Core Technology Guide to Agentic AI

Comprehensively covers the core technology stack and concepts needed to build Agentic AI.

The main content is as follows:

• LLM Fundamentals and Reasoning: How LLMs work, RL (Reinforcement Learning), and the model's Reasoning capabilities
• Memory Systems: Memory systems for agents, including RAG (Retrieval-Augmented Generation)
• Tools and Extensibility: Harness, MCP (Model Context Protocol), and Skills for performing specific tasks
• System Architecture: Multi-Agent Systems for performing complex tasks and evaluation methodologies