656 related articles

Jensen Huang's first tweet backs AI open source, but behind it lies NVIDIA's deep anxiety over CUDA ecosystem displacement. We analyze why open-source models matter and what's really at stake.

A detailed comparison of OpenAI Codex and Claude Code with hands-on testing. From AI agent concepts to account setup, helping developers quickly master AI coding agents.

A detailed guide to getting started with Codex and Claude Code—two leading AI agentic coding tools. From environment setup to hands-on practice, even beginners with no coding experience can master AI programming assistants.

Deep dive into the trending open source project Impeccable — a design language framework that enables AI tools to generate professional-grade UI. Learn how it bridges the design quality gap in AI-generated interfaces.

API Mock is fast but misses bugs; Sandbox is realistic but costly. This article analyzes their core differences and provides a layered testing strategy for building reliable Agent test systems.

AI coding tools are reshaping software development. Is learning to code still worthwhile? This article analyzes the challenges and opportunities of learning programming in the AI era.

A Reddit user tested Gemini 3.5 Pro in Arena and found it generates 20+ files with hundreds of lines of code per file in a single pass, with no lazy shortcuts or placeholders.

Know a little of everything but can't figure out what to build? Practical methods to overcome tech decision paralysis and find your ideal project direction.

Discover a hidden trick in Codex iOS voice mode: tap the central circle to show subtitles, solving pain points like unclear code names and hard-to-distinguish technical content in voice interactions.

With GitHub Copilot now billing at API rates, model costs match raw APIs. This article analyzes Copilot's real value in workflow integration, enterprise governance, and harness engineering.

A 12-person product team shares real-world experiences with Cursor, Codex, Claude Code, and CodeRabbit—exploring efficiency plateaus, scenario matching, and selection criteria for AI coding tools that actually stick.

Natural language programming is reshaping frontend development. This article explains AI code generation, Prompt formulas, pitfall avoidance, RAG, Agent orchestration, and skill maintenance.

Claude Code is Anthropic's command-line AI coding assistant that reads entire projects, auto-corrects errors, and delivers runnable code. Compare it with Cursor, Trae, and Copilot.

A complete guide to the three core categories of AI tools in the testing era (personal assistants, CLI geek tools, AI IDEs), revealing the real challenges of AI test case generation and the new AI test development paradigm.

Anthropic's Applied AI team breaks down a methodology for choosing AI models: building custom evals, avoiding three common pitfalls, measuring value by cost per success, and cutting costs with prompt caching and context engineering.

From prompt engineering to context engineering to Harness engineering, this article breaks down the three evolutions of AI coding and offers engineering solutions to pain points like hallucinations, non-standard code, and infinite loops.

A detailed walkthrough of the full Claude Code setup process, comparing AI coding tools like Cursor and Trae, and analyzing the cost and performance of models like Sonnet and DeepSeek V4 Pro.

An in-depth look at Claude Code's key strengths: full-project context reading and automatic debugging. Compare Cursor, Trae, Codex, and more to find your ideal AI coding assistant.

An in-depth look at an intelligent paper writing platform built on FastAPI + Vue 3, combining LLM, RAG, and multi-Agent collaboration for full-process automation—an excellent case study for AI developers.

No ChatGPT account? No problem. Learn how to connect DeepSeek and other Chinese LLMs to Codex using the Codex++ management tool — including Base URL setup, API Key creation, and token top-up.