Agent Drift in Multi-Agent LLM Systems: Why Your AI Teams Fail Over Time & How to Fix It

Agent Drift in Multi-Agent LLM Systems: Why Performance Degrades Over Extended Interactions Core question this article answers: Why do multi-agent large language model (LLM) systems gradually lose behavioral stability as interactions accumulate, even without any changes to the underlying models, and how severe can this “agent drift” become in real-world deployments? Multi-agent LLM systems—built on frameworks like LangGraph, AutoGen, and CrewAI—are transforming enterprise workflows by breaking down complex tasks across specialized agents that collaborate seamlessly. These systems excel at code generation, research synthesis, and automation. However, a recent study highlights a critical, often overlooked issue: agent drift, the progressive degradation …