Definition
What is Agent Drift?
Last updated
The gradual behavioral deviation of an AI agent from its original goal, role, or correct operation over long-running tasks.
Agent drift is the umbrella phenomenon covering six distinct failure modes in long-running agentic systems: goal drift, context drift, role drift, tool-use drift, hallucination cascades, and plan decay. Most production agent failures trace to one of these mechanisms rather than to raw model capability, and most are solvable with context engineering rather than bigger models.
Further reading
Articles about Agent Drift
Agentic context engineering: how ACE evolves contexts
ACE (ICLR 2026) beats tuned prompts by 10.6% with self-evolving contexts that avoid brevity bias and context collapse, two real failures of prompt tuning.
Anthropic's Managed Agents memory: what it changes
Anthropic launched Memory for Managed Agents on April 23, 2026 in public beta. What the design means for agent scope, freshness, and context engineering.
Why every agent handoff corrupts your context
Every multi-agent handoff is a lossy compression event. Learn which five types of context degrade at agent handoff boundaries and how to preserve them.
Agent drift: why long-running AI agents lose the plot
Agent drift is how AI agents silently deviate from goals over long-running tasks. Six mechanisms cause it, and most have nothing to do with the model.
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