1. Frame the task
Define outcome, constraints, and acceptance tests before asking any model to generate code.
End-to-end workflow
How to run a high-quality vibe coding process
2. Generate first pass
Use GitHub Copilot or GPT-Codex for scaffolding. Keep prompts specific to architecture and style guides.
3. Cross-check with another model
Ask Claude Code or GPT-Codex to review for hidden risks and edge cases.
4. Validate in VS Code
Run tests, linting, type checks, and manual QA. Treat model output as draft code until proven.
5. Capture reusable prompts
Store successful prompts in your team docs so quality improves over time across projects.