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Agentic System Design

Master agentic system design by learning to design advanced, adaptive AI systems with LLMs and real-world case studies, shaping smarter AI solutions for complex challenges.

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Overview

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This course offers a comprehensive overview for understanding, and designing AI agent systems powered by large language models (LLMs). We explore core AI agent components, delve into diverse architectural patterns, discuss critical safety measures, and examine real-world AI applications. In the process, we also learn to deal with associated challenges in agentic system design. You will study real-world examples, including Multi-Agent Conversational Recommender System (MACRS) and Nvidia’s Eureka learning agent. Drawing on insights from industry deployments and cutting-edge research, learners will gain the foundational knowledge needed to confidently start designing their agent-based systems. This course is ideal for anyone looking to build smarter, and more adaptive AI systems powered by LLMs.

This course offers a comprehensive overview for understanding, and designing AI agent systems powered by large language models (...Show More

WHAT YOU'LL LEARN

Define an AI agent and differentiate it from AI models

Identify and explain core AI agent components and memory systems

Differentiate and select agent orchestration patterns

Design and implement AI agent safety guardrails

Integrate human oversight into agent workflows

Analyze and apply strategies for agentic system challenges

Deconstruct real-world AI agent case studies

Design and architect adaptive, robust AI agent systems

Define an AI agent and differentiate it from AI models

Content

18 Lessons5 Quizzes

Agent Design Fundamentals

6 Lessons

This chapter lays the foundation for agentic system design, teaching AI agent components, architecture, orchestration, safety, and design challenges.

Introduction to AI Agents

Agent Architecture: Core Agent Components

Agent Architecture: Components Interaction and Agent Memory

Structuring Agent Behavior: Agent Orchestration Patterns

Building Trustworthy Agents: Guardrails and Human Oversight

Key Challenges and Design Strategies in Agentic AI Systems

Multi-Agent Conversational Recommender System (MACRS)

4 Lessons

This chapter explores MACRS, a multi-agent design pattern for conversational recommendations, covering planning, reflection, and superior performance.

Introduction to MACRS and the Design Challenge

MACRS Multi-Agent Act Planning Framework

MACRS User Feedback-Aware Reflection Mechanism

Evaluating MACRS: Performance and Insights

Nvidia Eureka Learning Agent

6 Lessons

This chapter explores Eureka, an LLM-powered meta-agent, for autonomous RL reward design, covering evolutionary search and human feedback.

Eureka: Automating Reward Design with Coding LLMs

Eureka’s Zero-Shot Reward Generation

Eureka’s Evolutionary Search for Iterative Improvement

Eureka's Reward Reflection Mechanism

Eureka from Human Feedback and Novel Reward Discovery

Evaluating Eureka: Performance and Insights

Applying Agentic Design Principles

1 Lessons

This chapter teaches applying agentic design principles to a case study, consolidating knowledge to confidently design adaptive AI agents.

Case Study: Designing a Smart Parking Agent System

Wrapping up

1 Lessons

This chapter consolidates agentic system design learnings on components, orchestration, and safety, to confidently design adaptive AI agents.

Final Thoughts

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Developed by MAANG Engineers

Every Educative lesson is designed by our in-house team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

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Hands-on Learning Powered by AI

See how Educative uses AI to make your learning more immersive than ever before.

Personalized Interview Prep

Skip the LeetCode grind with a custom roadmap that adapts to your goals. Hands-on practice for Coding Interviews, System Design, and more.

Mock Interviews

Test your skills in a simulated interview setting. Receive personalized feedback based on your performance. Available for Coding Interviews, System Design, and more.

AI Prompt

Build prompt engineering skills. Practice implementing AI-informed solutions.

Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

Explain with AI

Select any text within any Educative course, and get an instant explanation — without ever leaving your browser.

AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!

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