RAG

AI memory is not one thing. This guide separates context windows, retrieval (RAG), vector databases, and long-term memory in ChatGPT and Claude.

Cohere is the enterprise-focused LLM provider founded by a transformer co-author. Learn its models, strengths, and how it compares to OpenAI and Anthropic.

Perplexity AI is an answer engine that pairs live web search with LLMs and numbered citations. How it works, what it costs, and its legal fights.

LangChain and LlamaIndex both build LLM apps in Python. Differences, strengths, code examples, and when to pick each in 2026.

Vector databases store embeddings and run similarity search via ANN indexes. Pinecone, Weaviate, Qdrant, pgvector — compared for 2026.

Context windows define how much text an LLM can process at once. Learn token limits, the lost-in-the-middle problem, and 2026 model comparisons.

Embeddings turn text and images into vectors that capture meaning. Learn how vector search, RAG, and similarity work — with 2026 models compared.

RAG is the technique making AI tools actually useful for real work — letting models look things up instead of relying on memory. Here's how it works and why it matters.