Introduction
AI agents and agentic RAG for cybersecurity: Introduction
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1. Introduction to RAG in Cybersecurity
Learning objectives
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Introduction to retrieval-augmented generation (RAG)
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Exploring the GitHub repositories and additional resources
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Embeddings and embedding models
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Indexing techniques
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Vector databases
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Chunking strategies
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RAG vs. fine-tuning
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RAG, RAG fusion, and RAPTOR
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Running open-weight models with Ollama
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Exploring Open WebUI and other Ollama plugins
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Introduction to AI agents and agentic implementations
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Introduction to agentic RAG
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Introducing the Model Context Protocol (MCP)
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Introducing A2A and AGNTCY
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2. Introducing LangChain, LangGraph, and LlamaIndex
Learning objectives
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Introducing LangChain
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LangChain vs. LlamaIndex
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Prompt templates and system prompts
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Introducing LangSmith
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3. Prompt Engineering, Prompt Chains, and RAG Examples
Learning objectives
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Mastering prompt engineering
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Exploring basic prompt chain examples
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Creating prompt branching chains
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Exploring parallel prompt chains
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Creating a basic RAG application
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Creating a complete RAG application
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4. AI Agents and Agentic Frameworks
Learning objectives
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Introduction to AI agent frameworks
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Surveying CrewAI
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Introducing LangGraph
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Exploring examples of LangGraph in action
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Exploring an example of agents with MCP servers
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Securing agentic implementations
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Conclusion
AI agents and agentic RAG for cybersecurity: Summary
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