Last updated: April 2026 Karpathy’s LLM Wiki is a 3-layer architecture — raw sources, LLM-compiled markdown pages, and a schema file — that replaces stateless RAG with a persistent, self-maintaining knowledge base. Instead of retrieving and re-synthesizing documents on every query, the LLM “compiles” them once into cross-referenced wiki pages, then reads from the compiled … Read more
Model Context Protocol (MCP) is an open standard created by Anthropic in November 2024 that gives large language models a universal, JSON-RPC 2.0-based interface for connecting to external tools, databases, and services. Instead of writing custom connectors for every LLM-plus-tool pair (the N×M problem), developers expose capabilities through MCP servers and consume them through MCP clients … Read more
AI Agents Explained: How Autonomous AI Works in 2026 AI agents are autonomous software systems that perceive their environment, reason about goals, and take independent actions — such as calling APIs, booking flights, or coordinating with other agents — without step-by-step human instructions. In 2026, agentic AI has crossed from pilot programs into mainstream enterprise … Read more
Retrieval-Augmented Generation (RAG) is an AI architecture that enhances large language models by retrieving relevant documents from an external knowledge base before generating a response. Instead of relying solely on static training data, RAG injects real-time, domain-specific context into the prompt — reducing hallucinations and keeping answers current. This guide walks you through every layer … Read more