172 related articles

A detailed guide to Qoder's Rules feature: creation methods, type selection, and usage tips. Learn how to persistently constrain AI Agents like CLAUDE.md for better controllability.
科技前沿CLAUDE.md hits GitHub trending with 4 core rules for taming AI coding assistants: ask when unsure, don't over-engineer, stay on task, and give goals not steps. Master the new AI collaboration methodology.
教程攻略Deep dive into Claude Code's CLAUDE.md path loading logic, verifying hierarchical stacking through experiments, with three writing methods and practical tips for developers.

Bun runtime now generates a CLAUDE.md file by default with bun init, signaling AI assistants becoming first-class citizens in the development toolchain.

Deep dive into Harness Engineering: why AI Agents need memory management, durable execution, guardrails & approvals to go from demo to production.

Deep dive into Harness Engineering: why AI Agents need memory management, durable execution, guardrails & approvals to reach production. Based on Scott Moss's workshop.

Explore Harness Engineering: the next evolution beyond context engineering for AI programming. Learn how to build enterprise-grade Skill systems and deliver real projects with mid-tier models.

Complete guide to Pi coding agent: design philosophy, installation, shortcuts, session management, and 7-layer customization architecture. How this 45K-star minimalist terminal tool redefines AI coding workflows.

Claude Code creator Boris argues top engineers should embrace AI-era automation leverage. By encoding domain knowledge into infrastructure, preview environments, and lint rules, engineers multiply output—the core path to Staff Engineer.

Claude Code creator Boris and developer Theo reveal: in the AI Agent era, tinkering habits like automation, building small tools, and writing CLAUDE.md are becoming the core edge for reaching Staff engineer level.

Through a complete case of auto-generating test cases from requirement docs, this article explains Claude Code's Agent Skills packaging mechanism—turning proven AI workflows into reusable skills with on-demand loading.

Claude Code isn't just a chat AI—it can directly read projects, modify code, and run commands. This article compares Claude Code with regular AI across five dimensions to help you decide if it's worth trying.

Claude Code isn't just a chat AI—it can directly read projects, modify code, and run commands. This article compares Claude Code with ordinary AI across five dimensions: interaction, context, execution, memory, and tool calling.

Can AI coding tools let non-developers replace programmers? This deep dive examines Vibe Coding's real limits, compares Claude Code vs. Codex, and reveals the methodology behind enterprise-grade AI-assisted software engineering.

An in-depth guide to Anthropic's Claude Code agentic coding tool, covering installation, pricing plans, model selection, token management, CLAUDE.md global memory, MCP integration, Subagents, and more.

In-depth analysis of Claude Code customization methodology: from access, knowledge injection to tooling. Master context window management, zero-overhead Hooks, and MCP & Skills plugin primitives to build a scalable AI software engineering workflow.

Model performance gaps are closing. Real competitive advantage lies in portable AI agent architecture. Learn how to build a workspace that works across Claude Code, Codex, and beyond — no vendor lock-in.

A deep dive into the 7 core components for building long-running AI Agents: Goal, Evaluator, Verifier, Loop, Orchestration, Observability, and Memory.

A practical guide to Claude Code covering installation, Chinese LLM switching, project analysis, key commands, and conversational Git workflow automation for developers.

Deep dive into AI-era automated testing: using Pytest + Playwright + MCP for stable automation, constraining code conventions with Skills, avoiding non-determinism and high token costs. Includes real debugging war stories.