105 related articles

A detailed guide to Claude Code installation, domestic model switching, project analysis commands, and Git workflow practice to help developers quickly master this AI programming collaboration tool.

Loop Engineering is a paradigm shift in AI usage. Learn how to build automated loops where agents explore, execute, and verify tasks autonomously, with a hands-on e-commerce case study.

OpenAI's Jason Liu shares how he uses ChatGPT Workbench and Codex to build an AI work OS: Chief of Staff automation, persistent threads, Skills/Plugins, browser control, and app-building methodology.

A detailed guide to Vibe Coding with AI programming tools like Claude Code, Cursor, and Codex. Learn how to leverage AI-driven development to ship products independently and build lasting career value.

Clean Code author Robert C. Martin no longer reviews AI-generated code line by line, shifting to test-driven verification. We explore the logic, debate, and implications.

Complete guide to Claude Code covering CLI installation, domestic model switching, core commands, Git automation workflows, and automated code review and fix loops for enterprise projects.

A complete guide to Claude Code from beginner to enterprise practice: covering CLI installation, connecting domestic LLMs via CC Switch, basic commands, Git workflow integration, automated bug fixing, and engineering capabilities like MCP and SubAgents.

This week's GitHub trending focuses on AI coding: Skills sets rules for Agents, Omniroute is a never-down AI gateway, Code Review Graph is a code knowledge graph, PI is an open-source Agent toolbox, and AI Engineering from Scratch teaches from zero.

This week's GitHub trending focuses on AI coding: Skills sets rules for Agents, Omniroute is a never-down AI gateway, Code Review Graph builds a code knowledge graph, PI is an open-source Agent toolkit, and AI Engineering from Scratch teaches from the ground up.

In the AI programming era, Vibe Coding alone can only build toys. This article deeply analyzes the complete engineering path from Vibe Coding to SDD spec-driven development, covering Claude Code and Codex tool selection, the SuperPower plugin, and domestic LLM comparisons.

A complete guide to Claude Code: environment setup, switching to domestic LLMs, CLI commands, Git workflows, MCP, Subagents, and enterprise project walkthroughs.

Google DeepMind engineer Philip reveals: almost everyone uses coding agent Skills, yet almost no one writes evals for them. A deep dive into Skill evaluation methods, 8 actionable tips, and a real Gemini API case study.

AI code getting messier with edits? The root cause isn't weak model capability but a lack of context and process. A deep dive into Matt Pocock's Skills v1.1: grilling, vertical-slice tickets, TDD, and WebFinder.

A Claude Code open-source config with 278 skills and 67 sub-agents helps developers ship a full MVP in 8 hours. Covers security scanning, silent failure detection, and experience migration. Free under MIT license, compatible with Cursor and Codex.

Enterprise guide to Claude Code: CLI setup, switching to DeepSeek and other Chinese AI models, Git workflow automation, and bug fix loops to boost team productivity.

How to configure Cursor, Codex, Devin, and other AI coding agents for context management, code quality, and cross-tool collaboration. Practical tips on rule files, TDD, and structured context storage.

A deep dive into Waku Agent's four pillars: Loop Engineering, three-tier Memory system, Eval assessment, and the Harness scaffold. Full walkthrough of a local-first AI assistant from task execution to memory consolidation.

AI code spiraling out of control? This article breaks down a three-layer engineering system — Prompt rules, Skill workflows, and Harness feedback loops — with real-world results showing pass rates rising from 70% to 98%.
The Evolution of Coding Agents: A Para…
Coding agents are evolving from reactive code completers to proactive planners. Explore the "think ahead of time" paradigm, Plan-and-Execute architecture, and its impact on developer workflows.

OpenAI's new model reportedly proved the Cycle Double Cover Conjecture in under an hour using 64 parallel sub-agents. The real lesson? In the AI era, knowing how to ask the right questions matters more than knowing how to calculate.