Visual, beginner-friendly guides to the core concepts behind modern AI systems — from how language models work to agents, retrieval, and tooling protocols.
The essential vocabulary of large language models — what tokens are, how context windows work, why temperature controls creativity, and what causes hallucinations. Includes a clear breakdown of prompting vs RAG vs fine-tuning to help you pick the right tool for the job.
A visual walk-through of retrieval-augmented generation from raw documents to a grounded answer. Covers the offline indexing phase (chunking, embedding, vector index) and the online query phase (similarity search, prompt construction, generation).
The open protocol that lets AI models connect to external tools, databases, and services in a standardized way. Covers the host-client-server architecture, the tool call lifecycle, and the three primitives — tools, resources, and prompts.
How AI agents move beyond single-shot Q&A to complete complex, multi-step tasks autonomously using reasoning loops, memory, and tools. Covers the ReAct cycle, agent architecture components, and three key patterns — single-agent, multi-agent, and plan-and-execute.