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  How to Use OpenAI Codex Inside Claude Code with MCP Claude Code is already capable of inspecting repositories, editing files, running commands, and coordinating complex engineering work. But there are times when you may want Claude to delegate a focused task to OpenAI Codex—for example: Ask Codex to implement a change while Claude reviews it. Use Codex for a second independent code review. Let Codex clean up a technical review document. Run a repeatable Codex skill from a Claude Code session. Use Claude as the orchestrator and Codex as a specialist execution agent. The cleanest way to build this workflow is through the Model Context Protocol , or MCP. However, the phrase “install Codex inside Claude” can create the wrong mental model. Codex is not inserted into the Claude model. Instead, Claude Code launches Codex as a separate local process and communicates with it through an MCP tool interface. Claude orchestrates. Codex executes. Claude verifies. Alt text: Claude Code connecte...

The Five-Gate Method: A Practical Framework for Building Reliable AI Agents AI models have become remarkably capable at writing code, generating content, and solving complex problems. Yet even the most advanced models can still fail in surprisingly simple ways. They may solve the wrong problem, rely on an incorrect assumption, verify the wrong thing, or present uncertain conclusions with unwarranted confidence. These aren't intelligence problems—they're workflow problems. The Five-Gate Method introduces a structured process that improves reliability by guiding AI agents through five checkpoints before declaring a task complete. Instead of asking an AI to simply "think harder," the method encourages disciplined execution. Why Reliability Matters In production systems, correctness matters more than impressive reasoning. A beautifully written answer still fails if it: misunderstood the objective never inspected the real data fixed the wrong issue assumed success...

Claude Code Best Practices for Large Codebases Using Claude Code on a large software project can initially feel confusing. A large codebase may contain thousands of files, multiple applications, different programming languages, old systems, shared libraries, and separate testing commands. However, Claude Code does not need to read the entire project at once. It works by navigating the live codebase, searching files, reading relevant code, following references, and collecting the context needed for the current task. Claude performs better when the project gives it a clear starting point and the task is limited to a relevant part of the codebase. 1. Start With a Small, Clearly Defined Task Do not begin with a broad instruction such as: “Review this entire repository and improve everything.” Instead, give Claude one specific task: Find where user authentication is implemented. Explain how the payment service works. Fix one reported bug. Add tests for one function. Refactor one module. Cla...