509 related articles

A complete Claude Code beginner's guide: from CLI installation and switching to Chinese models like DeepSeek via CC Switch, to conversational Git operations, multi-branch management, and automated bug fixing.

A Google DeepMind engineer reveals that over 50,000 AI agent skills come with almost no evals. This guide covers skill descriptions, test design, eval harnesses, and retirement strategies.

An in-depth look at how AI Agents are disrupting traditional software testing: the core differences between LLMs and Agents, four capability dimensions (planning/memory/tools/skills), and how test engineers can achieve 10x efficiency gains in test case generation.

An in-depth look at how AI Agents disrupt traditional software testing: the core differences between LLMs and Agents, four capability dimensions (planning/memory/tools/skills), and how testers achieve 10x efficiency gains.

How do complete beginners get started with Claude Code? This guide covers VS Code setup, two ways to connect an LLM in China, four core usage modes, and building your first practical tool without writing a single line of code.

An in-depth guide to Claude Code from installation to hands-on practice: CLI setup, switching to domestic LLMs (CC Switch tool), conversational Git workflows, plus project analysis and automated bug fixing tips for AI-powered coding.

A complete guide to Claude Code: Node.js setup, CLI install, switching to Chinese LLMs with CC Switch, core commands, and conversational Git workflows with automated bug fixing.

NanoClaw founder David Boyd breaks down the core engineering of enterprise autonomous Agents: a triple security isolation model, LLM Wiki memory design, and the real-world path from personal Agents to team-scale deployment.

Hands-on test of open-source OfficeCLI: a single binary reads, edits, and generates Word/Excel/PPT. 1,000 cells rewritten in 0.37s, Chinese text supported. Covers XML internals, real failures, and AI Agent integration.

An in-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing methods and the transition path for test engineers.

In-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing and the transition path for test engineers.

A developer fine-tunes a small model with LoRA to extract conversation state, tackling the LLM long-conversation memory problem. A deep dive into the technical approach, dataset design, and the real trade-offs between fine-tuning and prompt engineering.

Step-by-step guide to deploying Dify AI platform locally with Docker. Covers Linux, Windows, macOS setup, docker compose launch, and first-time initialization in under 30 minutes.

From Vibe Coding to AI Engineering, explore Claude Code vs Codex tool selection, real enterprise boundaries of AI programming, and how to build maintainable AI-assisted development workflows.

Complete beginner's guide to OpenAI Codex desktop client: installation, setup, project management, and plugins — no coding required. Let AI actually do work for you.

A complete guide to Claude Code: CLI installation, switching to DeepSeek and other Chinese LLMs via CC Switch, and conversational Git workflows for developers.

A comprehensive guide to LangGraph's core concepts: Graph API vs Functional API, three-layer architecture, and workflow visualization methods for building AI Agents.

From the autocomplete nature of LLMs, tokens, and context windows to RAG vector databases, the MCP protocol, and AI agent loop design — this article uses vivid analogies to unpack the reality of AI engineering.

A deep comparison of Pipecat Flows and Vapi Squad for voice AI agent architecture — covering latency, accuracy, multi-agent handoffs, and when to use each.

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.