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06:00

Loop Engineering: Designing the System That Prompts Your Coding Agents

循环工程：让代码智能体在后台自主运行，而你设计的是循环本身

Addy Osmani argues that interacting with coding agents is shifting from prompt engineering to 'loop engineering'—designing a system that autonomously discovers tasks, delegates work, and verifies results using five building blocks: scheduled automations, parallel worktrees, project skills, connector plugins, and checker sub-agents. He maps how Claude Code and Codex both implement all five, noting that the leverage point has moved from writing good prompts to architecting persistent loops. The post cautions that loops amplify existing problems: verification, comprehension debt, and cognitive surrender become sharper risks. Intended for senior engineers evaluating how to productize AI coding tools beyond one-shot interactions.

x.com · 14 min · Agent Architecture · AI Agents · AI Engineering · Claude Code · Orchestration
06:00

How to Design a Loop That Prompts Your Agent

设计一个自行驱动 Agent 的多步任务循环

This article presents a loop architecture that enables an AI agent to autonomously complete multi-step tasks by building an automated prompting system instead of manually crafting each prompt. It breaks down the loop into five parts: defining a 'done' check, building prompts from dynamic state rather than hand-fed instructions, executing actions while capturing all outputs, feeding failures back as the next prompt, and setting hard stop conditions like max turns and cost limits. A walkthrough of fixing a login bug shows the loop in action, emphasizing that real costs come from repeated turns, making guardrails critical. Encapsulating repeated operations into reusable skills is highlighted as the key to long-term value, and common mistakes—like lacking an exit condition or discarding error output—are pointed out. Suitable for developers shifting from one-shot prompts to designing agent control flows.

x.com · 18 min · Agent Architecture · Agents · AI Engineering · Cost Optimization
06:00

AI Agents: What They Are and How to Build a Telegram Bot with Claude Code

AI Agent 实战：从理论光谱到零代码构建 Telegram 机器人

This guide clarifies that AI agents are not a category but a spectrum from simple chat to autonomous loops, defined by tools, memory, and a loop. It then provides a no-code, step-by-step tutorial on building a Telegram bot agent with Claude Code, including system prompt templates, systemd deployment, persistent memory, cost tracking, and practical skills. Also addresses the common memory problem and offers concrete fixes. Suitable for engineers who want a practical agent without writing code themselves.

x.com · 17 min · Agents · Ai Tooling · Claude Code · Context Engineering · Telegram Bot