3. Build an Agent with Memory

Agentic AI: Projects & Engineering Mastery

A book-shaped table of contents for Agentic AI: Projects & Engineering Mastery: hands-on practitioner builds, Principal/Staff-level technical leadership, and the lookup appendices and vendor/framework reference notes for the whole series. Book 6 of the AI Systems Engineering series.

7.1 Connecting Agents to Grafana

Wiring an agent's tool layer to Grafana's HTTP API and Prometheus datasource — authentication, the metrics query surface, and the error handling an agent needs when a query fails mid-investigation.

4.1 Building an Operational Knowledge Base

Turning runbooks, playbooks, architecture documents, incident reports, and best practices into a RAG corpus an investigation agent can actually retrieve from.

4.2 Retrieval-Augmented Generation (RAG)

Why RAG exists, document processing and chunking strategy, embeddings, vector database choice, and the retrieval pipeline that feeds relevant context into an agent's prompt.

1.1 Setting Up the Development Environment

Python project setup, virtual environments, and installing the OpenAI SDK, LangChain, and LangGraph so the rest of the book's code samples run without friction.