AI, Cloud & Code
Deep technical articles on AI agents, cloud architecture, and developer tools. Written by zhuermu.
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View all →Amazon's AI Full-Stack Breakdown 2026: Deep Pockets, Custom Chips, Global Infrastructure — So Why Is It the Least Visible Player in the AI Era?
Over the past two years, every time I open tech news, the headlines belong to the same names: OpenAI dropped another model, Google Gemini topped another benchmark, Anthropic's Claude 4 series sent developers into a frenzy, Microsoft Copilot landed another enterprise deal…
The Real Showdown After the Source Leak: Claude Code vs OpenClaw, 510K Lines vs 530K Lines
In our [previous article](https://zmead.com/blog/openclaw-vs-claude-code-design-philosophy), we dissected OpenClaw's 450K lines of open-source code alongside the 183 Markdown config files in Claude Code's public repository. We knew at the time that Claude Code's core runtime was closed-source — all we could analyze was the plugin ecosystem's definition layer. On March 31, 2026, security researcher Chaofan Shou discovered a 60MB `cli.js.map` file buried inside Claude Code v2.1.88's npm package — 1,884 TypeScript source files, 512,664 lines of code, fully exposed. This time, we finally get to crack open Claude Code's real engine and do a truly apples-to-apples source code comparison.
基于 Amazon CloudFront 和 Lambda@Edge 实现失败请求的完整记录与异步重放
本文介绍了一种基于 Amazon CloudFront 双 Lambda@Edge的架构方案，在不修改源站代码的前提下，完整记录被 WAF 拦截及源站返回错误的请求（含 headers 和 body），并通过 CloudWatch Logs + Kinesis Data Firehose 汇聚至 S3，支持异步补数重放。
WeChat Meets OpenClaw: What One CLI Command Tells Us About Platform Strategy in the AI Agent Era
WeChat's native integration with OpenClaw signals a major shift in platform strategy. Here's why the world's largest messaging app opening up to AI agents matters.
5 Pitfalls of Logging Failed Requests with CloudFront + Lambda@Edge
How we built a dual Lambda@Edge solution to capture full request headers and body for failed CloudFront requests — and the 5 pitfalls we hit along the way.
深入拆解 AI Coding Agent 的底层原理
从 LLM 推理、工具调用、上下文窗口管理到代码生成策略，全面解析 AI Coding Agent 的核心工作原理。