AI Agent System Architecture

The system architecture of the AI ​​Agent System is the core technological framework for enabling intelligent agents to autonomously perceive, make decisions, and act. This section will delve into the typical layered design of this architecture, including the user interaction layer, perception and memory modules, planning and inference engine, tool invocation interface, and execution and feedback loop. Among these, the large language model, as the cognitive core, is responsible for intent understanding and task decomposition; short-term and long-term memory mechanisms support context management and experience accumulation; and standardized tool invocation protocols (such as Function Calls, MCPs, or custom API gateways) enable the Agent to reliably operate on the external environment and third-party applications. By explaining the data flow, control flow, and exception handling strategies between the components, this architecture provides systematic guidance for building production-grade Agent systems with autonomy, responsiveness, and collaborative capabilities.