Complete lifecycle of large language models from pre-training through fine-tuning, RLHF, and deployment — with architecture diagrams and production considerations.

When and how to fine-tune LLMs: LoRA, QLoRA, full fine-tuning decision framework with cost analysis and real-world examples.

How LLMs use function calling and tool use — the mechanics behind tool-calling agents, from prompt engineering to structured output.

Step-by-step breakdown of an LLM tool call: request, schema validation, execution, and result handling with code examples.