7 Core Components of an AI Agent Architecture Explained

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This post details the seven core components of an AI agent architecture: Goal Definition, Perception and Input Processing, Memory Systems, Reasoning and Planning, Tool Execution and Action, Orchestration and Coordination, and Feedback and Observability. It explains how each component contributes to building scalable, compliant, and trustworthy AI systems, highlighting technical aspects like input sanitization, hybrid memory models, various reasoning strategies (rule-based, chain-of-thought, tree-of-thought, Monte Carlo), action sandboxing, supervisor-worker hierarchies, and observability for debugging and compliance. Glean's platform is mentioned as an example for several of these components, particularly in unifying perception, providing context-aware access to enterprise knowledge, and ensuring secure enterprise integrations.