What's Actually Inside an AI Agent

A layer-by-layer look at what's inside an AI agent — the tool-calling loop, memory, and the production infrastructure that keeps it alive.

Tokens

How tokenization works, token limits, context windows, and their impact on AI agent behavior.

RAG (Retrieval-Augmented Generation)

How retrieval, embeddings, and generation combine to let an LLM answer questions about your private data without retraining it.

CAG (Cache-Augmented Generation)

Prefilling a knowledge base once and reusing its KV cache across questions — how cache-augmented generation works and when it beats RAG.