Optimizing and Operationalizing Generative AI

Introduction

This lesson closes AI-103's largest domain, Implement generative AI and agentic solutions (30–35%). Building a working prompt, a RAG pipeline or an agent is only the beginning. The official skills for this part of the exam ask whether you can make a solution better, cheaper, faster and observable once real users arrive: prompt engineering and model parameters; reflection, chain-of-thought evaluation and self-critique loops; tracing, token analytics, safety signals and latency; and orchestrating multiple models, including hybrid designs that combine an LLM with a rules engine.