Introduction to LLM - LLM Primer V — Building Real-World LLM Applications
This page provides an easy-to-understand guide on LLMs (Large Language Models) from basics to applications for AI enthusiasts.
Chapter 8 — Optimizing Performance, Serving, and Cost
Eighth and final post of the LLM Primer V walkthrough. Semantic caching, dynamic model routing, and what actually happens inside the inference server — plus a look ahead to Volume VI on scaling.
2026-04-21
Chapter 7 — LLM Security and Guardrails
Seventh post of the LLM Primer V walkthrough. The OWASP LLM Top 10 as a working checklist, direct-versus-indirect prompt injection, and the four-layer mitigation matrix.
2026-04-20
Chapter 6 — AI Observability and Tracing
Sixth post of the LLM Primer V walkthrough. OpenTelemetry GenAI conventions, span design for LLM apps, cost tracking, and the loop back into the evaluation harness.
2026-04-19
Chapter 5 — Evaluating LLM Applications
Fifth post of the LLM Primer V walkthrough. The offline-online eval distinction, LLM-as-judge patterns, the RAG Triad, and trajectory tests for agents.
2026-04-18
Chapter 4 — AI Agents and Tool Calling
Fourth post of the LLM Primer V walkthrough. ReAct loops, tool schemas as contracts, and the three memory layers agents actually need in production.
2026-04-17
Chapter 3 — Retrieval-Augmented Generation
Third post of the LLM Primer V walkthrough. The RAG pipeline end to end — chunking, hybrid retrieval, query transformation, multimodal, and text-to-SQL — and where RAG fits versus fine-tuning and long context.
2026-04-16
Chapter 2 — Foundation Models & Prompt Engineering
Second post of the LLM Primer V walkthrough. Model tiering, sampling parameters, defensive prompt patterns, and structured outputs as engineering surfaces — the layer just inside the deterministic wrapper.
2026-04-15
Chapter 1 — The Discipline of AI Engineering
First post of the LLM Primer V walkthrough. Why the demo works and production doesn't — the deterministic wrapper around the probabilistic core, and the five pillars (reliability, quality, performance, cost, evolution) that keep the wrapper honest.
2026-04-14
LLM Primer V — Series Introduction & Index
Kicking off the chapter-by-chapter walkthrough of Book V in the LLM Primer series — Building Real-World LLM Applications. Why AI engineering is a discipline of its own, who this book is for, and the schedule for the eight posts that follow, April 14 through April 21.
2026-04-13