Agentic AI Crash Course

• Part 01

  01

  What Are Agents Anyway?

  Understanding the fundamental differences between generative AI and agentic AI, core capabilities, and real-world applications.

• Part 02

  02

  The 4 Types of Agentic Systems (and When to Use What)

  Explore workflow agents, semi-autonomous agents, rule-based systems, and autonomous agents with decision frameworks.

• Part 03

  03

  What Are Tools in AI?

  Learn about AI model integration, API connections, tool ecosystems, and custom tool development.

• Part 04

  04

  What Is RAG, and What Does It Mean to Make It Agentic?

  Deep dive into Retrieval-Augmented Generation, traditional vs agentic RAG, and implementation patterns.

• Part 05

  05

  What Is MCP and Why Should You Care?

  Understanding Model Context Protocol, AI model integration strategies, and enterprise implementation.

• Part 06

  06

  Planning in Agents + Reasoning Models

  Agent planning strategies, reasoning model integration, and advanced reasoning capabilities.

• Part 07

  07

  Memory in Agents

  Short-term and long-term memory systems, architecture patterns, and performance optimization.

• Part 08

  08

  Multi-Agent Systems

  Multi-agent architecture, hierarchical patterns, coordination strategies, and scalability considerations.

• Part 09

  09

  Real-World Agentic Systems (Under the Hood)

  Case studies of production systems, architecture patterns, and lessons from enterprise implementations.

• Part 10

  10

  AI Agent Lessons and What's Ahead

  Latest developments, future trends, industry roadmap, and emerging technologies in agentic AI.