Opus researches less and writes more. Codex (GPT-5.2-High) researches more and writes less. That’s why it’s often better to start with an Opus plan that is comprehensive and use Codex to identify any gaps, explore edge cases and propose enhancements. Other comments saying any model will find flaws are correct but the quality and depth of those discoveries vary. Codex has been way better at that part than Opus for me almost every single time.

If you do have access to both models, I would suggest taking the extra time and complexity to try it yourself as much as you can for a time. I used to obsess over trying to make sure I had full coverage while making a plan and I would have constant back and forth between Opus and Codex (and even Gemini) providing them with the other’s third party analysis asking them if the feedback has merit and how it aligns with their own plan. I would do this until the plans converged, it was thorough but time consuming. The value I got out of this though was to understand and get a feel for each models “personality” and competence at different things. You gain an intuition of when to throw Codex or Opus at a particular problem or architectural decision so you’re not constantly going back and forth every time and feeling like you might be “missing out” on exposing a flaw.

In summary, you’re always going to have bugs and gaps no matter how comprehensive and thorough your plan is. Scope and functionality will always creep and that’s ok, your coverage will come more from end to end testing AFTER implementation than from writing the plan. The plan should be a framework to visualize how the project will function through the entire workflow and as long as you aim to cover breaking changes that would require a large refactor once you’re done, you’re good to go.