If you still use one model for everything, you usually pay in one of three ways: higher cost, slower delivery, or more rework. A better setup is role-based collaboration: Claude Code for planning and quality gates, Codex for fast implementation and batch edits. ...
如果你现在还在“一个模型干到底”，大概率会遇到三个问题：要么贵、要么慢、要么返工多。 更实用的做法是：把 Claude Code 和 Codex 当成两个不同岗位来配合——一个偏长链路规划和重构，一个偏快速代码落地和批量执行。 ...
MCP sounds great in theory, but real-world setup often fails at browser debugging: AI cannot reach Chrome, cannot inspect network requests, and cannot collect performance traces. This guide gives you a copy-paste setup that works on Windows + WSL. ...
如果你把 AI 只当“聊天工具”，三家看起来差不多；但一旦进入真实开发链路，差异会非常明显。 我的结论先放前面：日常编码+项目内改动优先 Codex，长文推理和方案拆解用 Claude，OpenAI CLI 适合做标准化自动化和跨工具串联。 ...
If you use AI as a chatbot only, these tools feel similar. In real engineering workflows, they behave very differently. My conclusion first: use Codex for repo-native coding changes, Claude for deep reasoning and long-form planning, and OpenAI CLI for standardized automation pipelines. ...