What an Agent Loop Is and How It Powers Multi-Step AI Agents
A Juejin article explains an Agent Loop as a repeating process that sends context to a model, executes selected tools, adds the results to history, and continues until the task ends. It connects the loop to the Think–Act–Observe pattern and provides a short Python implementation with step limits, tool execution, and history management. The article also discusses parallel tool calls, stopping conditions, context overflow, repeated actions, and premature completion.
The tutorial gives developers a compact reference for the runtime structure that turns a model-and-tools setup into a multi-step AI agent.
同样是调
GPT或者Claude，网页聊天框里它只能回你一段话；放进Codex或者Claude Code里，它能自己翻文件、改代码、跑测试，折腾二十分钟把活干完。 差别不在模型，在模型外面那圈代码——一段while循环。
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0x00、Agent 和聊天框，差的就是一个循环
先看一个说法：AI Agent 就是一段会重复执行的代码。
它干的事可以用一句话说完：把当前状况发给大模型，执行模型选中的工具，把结果塞回去，再发一遍，一直转到任务做完。
Think（想）→ Act（做）→ Observe（看）→ 重复，直到目标达成。