AI Application Engineering (RAG and Agents)
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Stage One — What These Systems Can and Cannot Do
The Component You Are Building Around
Preview
Choosing a Model and Where to Run It
Deciding Whether the Model Belongs Here At All
3 lessons
Stage Two — Prompting and Structured Output
Prompt Construction That Holds Up
Structured Output and Defensive Parsing
Decomposition and Chaining
3 lessons
Stage Three — Retrieval Augmented Generation
Why Retrieval and What It Fixes
Chunking Embedding and Indexing
Improving Retrieval Quality
3 lessons
Stage Four — Agents and Tool Use
What an Agent Is and When It Helps
Designing Tools the Model Can Use
Safety Boundaries for Actions
3 lessons
Stage Five — Evaluation and Testing
Building an Evaluation Set
Grading Non-Deterministic Output
Regression Testing and Shipping Changes
3 lessons
Stage Six — Production Cost Latency and Safety
Cost and Latency Control
Safety Guardrails and Prompt Injection
Monitoring Feedback and the Career Path
3 lessons
Stage Three — Retrieval Augmented Generation
Chunking Embedding and Indexing
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