Deconstructing the AI Agent: Loops, Memory, and MCP

noninertialframe96 · reddit · 2026-08-15

This post breaks down the architecture of AI Agents into distinct layers to clarify the system:

Agent loop and stop conditions: Defining execution flow and termination.
Model settings and instructions: Core behavioral configuration.
Execution environment and sandboxing: Isolated runtime for safety.
Context policy and compaction: Managing input windows and information density.
Memory, Skills, and MCP: Storing experience, utilizing tools, and Model Context Protocol.

Based on an analysis of 20 open-source projects, it serves as a reference for understanding and improving agent features.

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