Tutorials · Chapter C · 3 of 4

Brain lab

LLM · tokens · RAG · agents — as toys

1. 01What is an LLM?7m
2. 02Tokens — how AI reads text6m
3. 2.5Training vs inference8m
4. 2.7Transformers in plain English9m
5. 2.9Serving Large Language Models9m
6. 03Context window suitcase6m
7. 04Temperature — safe vs creative6m
8. 05Embeddings — meaning as numbers7m
9. 06Vectors & similarity search7m
10. 07Overfitting playground6m
11. 7.5Multimodal AI8m
12. 08RAG — look it up, then answer8m
13. 09Inside RAG — the pipeline8m
14. 9.5Fine-tuning vs RAG9m
15. 10Tools — when AI takes action7m
16. 11Agents — think, act, repeat8m
17. 11.5Multi-Agent Systems9m
18. 12MCP — a standard plug for AI tools8m
19. 13Alignment and RLHF9m
20. 14Evals and benchmarks8m
21. 14.5AI Monitoring9m
22. 15Prompt injection & AI security9m
23. 16Choosing a model9m
24. 16.5Production AI Architecture10m