#架构设计
12 related articles
·2 min
Codex Systematic Tutorial: From Beginner to Enterprise-Level AI Engineering
In-depth guide to Codex AI programming tool: environment setup, Rules system, MCP protocol integration, multi-Agent collaboration, and enterprise RAG customer service project for complete AI engineering deployment.
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Tutorials·3 min
TheCherno Reboots Game Engine Series: AI-Assisted Development and Hazel Code Review
TheCherno reboots his Game Engine series with AI-assisted development. This article covers his Hazel engine code review, architecture analysis, and key improvements for building a new engine from scratch.
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Tutorials·3 min
MCP vs CLI: 40x Token Cost Difference — How AI Engineers Should Choose
In-depth comparison of MCP vs CLI architecture, Token costs (CLI ~1400 vs MCP ~54600), security mechanisms, and use cases with practical selection guidance for AI engineers.
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Product Reviews·4 min
OpenClaw vs Hermes: In-Depth Comparison and Selection Guide for Open-Source AI Agent Frameworks
In-depth comparison of OpenClaw and Hermes open-source AI Agent frameworks covering architecture, memory systems, auth, plugins, and channel distribution to guide developer selection.
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Tutorials·2 min
Deep Dive into Claude Code's Seven-Layer Architecture: Source-Level Analysis of the ReAct Loop and Configuration-Driven Design
Deep analysis of Claude Code's seven-layer architecture, ReAct loop core principles, and configuration-driven design. Source-level deconstruction of AI Agent mechanics with best practices.
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Tutorials·1 min
Deep Dive into OpenAI Codex Architecture: Three Core Layers Explained with Practical Pitfall-Avoidance Guide
Deep dive into OpenAI Codex's three-layer architecture: instruction parsing, code generation, and optimization. Covers task scheduling, context management, common pitfalls, and practical development cases.
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Tutorials·2 min
Multi-Model Hot-Swap Architecture: Switch AI Models at Minimal Cost
A complete guide to building a multi-model hot-swap architecture for production AI projects, covering abstraction layers, adapter patterns, visual configuration, and error-fixing workflows.
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Tutorials·2 min
Building an Agent Framework from Scratch: Breaking Down the Four Core Modules with Code Implementation
Learn how to split AI Agent capabilities into four modules—Tool Registry, Message Store, Agent Runtime, and Built-in Tools—and build a reusable, extensible Agent framework using Python decorators.
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Tutorials·3 min
Frontend Engineers Leveling Up to AI Agents: LangGraph.js Architecture Design & Practical Guide
How can frontend engineers advance into AI Agent development? This guide covers LangGraph.js core architecture (state, nodes, edges), LangChain comparison, and workflow agent design with practical examples.
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Industry Insights·2 min
How MCP Becomes a Deep Extension Point for Agent Platforms: Architecture Design and Practice
Deep dive into MCP protocol architecture in Agent platforms, covering MCP Proxy design, tool invocation for human-in-the-loop collaboration, permission integration, and advantages over Skill approaches.
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Industry Insights·1 min
Claude Code Architecture Deep Dive: Why a Single-Loop Design Beats Multi-Agent Systems
Deep dive into Claude Code's architecture: single-loop control, no RAG, 9,400-token tool prompts, and model tiering. The minimalist design behind a $1B AI coding tool.
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Tutorials·2 min
Claude Code Enterprise Deployment Guide: Ecosystem Framework and Hands-On Configuration
Deep dive into Claude Code's enterprise deployment architecture for large codebases, covering CLAUDE.md, Hooks, Skills, MCP servers, and organizational governance strategies.
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