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Core
Agent Memory: Short-Term, Long-Term, and Memory Stores
Agent memory is how an agent holds onto and recalls information across steps and sessions. Short-term (working) memory sits in the context window for the current task; long-term memory is durable information (facts, user preferences, past outcomes) kept outside the window and retrieved when it matters. The skill lies in choosing what deserves to be remembered, where to keep it, and when to read it back. Applied AI interviews test it because durable memory is what turns a one-shot chatbot into an agent that gets better over time.
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RELATED CONCEPTS
PRACTICE THIS IN REAL QUESTIONS
RAG & Agent System DesignHow do you manage memory and context for a long-running conversational agent?→RAG & Agent System DesignDesign the memory architecture for an agent that runs for weeks across thousands of interactions.→RAG & Agent System DesignWhen do you build an agent instead of a single LLM call, and how do you keep a multi-step agent reliable?→RAG & Agent System DesignWhen do you use a multi-agent system, and what orchestration patterns and pitfalls matter?→System Design for AI in ProductionDesign a deep research agent that answers complex questions by searching and synthesizing many sources.→System Design for AI in ProductionDesign memory for a personal AI assistant that remembers users across sessions.→
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