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Agentic Architecture: Build Intelligent AI Agent Systems
New
202 students

Agentic Architecture: Build Intelligent AI Agent Systems

Master Agentic AI, Autonomous Agents, Multi-Agent Systems, Planning, Memory, and Enterprise AI Architecture
Created byMeta Brains
Last updated 7/2026
English
English [Auto],

What you'll learn

  • Understand the fundamentals of Agentic AI and design autonomous AI systems using modern agent architectures.
  • Build AI agents with planning, reasoning, memory, tool usage, and multi-agent collaboration capabilities.
  • Design scalable agent workflows for task automation, decision-making, and enterprise AI applications.
  • Implement production-ready Agentic AI architectures using leading frameworks, LLMs, APIs, and best practices.

Course content

7 sections37 lectures3h 33m total length
  • What is Agentic Architecture5:31
  • Evolution from AI Assistants to Autonomous Agents5:39
  • Core Components of an Agentic System5:33

    Discover the core components of an agentic system, including reasoning models, instruction layers, tools, memory, and orchestration. Ensure governance, safety, and observability through guardrails and human-in-the-loop evaluation.

  • Enterprise Use Cases and Applications3:53
  • Understanding the Agent Execution Lifecycle6:26

    Understand the agent execution lifecycle from goal alignment and task decomposition to planning, tool use, execution, observation, evaluation, and iteration, ensuring reliable, traceable outputs.

  • Overview of Agent Frameworks and Ecosystems7:54

Requirements

  • Basic knowledge of Python and Large Language Models (LLMs) is helpful but not required. All Agentic AI concepts are explained step by step with practical examples.

Description

Disclaimer : This course contains the use of artificial intelligence.

Artificial Intelligence is entering a new era where systems can reason, plan, use tools, collaborate, and autonomously complete complex tasks. This is the foundation of Agentic AI, and understanding Agentic Architecture is becoming an essential skill for AI engineers and developers building next-generation intelligent applications.

In this comprehensive course, you'll learn how to design and build modern Agentic AI architectures that go far beyond traditional chatbot applications. You'll explore the core principles that enable AI agents to make decisions, execute multi-step workflows, interact with external tools, maintain memory, and collaborate with other agents to solve real-world problems.

Throughout the course, you'll gain a deep understanding of agent planning, reasoning strategies, memory architectures, tool integration, function calling, orchestration, autonomous workflows, multi-agent collaboration, task decomposition, and enterprise AI design patterns. You'll also learn architectural best practices for creating scalable, reliable, and production-ready agent systems.

This course focuses on practical concepts and real-world architecture rather than theory alone. You'll discover how modern AI assistants, research agents, coding agents, business automation systems, customer support agents, and enterprise AI platforms are designed using Agentic AI principles.

By the end of this course, you'll have the knowledge to design intelligent AI agent ecosystems capable of planning, reasoning, adapting, and interacting with external systems to accomplish sophisticated tasks.

Whether you're an AI engineer, Python developer, software architect, machine learning practitioner, automation specialist, or GenAI enthusiast, this course will equip you with the architectural skills needed to build autonomous AI systems that represent the future of artificial intelligence.

Who this course is for:

  • AI engineers, Python developers, machine learning practitioners, software architects, automation engineers, GenAI enthusiasts, and anyone interested in building intelligent autonomous AI agents and modern Agentic AI systems.