How AI Agents Work: Tools, Memory, MCP, Guardrails

How AI agents work beyond the LLM: prompt → tool call → policy → runtime → observation. Follow one agent from a user request to a controlled real-world action-plus memory, MCP, and guardrails. What you will learn • Why writing a plan is not taking an action • Structured tool calls and the agent loop • Session context vs durable memory • MCP discovery is not permission • Policy gates, human approval, budgets, and tracing Playlists AI Agents: https://www.

youtube. com/playlist? list=PLalLLKYP46NI OpenClaw: https://www. youtube. com/playlist? list=PLd5NwnNjVa64 DEEP AI: https://www. youtube. com/playlist? list=PLK3S1GR94Fzg Claude: https://www. youtube. com/playlist? list=PLkN0YpuOmhzOZQ5OaOBhgExLQd3d8aH1z

Watch the video for the full walkthrough. Use this page when you want the argument in writing without scrubbing the timeline.