A step-by-step workflow for using AI coding agents safely
A developer proposed a workflow for using like Claude, Codex, and Cursor in a production-safe way and asked the community for feedback. The process runs in stages. First, a human defines the feature to build. The AI agent then studies the existing codebase, asks clarifying questions, and drafts an .
A human reviews and refines that plan. Next, the AI generates test cases, and a human reviews them and adds any missing edge cases. The AI then implements the feature, but it must get human approval before making s and before performing any cloud or operations. It runs linting and tests, fixing issues on its own until everything passes.
Finally, a human does the final code review and merges the change. The design lets the AI handle planning, test writing, , and self-correction, while inserting human approval checkpoints at the highest-risk decision points.
Key points
- Flow: define feature → AI drafts plan → human reviews → AI writes tests → human adds edge cases → AI implements → human does final review and merges
- The AI agent studies the existing codebase and asks clarifying questions before drafting a plan
- s and cloud/ operations require explicit human approval before the AI proceeds
- The AI runs linting and tests and iterates on fixes on its own until everything passes
- The workflow assumes using multiple together — Claude, Codex (OpenAI), and Cursor