LLM Primer

By LLM-PRIMER

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Episodes: 19

Description

LLM Primer is a structured deep dive into Large Language Models, based on a seven-book series covering everything from foundational concepts and mathematical intuition to RAG, MCP, scalable AI systems, and AI security. This podcast is built for engineers and serious professionals who want real understanding—not surface-level explanations. Each season corresponds to one book. Each episode builds technical clarity step by step. Understand the model. Build better systems.

Episode Date
2-7-7. Hallucinations and Reliability: Managing Confident Errors
Feb 19, 2026
2-7-6. Retrieval-Augmented Generation Risks: Securing the Knowledge Pipeline
Feb 19, 2026
2-7-5. Input Validation and Output Filtering: The Defense Pipeline
Feb 18, 2026
2-7-4. Prompt Injection and Jailbreaks: Defending the Interpreter
Feb 18, 2026
2-7-3. Data Security and Privacy: The AI Lifecycle
Feb 18, 2026
2-7-2. Threat Modeling for LLM Systems: A Step-by-Step Guide
Feb 18, 2026
2-7-1. The Probabilistic Shift: Why AI Security is Different
Feb 18, 2026
2-1-12. The System Architect — Building Your Own LLM System
Feb 17, 2026
2-1-11. The Research Frontier — Cutting-Edge Research
Feb 17, 2026
2-1-10. The Trust Architecture — Safety, Ethics, & Trust
Feb 17, 2026
2-1-9. The Cost of Intelligence — Performance, Scaling, and Costs
Feb 17, 2026
2-1-8. The Engineering Reality — Using LLMs in Applications
Feb 17, 2026
2-1-7. The Hybrid System — Beyond Next-Token Prediction
Feb 17, 2026
2-1-6. From Generalist to Specialist — Fine-Tuning & Adaptation
Feb 17, 2026
2-1-5. The Industrial Pipeline — Training Large Models
Feb 17, 2026
2-1-4. The Blueprint of Intelligence — The Transformer Architecture
Feb 17, 2026
2-1-3. The Computational Engine — Neural Networks for Language
Feb 17, 2026
2-1-1. Mechanism, Not Mythology — What Is a Large Language Model?
Feb 16, 2026
2-1-2 The Statistical Backbone — Probability, Tokens, and Text
Feb 16, 2026