423 related articles

Master OpenAI Codex end-to-end: CLI setup, slash commands, AGENTS.md design, MCP protocol, multi-agent coordination, and enterprise plugin development.

Claude Code is Anthropic's local AI programming assistant that reads your entire codebase, auto-debugs, and delivers far higher accuracy than Cursor and Trae. Here's why it's the strongest AI coding tool today.

Claude Code, Codex, or Cursor? This in-depth comparison covers each tool's positioning, ideal users, and how to combine them for maximum productivity in your AI coding workflow.

Is Cursor's $20 Pro plan enough? This deep dive breaks down fast vs. slow requests, compares ChatGPT and Claude quotas, and helps developers decide whether to subscribe.

Hands-on with GPT-5.6 Sol: auto-generate real-time voice anime characters from one prompt, write physics engines from scratch, and build unfamiliar toolchains autonomously. In-depth review of coding, agentic tasks, benchmarks, and its hallucination weakness.

How to learn AI coding from scratch? This article breaks down a four-week framework for Codex and AI Agents: master core skills, build workflows, develop Agents, and complete real projects.

An in-depth analysis of the AI-driven software testing paradigm: with Skill and CLI as the core hub, supporting both platformized management and digital employees, helping testing teams transform from script writers into capability builders.

Major players are pulling companion agents en masse, exposing the triple dilemma of high consumption, low payment, and poor retention. A deep dive from Character.ai's financials to the "Day 30 death" phenomenon.

Andrew Ng partners with JetBrains to launch a Spec-Driven Development course, teaching how to direct AI coding agents via spec files to boost intent fidelity and build maintainable production apps.

An in-depth guide to building an AI-driven second brain with Obsidian + Hermes Agent. Covers living files, VPS deployment, core memory mechanisms, and skill visualization.

A systematic guide to Coze's positioning and capabilities, covering Agent-building platform categories, Skill modules, workflow orchestration, and multi-Agent team building.

A developer stress-tested GPT-5.6 for six weeks across 67 projects, burning $180K-$240K in inference. Real cases of task persistence, Rust rewrites, autonomous browser control — plus honest frontend and 3D shortfalls.

Browser Use is an open-source AI Agent framework that lets LLMs autonomously drive browser operations via natural language. This article breaks down its four-layer architecture, core Agent loop, CDP perception layer, dynamic Tools dispatch, and its Skills, Sandbox, and MCP extension capabilities.

Many enterprises fail at AI Agents due to choosing the wrong tools and lacking methodology. This article outlines an eight-step Agent development method—from cognitive foundations, scenario selection, hand-writing ReAct, and structured output to Tool Use, RAG, evaluation sets, and production fallback.

OpenAI launches the GPT-5.6 model family (Sol/Terra/Luna) and ChatGPT Work, enabling automated financial analysis, local file operations, Codex coding, and cross-app workflows—AI officially becomes a real work partner.

OpenAI merged Codex into ChatGPT, killing a developer-beloved AI coding brand. A deep dive into the gains and losses of this brand consolidation.

When an intern uses AI to generate professional-looking slop code, stand-ups balloon from 15 to 45 minutes. This article dissects why AI slop is hard to spot and offers practical team solutions.

OpenAI releases the GPT-5.6 series (Sol/Terra/Luna), with flagship Sol directly handling smaller model Luna's post-training—marking recursive AI self-improvement in practice. A deep dive into performance, cost, ChatGPT Work, and computer use design leaps.

Developer Theo spent ~$200K over 6 weeks testing GPT-5.6 across 67 projects — from 20-hour autonomous coding runs to fixing boot partitions and Rust rewrites.

A deep dive into OpenAI Codex's cloud workflow: using a Next.js project to demo Ask/Code modes, auto-generating Pull Requests, and locally verifying merges for AI-assisted development.