codex-review-loop

A dual AI code review loop improves software quality by having one AI phase plan and implement code while another validates and cross-reviews it. This continuous feedback cycle iteratively remediates bugs and enforces architecture standards.

To set up an automated plan and verify loop, initiate a command instructing the AI to sequence through planning, implementation, validation, and review phases. The loop iterates until defined quality criteria are fully met.

Yes, you can choose different AI models for code generation and validation. The loop supports multiple model options including gpt-5.2-codex, gpt-5.1-codex-mini, and gpt-5.1-codex-max to balance cost versus capability.

Cross-review in an automated engineering workflow is a validation mechanism where an AI reviews the code implementation against the original plan. It ensures continuous verification between planning and execution phases to reduce bugs.

Recovery procedures during iterative code refinement are handled through explicit phase sequencing and safeguards built into the core loop. If validation fails, the loop applies remediation steps to recover and re-verify the code.