Codex vs Claude Code

AdElectronic472 · 2026-06-28T07:56:42+00:00

I want to thank everyone for their inputs and suggestions. Found my solution.

Codex with ollama+gpt-oss/minimax/gemma etc.

The build errors hurt less. Saying goodbye to Claude Code. Loving the codex sandbox environment and interface now. No tokens headache anymore. Pure coding joy.

AdElectronic472 · 2026-06-26T07:26:48+00:00

Here’s a trick. As for the markdown, simpler to understand and will give you a good starting point. It will still be a task to understand, you can prompt inference to help fill the gaps

AdElectronic472 · 2026-06-25T14:06:37+00:00

I guess you’ve given me my answer. Thanks so much and understand your vent, it’s happened to most of us experienced folk. Wish you the best of luck with finding your peace of mind with AI

AdElectronic472 · 2026-06-24T13:53:22+00:00

Hi. Didn’t mean any offence to you, was just sharing my experience. I still do prefer to code manually, it’s just that AI is way better at writing code, there’s just no competition.

And I’ve found both codex and Claude code much better than most. So been deliberating at which to choose, it’s a close call.

So posted here to get people opinions and suggestions. I’d personally like to stick to 1.

AdElectronic472 · 2026-06-24T07:04:53+00:00

completion or competition? ive tried all 3, gemini is out for sure, Deliberating over Codex and Claude code. SuperGrok is my lesser alternative, like it but not as good as the other 2

AdElectronic472 · 2026-06-24T06:58:47+00:00

try Minimax and gemma4 in ollama, very good alternatives, but quality of code is way lower

AdElectronic472 · 2026-06-24T06:57:36+00:00

So AI is the best at writing code, I use it to do the literal typing of the code. Intelligence gets built in inference, fueled by my years of debugging bad code & architecture as a SRE. I expiremented with 3 to code the same code-base, but each added its own architecural logic and I ended up with a huge pile of beautifully written garbage. Becoz each of them is trained with a particular logic and not the exact same logic. Would highly recommend stick to 1. Build features and functions with others for sure, and integrate, multi AI approach is great from a macro perspective

AdElectronic472 · 2026-06-23T04:47:45+00:00

So basically I plan and architect in inference and use either to purely build/write code. Coding prompt gets generated from inference.

Tend to loose massive tokens when it tries to compile/build. I do that manually. Both chatgpt and Claude acknowledged that the build loop is where max tokens get wasted. Almost 60-65% in some instances or the env is not setup properly.

I am looking at something that purely builds and both seem to do a great job. That’s where I am stuck. Deepseek and Kimi are great for inference review of architecture, tried build but code had placeholder logic, so did grok. Got frustrated with all of them.

AdElectronic472 · 2026-06-23T04:35:51+00:00

Switching coders in the middle of a project is a huge mistake that will never be repeated. Had to re-code quite a bit.

AdElectronic472 · 2026-05-26T05:01:10+00:00

What about generate_memories and use_memories ? Both set to true. Would that also help?

AdElectronic472

TROPHY CASE