What is an AI Agent? The Complete Architectural Guide to Autonomous Systems
AI Agents have transitioned from theoretical research to the backbone of enterprise automation. An agent is an autonomous entity capable of sensory perception, stateful memory persistence, goal decomposition, and external tool execution.
AM LABPassive Chatbots vs Active Autonomous Agents
Passive LLMs execute single-pass text generation. Agents operate in continuous cyclical feedback loops (Perceive -> Reason -> Act -> Observe -> Reflect). They handle non-deterministic environments and self-correct on runtime exceptions.
Cognitive Architectures: ReAct, Plan-and-Solve, Reflexion
Understand the mechanics of ReAct decision framing, dynamic plan reformulation, and introspective error recovery loops in modern agentic design.
Tool Execution Protocols and Model Context Protocol (MCP)
Explore how standardized schemas enable LLMs to safely query databases, trigger API mutations, and manipulate local development environments.
Production Guardrails: Circuit Breakers and Human-in-the-Loop
Eliminate runaway execution loops, enforce strict iteration timeouts, and implement approval gates for destructive production actions.
Silicon Telemetry & Production Verification
vllm serve what-is-an-ai-agent-guide --tensor-parallel-size 4 --gpu-memory-utilization 0.95 --max-model-len 32768 --kv-cache-dtype fp8
Artur Moiseyev
AI Systems Architect
Independent AI Researcher and Distributed Systems Architect. Building autonomous multi-agent workflows, open reasoning models, and real-time inference infrastructure.
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