Definition
What is Context Drift?
The gradual loss of task-relevant information as an AI agent's context window fills with accumulated history.
Context drift occurs when new tool outputs, observations, and messages push critical information like the original task goal or early decisions out of the model's effective attention range. Unlike hitting a token limit, drift degrades performance silently. Studies attribute 65% of enterprise agent failures to context drift during multi-step reasoning rather than raw context exhaustion.
The gradual degradation of an AI system's usefulness as the context it relies on becomes stale, incomplete, or outdated.
The practice of reducing token count in an AI agent's context window while preserving the information needed to complete tasks.
The maximum amount of text (measured in tokens) that a language model can process in a single inference call.
An autonomous software program that uses a large language model to plan and execute multi-step tasks.
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