Guides

Demystify temperature, top-p, and top-k sampling. Learn what these parameters actually do, how they affect output, and practical recommendations for different use cases.

Understand tokenization, context windows, and how different AI models handle long conversations. Learn practical strategies for working within token limits and comparing model capacities.

Understand retrieval-augmented generation (RAG): the architecture, when to use it, how it compares to fine-tuning, and prompt patterns for building effective RAG systems.

What AI agents actually are, how function calling works, planning loops, multi-agent architectures, and how to evaluate and safely deploy agent systems.