AI Integration Guides & Tutorials

RAG pipeline illustration showing documents being converted to vectors and retrieved

September 6, 2026

RAG Explained: Retrieval-Augmented Generation for Production AI

Large language models are powerful, but they have a fundamental limitation: they only know what was in their training data. When a…

Local LLM illustration showing on-premise server running AI models

September 6, 2026

Running Local LLMs with Ollama: Privacy, Cost, and Control

Cloud LLMs are powerful, but they come with trade-offs: per-token costs that scale with usage, data leaving your infrastructure, and dependence on…

MCP hub-and-spoke diagram showing Model Context Protocol connecting AI to tools

September 4, 2026

MCP (Model Context Protocol): The Universal Standard for AI Tools

Every time you build an AI agent, you write integrations — code that connects the model to your databases, APIs, and file…

Vector database illustration showing points clustered in vector space

September 2, 2026

Vector Databases Compared: Pinecone vs. Weaviate vs. Qdrant vs. Chroma

Vector databases are the storage layer that makes RAG, semantic search, and AI memory possible. They store high-dimensional vectors (embeddings) and find…

Latest from Affix Agent

RAG Explained: Retrieval-Augmented Generation for Production AI

Running Local LLMs with Ollama: Privacy, Cost, and Control

MCP (Model Context Protocol): The Universal Standard for AI Tools

Vector Databases Compared: Pinecone vs. Weaviate vs. Qdrant vs. Chroma