AI Agent

Definition

An AI Agent is a software system that perceives its environment, reasons about goals, and takes autonomous actions using a large language model (LLM) as its reasoning core. Unlike traditional software that follows hard-coded rules or decision trees, an AI agent uses the LLM to dynamically determine what actions to take in order to achieve a given objective. This means the agent can handle novel situations, compose multi-step plans, and adapt its behavior based on feedback from the environment—all without explicit programming for each scenario.

Engineering Context

In production, AI agents consist of four primary components: a reasoning loop powered by an LLM, a set of tools (APIs, databases, external services) the agent can invoke, memory systems (in-context and persistent), and guardrails for input/output validation. The LangGraph framework models agents as directed state machines, giving engineering teams explicit control over execution flow and making behavior auditable. Production agents are not monolithic—they are composed systems where each component has explicit interfaces, failure modes, and observability instrumentation. When deploying AI agents at enterprise scale, teams must account for latency budgets, cost per invocation, and retry logic across each component.

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