Definition

What is Context Drift?

Last updated

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.

Related Context Rot Context Compression Context Window AI Agent

Further reading

Articles about Context Drift

AI agent reliability is a context problem

AI agent reliability fails because the same task assembles different context every run. Non-determinism is a context engineering problem, not a model flaw.

How prompt caching cuts AI agent costs by 90%

Prompt caching reduces AI agent API costs by up to 90% and latency by 31%. Here's how it works, where it breaks, and how to implement it right.

All terms

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Agent Drift Agent Reliability Agentic Retrieval AI Agent AI Hallucination AI Second Brain Chunking Context as a Service Context Bloat Context Compression Context Container Context Drift Context Engineering Context Offloading Context Poisoning Context Portability Context Pruning Context Rot Context Window Epistemic Provenance Fine-Tuning Knowledge Graph MCP Resources MCP Server MCP (Model Context Protocol) Multi-Agent System Prompt Caching Prompt Engineering RAG (Retrieval-Augmented Generation) Semantic Search Structured Context Tool Poisoning Wire

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