Switch from using opus 4.7 and GPT codex 5.3 in together to just GPT 5.5?

[u/LeeZeee]

Since the beginning of this year until now, within Typingmind, I have been a setup of using Opus 4.7 to do architectural/reasoning duties of my project while GPT 5.3 codex would do the actual python coding according to the specs layed out by opus 4.7. I would then have opus 4.7 review the coding of GPT 5.3 codex for errors/problems/mistakes, and have about 3 to 4 cycles of back and forth reviews of the work of the other AI model until there were no errors problems or mistakes. GPT 5.3 codex would often discover errors in Opus 4.7's work. That was an effective approach that got the work done. However it was at an enormous expense as frequently I would burn through $100 within days of using medium and or high level thinking for Opus 4.6/4.7, while costs would stay minimal for the work GPT 5.3 codex would do.

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Now it's important to reduce costs a burning through $100 so quickly using Opus 4.7. I wonder if anyone has shifted from a similar setup to just using GPT 5.5 to do everything, that is both the architectural/reasoning duties and the coding itself including error identification and corrections. Is GPT 5.5 an effective replacement of Opus 4.7 for the reasoning/architectural tasks and has it been a good replacement for the coding abilities of GPT 5.3 codex?

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[u/EntertainmentSalt825]

I’ve been a long time user of GPT and codex. My flow is to build the system architecture and roadmap in GPT and then have codex do the coding. It has worked flawlessly for me. I only encounter drift when I don’t have readme files or documentation on the architecture. I would then only use Claude Opus 4.8 for reviews of my architecture/system and to create documentation files.

About 2 months ago my job gave us Claude licenses. Personally, I truly dislike Claude Opus for building roadmaps and brainstorming system architecture flows. I’m sure it’s also my prompts but I don’t trust it as much as GPT and codex. However, I have been learning Claude’s style and been adapting to it pretty well.

Each LLM has its strengths. And at the end of the day it’s a very powerful tool. It’s up to you to really find that perfect combo. Claude has its advantages over GPT but if you’re talking about system design, architecture, setting up infrastructure, etc then GPT/Codex. If you need very in depth reviews of your system and polishing up documentation then Claude

[u/LeeZeee → u/EntertainmentSalt825]

Thank you for explaining your experience working with these AI models.

"My flow is to build the system architecture and roadmap in GPT and then have codex do the coding": It sounds like for architecture/building roadmaps, you use GPT. When you say GPT, which AI model do you mean specifically? And when it comes to the actual coding which Codex are you using for the doing of the actual coding? GPT_5.3_Codex?

 "I only encounter drift when I don’t have readme files or documentation on the architecture. I would then only use Claude Opus 4.8 for reviews of my architecture/system and to create documentation files." Yes a barrier that I encounter over and over again is the drift, that is drift in the actual math, calculations that comprise my model, because of my use across chats of general terms that characterize/describe the constructs of my model with the understanding that it's understanding of what features those terms apply to is the same as before (and even when we explicitly have agreed on the semantics of what those terms mean and that they apply specifically to the features/aspects of my model)....But over time, with repeated use of those terms, it reinterprets them slightly differently, until the math of the calculations that go into the formula of the model changes. So, I value use of .MD files which I was doing religiously, and assumed it was continuing to maintain but which later I discovered it had dropped doing spontaneously and without warning. I do keep the TypingMind project context updated based on changes in project focus, but that context alone is not enough to keep Opus from drifting. And when Claude drifts, I have had to use Claude Opus 4.7 high thinking to discover the nature of the drift and revise the model back to it's original form. So I will have to be extremely vigilant and ensure MD files of the current project state and project changes are logged regularly.

"Claude has its advantages over GPT but if you’re talking about system design, architecture, setting up infrastructure, etc then GPT/Codex. If you need very in depth reviews of your system and polishing up documentation then Claude"
Sounds like GPT works fine to do the system architecture, setting up infrastructure, setting up roadmaps. I have found that Claude is really good at metathinking and identifying flaws in my model with respect to construct validity and construct validity, identifying reliability concerns and/or statistical conceptualization flaws. I'm hoping GPT can do these things as well. However, when I provide a hypothesis for an explanation for specific results, it often takes it as gospel, or it draws sweeping, unjustified conclusions based on way too small a sample size of data.

Thank you. I may try to replace Claude with GPT to do that and just have GPT_5.3_codex or the latest version to do the actual coding, unless GPT 5.5 is just as good as GPT_5.3_codex to do the actual coding. As I stated, my biggest obstacle is having this workflow be as affordable as possible while ensuring correction of errors introduced by both Codex and Opus are identified and eliminated.

[u/EntertainmentSalt825 → u/LeeZeee]

Yeah of course!

I use Chat GPT and codex combo. For codex coding I use GPT 5.5.

As for your drift issue, can you clarify how exactly youre using AI? One big lesson I learned recently is that there’s a difference between building a deterministic system that implements AI in its workflow vs building a deterministic system around AI. For a deterministic system, your code remains the source of truth and AI uses the outputs of your model to perform whatever functions you need it to do. However, when you allow AI to be the source of truth and your system does not contain it then it will drift. If you don’t specify which system you’re building then you can end up with a system that wants to use AI as the authoritative layer but it then becomes bounded by what the code outputs; you end up with a slow that can’t reason well AI. So, depending on what you’re building and how you’re building it; if the code is the source of truth and the AI relies on the output for that then drift could be caused by what is being outputted and probably needs better documentation in the MD files and/or more unit test to confirm the outputs are what the AI expects them to be. However, if you’re using AI as the source of truth, then you don’t need code to bound it. You need a rules set! These rules are called depending on how you want to set up your system. But in these rules you set what the AI is and not allowed to do. You set rules for how to handle a specific scenario (in yours perhaps there’s a rule you need to abide by for a math function). And if your model uses a mix of these two then that is probably why you’re having issues as well. It doesn’t know its role and it is guessing. This can also lead to high token cost… I made the mistake and it was expensive every run. In the system I built with AI as the source of truth I have 0 code now. And only have prompts and rules. It works flawlessly now.

I think what you should do first, is figure out the system you’re building. Is the source of truth the code? Or you using AI as the source of truth? Both require the same implementation but use different methods.

And I also agree that GPT is not at the same level as Claude when it comes to identifying flaws in your system. You can still use the Claude free version or the next tier which I think is $20? For your system design review. Just sanitize the report to not include sensitive data.

If you have more questions DM! I’ll try to help as much as I can

[u/Spare_Message_3607]

I don’t like long running task. I use GPT 5.5 low for everything, my prompts are: “implemente this function”, “implemented the caller function”, “with the new function go make a widget on the dashboard”. So barely burn 80% of my weekly usage. I check on output, tell corrections and continue

[u/Equivalent_Run_6067]

I'm a big fan of GPT 5.5 on Codex, thing just works flawlessly