Agentic AI Engineering
Build production-grade AI agents from foundations to deployment
A technical workbook for engineers building production AI agents — covering LLM core, memory architectures, tool design, multi-agent systems, evaluation, and production operations.
Is this course right for you?
Build production-grade AI agents from foundations to deployment. A technical workbook for engineers building production AI agents — covering LLM core, memory architectures, tool design, multi-agent systems, evaluation, and production operations.
What you'll learn
Across 4 chapters, this course builds practical reasoning you can apply immediately:
- An AI agent is a cognitive loop that independently pursues goals using tools — build one only when complex decisions, brittle rules, or unstructured data make simpler approaches provably inadequate.
- The difference between a demo agent and a production agent is almost entirely prompt architecture — not model capability. Master the 7-section system prompt and model tiering.
- Production agents require a four-tier memory model — working, episodic, semantic, procedural — each with distinct infrastructure, retrieval strategy, and governance controls.
- Tools are an attack surface. Every production tool needs least-privilege security, a schema designed to make errors impossible, and a lifecycle governance policy.
Chapters
What Is an AI Agent? Anatomy, Types & When to Build One
An AI agent is a cognitive loop that independently pursues goals using tools — build one only when complex decisions, brittle rules, or unstructured data make simpler approaches provably inadequate.
The LLM Core — Model Selection, Prompts, Persona & Goals
The difference between a demo agent and a production agent is almost entirely prompt architecture — not model capability. Master the 7-section system prompt and model tiering.
Agent Memory — Short-Term, Long-Term & Retrieval Architectures
Production agents require a four-tier memory model — working, episodic, semantic, procedural — each with distinct infrastructure, retrieval strategy, and governance controls.
Tool Use — Design Principles, Integration Patterns & Security
Tools are an attack surface. Every production tool needs least-privilege security, a schema designed to make errors impossible, and a lifecycle governance policy.