AgenticOps 101

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About Course

AgenticOps 101: Building Intelligent AI Agent Systems

Move beyond simple chatbots and learn how to design, build, and operate production-ready AI agents.

AgenticOps 101 is a beginner-friendly, hands-on course that introduces the core concepts behind modern AI agent systems. You’ll understand why traditional LLMs fall short, how Retrieval-Augmented Generation (RAG) enhances AI applications, and how autonomous agents differ from conventional retrieval systems.

Throughout the course, you’ll explore how AI agents remember information across interactions using modern memory architectures, and learn why observability is essential for monitoring, debugging, and improving AI systems in production.

By the end of this course, you’ll have a solid understanding of the fundamental building blocks required to create reliable, context-aware, and production-ready AI agents.

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What Will You Learn?

  • Understand why Large Language Models (LLMs) need Retrieval-Augmented Generation (RAG)
  • Learn how RAG overcomes knowledge limitations in AI systems
  • Compare traditional RAG with Agentic RAG architectures
  • Understand how AI agents reason, plan, and use tools
  • Explore multi-layer memory systems for intelligent agents
  • Learn the purpose of short-term, semantic, episodic, and procedural memory
  • Understand the importance of observability in AI applications
  • Learn tracing, metrics, logging, and debugging techniques for AI agents
  • Gain a strong foundation for building production-ready AI agent systems

Course Content

AgenticOps 101

  • AgenticOps 101
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