Explore how memory empowers agentic AI systems—why memory matters, how it’s built, what types exist, what challenges and design-patterns to use, and how memory transforms reactive tools into truly autonomous agents. Introduction There is nothing more frustrating than building an AI agent that 'forgets' what you said two minutes ago. We’ve all been there—prompting a bot only to realize it has lost the context of the project. This isn't a problem with the AI's 'intelligence'; it's a problem with its Memory Architecture . Today, I’m breaking down how I build memory into my agents so they actually learn from every interaction. What is memory in the context of agentic AI? When we speak of memory for agentic AI systems, we refer to the mechanisms and architectures by which agents store, recall and utilise information from past interactions, experiences or user context. IBM defines agent memory as: “an artificial intelligence system’s ability to store and recall...
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