The original title is "AI Agentic Workflow Explained: A Quick Tour of Harness, Tools, Skills, MCP, and Memory"

Short summary

An overview of production AI agent architecture, breaking down components beyond the LLM: harness, tools, skills, MCP integrations, and memory. Explains the reason-act-observe loop and how the harness manages context assembly, tool access, and security. Introduces Model Context Protocol as a standard way to connect agents to external systems without custom integrations per application.

• •A production AI agent combines a model with a harness, tools, skills, MCP integrations, and memory
• •The agent loop is Reason → Act → Observe → Repeat, with the harness bridging reasoning and execution
• •MCP standardizes connections to external systems, replacing per-application custom integrations

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