft, Copilot Lead PM For Microsoft Fabric

Raj Singh Rikhy is a leader in AI and generative AI technologies with extensive experience at Microsoft, IBM, and Salesforce. Known for driving innovation and delivering results, Raj brings practical insights and hands-on expertise to his teaching.

At Microsoft, Raj led the development and implementation of advanced AI solutions for Azure Data, focusing on enhancing user engagement and integrating technologies across diverse teams. His strategic approach and ability to manage complex AI projects provide students with real-world perspectives on AI development.

Previously at