Planned lesson
AI Agents Explained: Tools, Memory, RAG, and Guardrails
Understand the components that turn model output into bounded action
A planned lesson describing agent loops, tool use, memory, retrieval-augmented generation, and guardrails as distinct system responsibilities.
Learning objectives
- Distinguish an agent loop from a single language-model request.
- Compare the roles of tools, working memory, durable memory, and retrieval-augmented generation.
- Identify where permissions, validation, human review, and guardrails constrain agent behavior.
Educational notice
For educational purposes only. Agent designs require context-specific security, privacy, legal, and human-oversight review.