Beginner · Systems

Agentic Context

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. The full set of information an agent has available when it decides its next action — goals, state, tools, memory, and retrieved data.

Technical Definition

The full set of information an agent has available when it decides its next action — goals, state, tools, memory, and retrieved data.

How it works

Agentic context is everything that shapes an agent's next decision: the system instructions and role, the user's goal, conversation history, tool definitions and their outputs, retrieved documents, long-term memory, and environment state such as time, permissions, or the current file tree. Unlike a chatbot prompt, agentic context changes on every loop iteration as the agent observes results and updates its plan. Because model behaviour is almost entirely determined by what is in the window, context quality — not model choice — is usually the dominant factor in agent reliability.

Related Concepts

• Agentic Context Management (ACM) — The discipline of deciding what an AI agent knows at each step — assembling, curating, compacting, and securing its working context.
• Agent Memory — Information an agent retains beyond the current context window — episodic history, learned facts, preferences, and task state.
• Context Window — The maximum number of tokens a model can process in a single input, determining information capacity.
• AI Agent — An AI system that autonomously plans, uses tools, and takes actions to accomplish goals through iterative reasoning.