日刊 · 2026-05-28 — Glean

Thu, May 28, 2026 8picks

13:39

Agent Unveiled: Principles, Architecture, and Engineering Practices

Agent 架构、工程实践与落地：从原则到 OpenClaw

This article systematically examines the underlying architecture and engineering practices of agent systems. Starting from a stable agent loop, it contrasts workflows with agents, explains five control patterns, and emphasizes that the harness (evaluation baselines, execution boundaries, feedback, and fallbacks) often matters more than the model itself. It details context engineering via layered management and three compression strategies to prevent context rot, ACI‑oriented tool design, a four‑type memory system with consolidation, long‑task state externalization across sessions, protocol‑based multi‑agent coordination, eval frameworks (Pass@k and Pass^k), and event‑driven observability. Finally, it shows how these principles are implemented in OpenClaw, providing a practical reference for engineers building robust agents.

tw93.fun · 31 min · Agents · Framework · LLM

11:18

Deconstructing Claude Code: Architecture, Governance, and Engineering Practices

拆解 Claude Code：六层架构、治理与工程实践

Based on six months of intensive use of Claude Code, the author breaks down its functionality into six layers (CLAUDE.md/rules/memory, Tools/MCP, Skills, Hooks, Subagents, Verifiers) and provides design principles, anti-patterns, and configuration examples for each. The article focuses on context engineering (token cost structure, layered loading strategy, compaction pitfalls), tool design, Hooks for mandatory enforcement, Subagents for context isolation, prompt caching, and verification loops. Ideal for engineers wanting to move from ad‑hoc chat to a disciplined agent engineering workflow.

tw93.fun · 20 min · Agents · AI

09:41

Beyond the Coding Assistant — A New Series

超越编码助手：企业级 AI 辅助软件工程系列开篇

This free series examines AI-assisted software engineering at enterprise scale. While individual coding speed has skyrocketed, many teams have not seen delivery improve—some have even slowed down. The author argues that current AI coding assistants optimize a single role, but software is shipped by teams with many non-coding roles. The next frontier is lifecycle orchestration, not better code generation. The series is structured in four parts, publishing three times a week with no paywall. It is aimed at engineering leaders, architects, and developers interested in AI engineering.

articles.zimetic.com · 8 min · Agents · AI

09:30

CSS Refactoring with an AI Safety Net

用AI安全网重构CSS：零视觉变化的七阶段计划

The author refactored a tangled CSS codebase into a clean architecture using Claude Code and Playwright, ensuring zero visual changes across seven phases. A Playwright script captured 9 app states, and after each phase, Claude compared screenshots to baseline, catching regressions like a line-height shift. The result: layered CSS with modern reset, unified button classes, and CSS variables. The post details state enumeration, script writing, and AI-driven diffing, and discusses trade-offs with dedicated tools. Essential reading for front-end developers tackling legacy CSS.

danielabaron.me · 12 min · AI · Framework

09:24

Andrej Karpathy wrote something that every Claude Code user has felt b

卡帕西三句话，说破每个Claude Code用户的痛点

Andrej Karpathy's three observations about LLM behavior—making silent assumptions, overcomplicating code, and performing careless side effects—inspired a single CLAUDE.md file with four principles: think before coding, prioritize simplicity, make surgical changes, and execute goal-driven. Each principle directly addresses a specific pain point. The file is ready to drop into any project to guide AI coding assistants toward more disciplined output. For every Claude Code user who has experienced these issues but struggled to articulate them.

x.com · 2 min · AI · LLM

09:14

how to build a production grade ai agent

构建生产级AI智能体的十条工程原则

Over 40% of agentic AI projects fail, not because of models, but due to poor risk controls, architecture, and business value. This article presents ten engineering principles: threat modeling, strictly typed tool contracts, least-privilege execution, compact context engineering, governed retrieval, deterministic orchestration, separated memory, reliability mechanics, full observability, and continuous governance. Each principle provides concrete implementation details and real-world numbers (e.g., prompt injection appears in 73% of deployments), guiding teams to build secure, scalable production-grade agents.

x.com · 20 min · Agents · AI · LLM

09:13

The 8 Levels of Agentic Engineering

Agentic 工程的八个层级：从自动补全到自治团队

Bassim Eledath maps the progression of AI-assisted coding into 8 levels, from tab-complete and AI IDEs to context engineering, compounding engineering, MCPs & skills, harness engineering with automated feedback loops, background agents, and autonomous agent teams. Each level builds on the previous, with practical insights on closing the gap between model capability and practice. He argues that plan mode is fading, multi-model dispatching yields better results, and true autonomous teams are still experimental. The piece serves as a roadmap for engineers looking to leverage AI more effectively.

www.bassimeledath.com · 22 min · Agents · AI · LLM

09:13

How Coding Agents Are Reshaping Engineering, Product and Design

编码代理如何重塑工程、产品与设计

Coding agents are fundamentally reshaping the EPD (Engineering, Product, and Design) collaboration model. With the cost of implementation plummeting, the traditional PRD→mockup→code waterfall is dead, replaced by a review-centric process where prototypes are rapidly generated and then scrutinized. Generalists who wield coding agents gain unprecedented leverage; system thinking and product sense become essential for everyone. The bar for specialization rises, and roles converge into either builders or reviewers. Ultimately, anyone with a deep grasp of both product and technology can thrive, blurring traditional role boundaries.

x.com · 12 min · Agents · AI

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