AI Agent Context Management: Where Context Should Live

AI agents lose context between runs. This guide explains how memory, RAG, and context windows differ, and why file-based context drives are emerging.

AI agents can feel impressively competent inside a single task. Then the run ends and the next session starts, and the agent is back to asking the same questions and repeating the same mistakes. This is not mainly a “model got smarter” problem. It’s an agent context management problem: where does the agent’s context live, how does it persist, and how does the agent reliably get the right slice of it at the right time?

Read the full article: https://www.puppyone.ai/en/blog/ai-agent-context-management-where-context-lives

• URL: https://www.puppyone.ai/en/blog/ai-agent-context-management-where-context-lives
• Owner Name: Steve Mu
• Owner Email: support@puppyone.ai
• Meta Keywords:

  agent context management, agent memory, RAG, context window, AI agents

• Meta Description:

  AI agents lose context between runs. How memory, RAG, and context windows differ, and why file-based context drives are emerging.