Agents
A failure mode where a hallucination or error gets written into an agent's context and is then treated as fact on every later turn.
A failure mode where a hallucination or error gets written into an agent's context and is then treated as fact on every later turn. Google's Gemini 2.5 technical report used the term for its Pokemon-playing agent, where misinformation about the game state spread into its goals and summary sections, took a long time to undo, and pushed it into misguided strategies. The usual fixes are pruning or resetting the poisoned context and checking facts before an agent writes them into memory or summaries.
Primary source: arxiv.org
Example
In practice, developers reach for Context Poisoning when they need the capability described above as part of an AI feature or workflow.
Hands-on guides, comparisons, and tutorials that cover Agents.
FAQ
A failure mode where a hallucination or error gets written into an agent's context and is then treated as fact on every later turn.
Context Poisoning sits in the Agents part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Developers Digest publishes tutorials and videos that cover Agents topics including Context Poisoning. Check the blog and YouTube channel for hands-on walkthroughs.
Related
A multi-agent mechanism where one agent passes control of the conversation to a more specialized agent, rather than calling it as a subroutine.
A beta Claude API feature that automatically clears stale content from a conversation server-side before it reaches the model, while your client keeps the full history.
A benchmark from Sierra that tests agents in multi-turn customer-service conversations, where a language-model-simulated user talks to an agent that has domain API tools and a written policy to follow.

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