How to Build an AI Agent That Works in Loops

The practical 2026 guide to building an AI agent with tools, skills, memory, checks, and a real stopping point.

How to Build an AI Agent That Works in Loops

TL;DR

  • AI agents are designed to work continuously towards a goal, repeating tasks until completion.
  • Key components of a working AI agent loop include: Trigger, Goal, Tools, State, Check, and Stop.
  • The agent's effectiveness comes from its ability to observe, act, use tools, inspect results, update state, and check completion in a repeating cycle.
  • Newer SDKs like Claude Code and OpenAI's Agents SDK simplify agent creation by managing loops, tools, and sessions.
  • The core principle is to start with a narrow job, make verification visible, and avoid unnecessary complexity in memory, tools, or additional agents.