AI Fundamentals

Context Window

The maximum amount of text an AI model can process in a single interaction, measured in tokens.

modelslimitationsmemory

The context window is an LLM's working memory — the total amount of text it can "see" at once, including the conversation history, system instructions, and any retrieved documents. It is measured in tokens, where one token roughly equals 3-4 English characters.

Context window sizes have grown dramatically. Early models had 4K tokens (about 3,000 words). Modern models like Claude offer 200K tokens (about 150,000 words — roughly a full novel). This expansion fundamentally changes what AI agents can do: they can analyze entire codebases, process lengthy documents, and maintain coherent long conversations.

For AI agent systems, context window size determines how much information an agent can work with simultaneously. A larger context window means the agent can see more of your codebase, understand more of the project history, and make better-informed decisions. At Agentik {OS}, we use context management strategies — RAG, summarization, and selective retrieval — to ensure our agents always have the most relevant information within their context window, regardless of project size.

Related Terms

Token

The basic unit of text that AI models process — roughly equivalent to a word or word fragment.

Large Language Model (LLM)

A neural network trained on massive text data that can understand and generate human-like language, code, and reasoning.

Retrieval-Augmented Generation (RAG)

A technique that gives AI models access to external knowledge by retrieving relevant documents before generating a response.

Prompt Engineering

The practice of crafting instructions that guide AI models to produce accurate, relevant, and useful outputs.

Want to see AI agents in action?

Book a Demo