AIエージェントとは何か？自律システムの完全アーキテクチャ設計ガイド
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 LAB
Passive 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ハンドブック内の関連調査
AM LABAIスキル「Deep Research」完全解説：ChatGPT・Perplexity・Geminiが数時間のリサーチを10分に短縮する仕組み
ChatGPT、Perplexity、GeminiのDeep Research機能をわかりやすく解説。
AM LABAIスキル「Computer Use & Operator」解説：AIがブラウザやマウスを自動操作する仕組み
画面を見てクリックや入力を代行するブラウザAIエージェントの活用法。
AM LABAIスキル「MCP（Model Context Protocol）」を超わかりやすく解説：AIと外部アプリを繋ぐ万能USBポート
なぜ今「MCP」がこれほど注目されているのか？専門用語なしで仕組みと活用法を徹底解説。